Surgical instrument with user adaptable techniques

Description

TECHNICAL FIELD

The present disclosure generally relates to ultrasonic surgical systems and, more particularly, to ultrasonic and electrosurgical systems that allows surgeons to perform cutting and coagulation and adapt and customize techniques for performing such procedures based on the type of tissue being treated, employing multiple energy modalities based on tissue parameters, based on tissue impedance, and employing simultaneous energy modalities based on tissue parameters.

BACKGROUND

Ultrasonic surgical instruments are finding increasingly widespread applications in surgical procedures by virtue of the unique performance characteristics of such instruments. Depending upon specific instrument configurations and operational parameters, ultrasonic surgical instruments can provide substantially simultaneous cutting of tissue and hemostasis by coagulation, desirably minimizing patient trauma. The cutting action is typically realized by an-end effector, or blade tip, at the distal end of the instrument, which transmits ultrasonic energy to tissue brought into contact with the end effector. Ultrasonic instruments of this nature can be configured for open surgical use, laparoscopic, or endoscopic surgical procedures including robotic-assisted procedures.

Some surgical instruments utilize ultrasonic energy for both precise cutting and controlled coagulation. Ultrasonic energy cuts and coagulates by vibrating a blade in contact with tissue. Vibrating at high frequencies (e.g., 55,500 times per second), the ultrasonic blade denatures protein in the tissue to form a sticky coagulum. Pressure exerted on tissue with the blade surface collapses blood vessels and allows the coagulum to form a hemostatic seal. The precision of cutting and coagulation is controlled by the surgeon's technique and adjusting the power level, blade edge, tissue traction, and blade pressure.

Electrosurgical devices for applying electrical energy to tissue in order to treat and/or destroy the tissue are also finding increasingly widespread applications in surgical procedures. An electrosurgical device typically includes a hand piece, an instrument having a distally-mounted end effector (e.g., one or more electrodes). The end effector can be positioned against the tissue such that electrical current is introduced into the tissue. Electrosurgical devices can be configured for bipolar or monopolar operation. During bipolar operation, current is introduced into and returned from the tissue by active and return electrodes, respectively, of the end effector. During monopolar operation, current is introduced into the tissue by an active electrode of the end effector and returned through a return electrode (e.g., a grounding pad) separately located on a patient's body. Heat generated by the current flowing through the tissue may form hemostatic seals within the tissue and/or between tissues and thus may be particularly useful for sealing blood vessels, for example. The end effector of an electrosurgical device also may include a cutting member that is movable relative to the tissue and the electrodes to transect the tissue.

Electrical energy applied by an electrosurgical device can be transmitted to the instrument by a generator in communication with the hand piece. The electrical energy may be in the form of radio frequency (“RF”) energy. RF energy is a form of electrical energy that may be in the frequency range of 200 kilohertz (kHz) to 1 megahertz (MHz). In application, an electrosurgical device can transmit low frequency RF energy through tissue, which causes ionic agitation, or friction, in effect resistive heating, thereby increasing the temperature of the tissue. Because a sharp boundary is created between the affected tissue and the surrounding tissue, surgeons can operate with a high level of precision and control, without sacrificing un-targeted adjacent tissue. The low operating temperatures of RF energy is useful for removing, shrinking, or sculpting soft tissue while simultaneously sealing blood vessels. RF energy works particularly well on connective tissue, which is primarily comprised of collagen and shrinks when contacted by heat.

The RF energy may be in a frequency range described in EN 60601-2-2:2009+A11:2011, Definition 201.3.218—HIGH FREQUENCY. For example, the frequency in monopolar RF applications may be typically restricted to less than 5 MHz. However, in bipolar RF applications, the frequency can be almost anything. Frequencies above 200 kHz can be typically used for monopolar applications in order to avoid the unwanted stimulation of nerves and muscles that would result from the use of low frequency current. Lower frequencies may be used for bipolar applications if the risk analysis shows the possibility of neuromuscular stimulation has been mitigated to an acceptable level. Normally, frequencies above 5 MHz are not used in order to minimize the problems associated with high frequency leakage currents. Higher frequencies may, however, be used in the case of bipolar applications. It is generally recognized that 10 mA is the lower threshold of thermal effects on tissue.

A challenge of using these medical devices is the inability to control and customize the power output depending on the type of tissue being treated by the devices. It would be desirable to provide a surgical instrument that overcomes some of the deficiencies of current instruments. The surgical system described herein overcomes those deficiencies.

SUMMARY

In one aspect, a surgical instrument for coagulating and dissecting tissue is provided. The surgical instrument comprising a processor; an end effector at a distal end of the surgical instrument, the end effector configured to interact with tissue, the end effector comprising: a clamp arm; an ultrasonic blade; a force sensor in communication with the processor and configured to measure a force applied to tissue located between the clamp arm and the ultrasonic blade; and a temperature sensor in communication with the processor; an ultrasonic transducer acoustically coupled to the ultrasonic blade and configured to receive a drive signal from a generator to cause ultrasonic motion of the ultrasonic blade and deliver energy to the ultrasonic blade; wherein the processor is configured to: determine a type of tissue interacting with the end effector based on a tissue coefficient of friction, wherein the tissue coefficient of friction is determined based on the force applied to the tissue by the end effector, the ultrasonic motion of the ultrasonic blade, and a rate of heat generated by the end effector; and dynamically control the drive signal delivered to the ultrasonic transducer based on the type of tissue interacting with the end effector.

In one aspect, a method for detecting a short circuit in a surgical system configured to apply radio frequency energy and ultrasonic energy to a target surgical site is provided. The method comprises applying radio frequency (RF) energy with an end effector to the target surgical site; transitioning from applying the RF energy to applying ultrasonic energy with the end effector to the target surgical site; transmitting an exploratory ultrasonic pulse to the surgical site; measuring an ultrasonic property about the ultrasonic pulse upon transmission to the surgical site; determining whether the ultrasonic property is consistent with a behavior of low impedance tissue when ultrasonic energy is applied to the low impedance tissue; and continuing to apply ultrasonic energy to cut the low impedance tissue if it is determined that the ultrasonic property is consistent with ultrasonic energy being applied to low impedance tissue.

According to aspects of the present application, during tissue treatment, a parameterized tissue model can be fitted to the tissue. The parameters that are found in the model can be used to generate an optimal controller in real-time and could also be correlated to specific tissue characteristics. The present application provides real-time optimization on a generator control system based on RF impedance and real-time tissue evaluation.

According to aspects of the present application, methods of system identification may be used to model the tissue in real-time and develop controllers in real-time, specific to a particular tissue type to maximize sealing, minimize sticking of tissue, and cycle times. Furthermore, control of the output of a surgical instrument based on tissue characteristics and changes in tissue during sealing and cutting cycles is provided.

According to one aspect, a surgical instrument uses an RF energy modality to sense tissue characteristics, such as impedance, and the changes of the tissue characteristics to modulate the output power of an ultrasonic tissue treating system. Specifically, the output power of a surgical instrument may be modulated as a function of a desired impedance trajectory where the impedance trajectory results in a desired tissue effect or outcome. In one aspect, the RF output may be therapeutic, e.g. tissue treating, or sub-therapeutic, e.g. sensing only. The RF output may be applied to the tissue and the voltage and current, or representations of the voltage and current, are measured or estimated. The impedance may be calculated by determining the ratio of the voltage to the current.

In addition, RF impedance is known to change during the heating and coagulation of tissue. RF impedance can be used as an indicator of the state of the tissue and therefore can be used to indicate progress in a coagulation cycle, vessel sealing cycle, cutting etc. An extension of this change in RF impedance can be used to form a desired treatment cycle if the output is modulated such that the RF impedance follows a particular, desired course of change in impedance. The desired course of impedance can be pre-determined based on the instrument's operating parameters or determined by selection of the surgeon or measurement of tissue parameters to set this course of treatment. The course of impedance can determine one or more of the output power, output waveform or waveshape, selection of energy mode or modality or a point to terminate the application of energy to tissue.

In one aspect, a surgical energy generator system is disclosed, the system comprises an ultrasonic output stage configured to drive a transducer coupled to a tissue treating portion of a surgical instrument, where the tissue treating portion applies vibrational energy to tissue to affect treatment of that tissue and vibration amplitude of the tissue treating portion is controlled by a controller; an RF output stage configured to supply electrosurgical energy to the tissue via at least one electrode configured to apply electrosurgical energy to the tissue; sensing circuitry configured to measure impedance of the tissue; and a controller programmed to determine whether a tissue reaction has occurred as a function of impedance values and a predetermined rise in impedance, where the tissue reaction corresponds to a boiling point of tissue fluid, to generate a target impedance trajectory as a function of measured impedance and a predetermined desired rate of change of impedance based on the tissue reaction determination, where the target impedance trajectory includes a plurality of target impedance values for each of a plurality of timesteps, and to drive tissue impedance along the target impedance trajectory by adjusting the output level of the ultrasonic output stage to substantially match tissue impedance to a corresponding target impedance value for at least a predetermined minimum time period.

In one aspect, an apparatus is provided for dissecting and coagulating tissue. The apparatus comprises: a surgical instrument having an end effector configured to interact with a tissue at a distal end thereof; a generator electrically coupled to the surgical instrument and configured to deliver radio frequency (RF) energy and ultrasonic energy to the end effector to allow the end effector to interact with the tissue; wherein the energy delivered to the end effector switches between RF energy and ultrasonic energy based on a determination of a tissue impedance of the tissue interacting with the end effector such that the generator switches from RF energy to ultrasonic energy when the tissue impedance reaches a threshold level.

In addition to the foregoing, various other method and/or system and/or program product aspects are set forth and described in the teachings such as text (e.g., claims and/or detailed description) and/or drawings of the present disclosure.

The foregoing is a summary and thus may contain simplifications, generalizations, inclusions, and/or omissions of detail; consequently, those skilled in the art will appreciate that the summary is illustrative only and is NOT intended to be in any way limiting. Other aspects, features, and advantages of the devices and/or processes and/or other subject matter described herein will become apparent in the teachings set forth herein.

In one or more various aspects, related systems include but are not limited to circuitry and/or programming for effecting herein-referenced method aspects; the circuitry and/or programming can be virtually any combination of hardware, software, and/or firmware configured to affect the herein-referenced method aspects depending upon the design choices of the system designer. In addition to the foregoing, various other method and/or system aspects are set forth and described in the teachings such as text (e.g., claims and/or detailed description) and/or drawings of the present disclosure.

Further, it is understood that any one or more of the following-described forms, expressions of forms, examples, can be combined with any one or more of the other following-described forms, expressions of forms, and examples.

The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

FIGURES

The novel features of the described forms are set forth with particularity in the appended claims. The described forms, however, both as to organization and methods of operation, may be best understood by reference to the following description, taken in conjunction with the accompanying drawings in which:

FIG. 1 illustrates one aspect of a surgical system comprising a generator and various surgical instruments usable therewith;

FIG. 2 is a diagram of one aspect of the ultrasonic surgical instrument of FIG. 16;

FIG. 3 is a diagram of one aspect of the surgical system of FIG. 16;

FIG. 4 is a model illustrating one aspect of a motional branch current;

FIG. 5 is a structural view of one aspect of a generator architecture;

FIG. 6 illustrates one aspect of a drive system of a generator, which creates the ultrasonic electrical signal for driving an ultrasonic transducer;

FIG. 7 illustrates one aspect of a drive system of a generator comprising a tissue impedance module;

FIG. 8 illustrates one aspect of a generator for delivering multiple energy modalities to a surgical instrument;

FIG. 9 is an example graph of two waveforms of energy from one aspect of a generator;

FIG. 10 is an example graph of the sum of the waveforms of FIG. 9;

FIG. 11 is an example graph of sum of the waveforms of FIG. 9 with the RF waveform dependent on the ultrasonic waveform;

FIG. 12 is an example graph of the sum of the waveforms of FIG. 9 with the RF waveform being a function of the ultrasonic waveform;

FIG. 13 is an example graph of a complex RF waveform;

FIG. 14 illustrates one aspect of an end effector comprising RF data sensors located on the clamp arm;

FIG. 15 illustrates one aspect of the flexible circuit shown in FIG. 14 in which the sensors may be mounted to or formed integrally therewith;

FIG. 16 is a cross-sectional view of the flexible circuit shown in FIG. 15;

FIG. 17 illustrates one aspect of a segmented flexible circuit configured to fixedly attach to a clamp arm of an end effector;

FIG. 18 illustrates one aspect of a segmented flexible circuit configured to mount to a clamp arm of an end effector;

FIG. 19 illustrates one aspect of an end effector configured to measure a tissue gap G_T;

FIG. 20 illustrates one aspect of a left-right segmented flexible circuit;

FIG. 21 illustrates one aspect of an end effector comprising segmented flexible circuit as shown in FIG. 20;

FIG. 22 illustrates the end effector shown in FIG. 21 with the clamp arm clamping tissue between the clamp arm and the ultrasonic blade;

FIG. 23 illustrates graphs of energy applied by the right and left side of an end effector based on locally sensed tissue parameters;

FIG. 24 illustrates a graph depicting one aspect of adjustment of threshold due to the measurement of a secondary tissue parameter such as continuity, temperature, pressure, and the like;

FIG. 25 is a cross-sectional view of one aspect of a flexible circuit comprising RF electrodes and data sensors embedded therein;

FIG. 26 is a cross-sectional view of one aspect of an end effector configured to sense force or pressure applied to tissue located between a clamp arm and an ultrasonic blade;

FIG. 27 is a schematic diagram of one aspect of a signal layer of a flexible circuit;

FIG. 28 is a schematic diagram of sensor wiring for the flexible circuit shown in FIG. 27;

FIG. 29 is a schematic diagram of one aspect of an RF energy drive circuit;

FIG. 30 is a graphical representation of measuring tissue gap at a preset time;

FIG. 31 is a time to preset force versus time graph for thin, medium, and thick tissue types;

FIG. 32 is a graphical depiction of a graph of three curves, where the first curve represents power (P), voltage (V_RF), and current (I_RF) versus tissue impedance (Z), the second curve and third curve represent tissue impedance (Z) versus time (t);

FIG. 33 is a plan view of one aspect of an end effector;

FIG. 34 is a side view of the end effector shown in FIG. 33 with a partial cut away view to expose the underlying structure of the clamp arm and an ultrasonic blade;

FIG. 35 is partial sectional view of the end effector shown in FIGS. 33, 34 to expose the ultrasonic blade and right and left electrodes, respectively;

FIG. 36 is a cross-sectional view taken at section 36-36 of the end effector shown in FIG. 33;

FIG. 37 is cross-sectional view taken at section 37-37 of the end effector shown in FIG. 33;

FIG. 38 is a cross-sectional view taken at section 36-36 of the end effector shown in FIG. 33, except that the ultrasonic blade has a different geometric configuration;

FIG. 39 is cross-sectional view taken at section 37-37 of the end effector shown in FIG. 33, except that the ultrasonic blade has a different geometric configuration;

FIG. 40 is a cross-sectional view taken at section 36-36 of the end effector shown in FIG. 33, except that the ultrasonic blade has a different geometric configuration;

FIG. 41 is cross-sectional view taken at section 37-37 of the end effector shown in FIG. 33, except that the ultrasonic blade has a different geometric configuration;

FIG. 42A is a graphical representation of one aspect of a medical device surrounding tissue;

FIG. 42B is a graphical representation of one aspect of a medical device compressing tissue;

FIG. 43A is a graphical representation of one aspect of a medical device compressing tissue;

FIG. 43B also depicts example forces exerted by one aspect of an end-effector of a medical device compressing tissue;

FIG. 44 illustrates a logic diagram of one aspect of a feedback system;

FIG. 45 is a graph of power versus force as measured with a plurality of plot points for various tissue types;

FIG. 46 is another graph of power versus force as measured with a plurality of plot points for various tissue types;

FIG. 47 is a logic flow diagram of one aspect of dynamically changing the energy delivered to a surgical instrument based on a determination of tissue type being treated by the instrument;

FIG. 48 is a logic flow diagram of one aspect of dynamically changing the energy delivered to a surgical instrument based on a determination of tissue type being treated by the instrument;

FIG. 49 is a logic flow diagram of one aspect of a method of dynamically changing the energy delivered to a surgical instrument based on a determination of the hydration level of tissue being treated by a surgical instrument;

FIG. 50 is a logic flow diagram of one aspect of a method of dynamically changing energy being delivered from a generator based on the type of tissue being treated by a surgical instrument and various characteristics of the tissue;

FIG. 51 is a logic flow diagram of one aspect of a technique for dynamically changing the energy delivered from a generator based on aperture defined by the end effector and energy parameters;

FIG. 52 is a logic flow diagram of one aspect of a technique for dynamically changing the energy delivered from a generator based on aperture defined by the end effector and energy parameters;

FIG. 53 is a logic flow diagram of one aspect of a dynamic tissue sensing technique;

FIG. 54 is a logic flow diagram of one aspect of a process for sealing or sealing and cutting large vessels or large tissue bundles;

FIG. 55 is a logic flow diagram of one aspect of a process for sealing or sealing and cutting large vessels or large tissue bundles by dynamically changing energy being delivered from the generator during the treatment of the tissue based on the changing aperture defined by the end effector;

FIG. 56 is a logic flow diagram of one aspect of a process for sealing or sealing and cutting large vessels or large tissue bundles by dynamically communicating energy parameters to the generator during the treatment of the tissue based on the changing aperture defined by the end effector of the surgical instrument;

FIG. 57 is a logic flow diagram of a technique to seal or seal and cut vessels using RF and ultrasonic energy in conjunction with tissue impedance measurements and the aperture defined by the clamp jaw measurements;

FIG. 58 is a logic flow diagram of one aspect of a method of dynamically changing the energy delivered to a surgical instrument based on a determination of a state of coagulation of tissue being treated by the surgical instrument;

FIG. 59 is a logic flow diagram of a technique to seal or seal and cut vessels using RF and ultrasonic energy in conjunction with tissue impedance measurements;

FIG. 60 is a logic flow diagram of a technique to seal or seal and cut vessels using RF and ultrasonic energy in conjunction with tissue impedance measurements and the aperture defined by the clamp jaw measurements;

FIG. 61 is a logic flow diagram of a technique for distinguishing a short circuit from low impedance tissue while utilizing RF energy by measuring voltage properties of an exploratory ultrasonic pulse;

FIG. 62 is a logic flow diagram of a technique for distinguishing a short circuit from low impedance tissue while delivering RF energy and measuring acoustic properties of an exploratory ultrasonic pulse, according to some aspects;

FIG. 63 is a logic flow diagram of a technique for conducting a tissue sealing technique without cutting by using a combination of ultrasonic energy and RF energy, according to some aspects;

FIG. 64 is a logic flow diagram of a technique for conducting a tissue sealing technique without cutting by using a combination of ultrasonic energy and RF energy, according to some aspects;

FIG. 65 is logic flow diagram of a technique for detecting low impedance tissue or metal shorts that may cause false short circuits in RF mode;

FIG. 66 is a timing diagram of a seal only pulse sequence illustrating a basic configuration of pulsing RF and ultrasonic energy for “Seal Only” mode;

FIG. 67 is a timing diagram of a seal only pulse sequence illustrating a basic configuration of pulsing RF and ultrasonic energy for “Seal Only” mode;

FIG. 68 is a timing diagram of a seal only pulse sequence;

FIG. 69 is a timing diagram of a seal only pulse sequence;

FIG. 70 is a timing diagram of a seal and cut pulse sequence, which begins and ends with ultrasonic energy pulses delivered at the same amplitude during the sealing a cutting cycles;

FIG. 71 is a timing diagram of a seal and cut pulse sequence, which begins and ends with ultrasonic energy pulses delivered at variable amplitude during the sealing a cutting cycles;

FIG. 72 is a timing diagram of a seal only pulse sequence where the ultrasonic energy pulse current is be set based on the impedance measured with the preceding RF energy pulse;

FIG. 73 is a logic flow diagram of a technique for delivering pulses of different energy modalities to tissue;

FIG. 74 is a logic flow diagram of a technique for delivering pulses of different energy modalities to tissue;

FIG. 75 is a logic flow diagram of a technique for delivering pulses of different energy modalities to tissue;

FIG. 76 is a logic flow diagram of one aspect of a process of applying simultaneous activation of different energy modalities to tissue;

FIG. 77 is a graphical representation of RF Impedance versus Time in connection with the logic flow diagram of FIG. 67 to illustrate the ultrasonic termination impedance;

FIG. 78 illustrates an example of the quality of a seal made in a vessel using the simultaneous activation of RF and ultrasonic energy modalities as described in connection with FIGS. 76 and 77;

FIG. 79 is a graphical representation of seal burst pressure of carotid bundles versus an RF only seal and a simultaneous RF/ultrasonic seal as described in connection with FIGS. 76-78;

FIG. 80 is a logic flow diagram of a process of simultaneous activation of RF and ultrasonic energy modalities;

FIG. 81 is a block diagram of one aspect describing the selection and application of composite load curves in a tissue seal control process;

FIG. 82 illustrates one aspect of a neural network for controlling a generator;

FIG. 83 is an example graph showing RF impedance versus time of tissue impedance at which a proper tissue seal is achieved using RF energy;

FIG. 84 is a graphical representation of RF impedance versus time of tissue impedance with 40 W of RF power delivered to tissue using a downhill simplex technique for a model of tissue and experimental data;

FIG. 85 is a graphical representation of RF impedance versus time of tissue impedance using a linear quadratic controller (LQR) with precompensation to achieve steady state at a tissue impedance equal to 250 Ohms for a model of tissue and experimental data;

FIG. 86 is a graphical representation of RF impedance versus time of tissue impedance using a linear quadratic controller (LQR) with precompensation to achieve steady state at a tissue impedance that rises at a rate of 50 Ohms/second for a model of tissue and experimental data;

FIG. 87 is a logic flow diagram of a method for identifying a tissue type and developing a control process to control the application of an energy modality to the tissue according to tissue impedance;

FIG. 88 is a logic flow diagram of a method for treating tissue based on tissue impedance according to one aspect of the present disclosure;

FIG. 89 is a graphical depiction of a tissue impedance function represented as tissue impedance |Z| (Ohms) as a function of time (Sec) showing one aspect of a termination impedance at which a proper tissue seal is achieved utilizing RF energy;

FIG. 90 is a logic flow diagram of one aspect of a method of dynamically changing the energy delivered to a surgical instrument based on a determination of a tissue impedance of tissue being treated by a surgical instrument;

FIG. 91A is a graphical depiction of power and impedance as a function of time delivered from a generator to an end effector of a surgical instrument;

FIG. 91B is a graphical depiction of voltage and current as a function of time delivered from a generator to an end effector of a surgical instrument;

FIG. 91C is a graphical depiction of power, impedance, voltage, and current as a function of time delivered from a generator to an end effector of a surgical instrument as shown in FIGS. 91A and 91B;

FIG. 92 is a logic flow diagram of one aspect of a process of applying simultaneous activation of different energy modalities to tissue;

FIG. 93 is a graphical depiction of an RF tissue impedance function represented as RF tissue impedance (Ohms) as a function of time (Sec) in connection with the logic flow diagram of FIG. 92 to illustrate the ultrasonic and RF termination impedance;

FIG. 94 illustrates an example of the quality of a seal made in a vessel utilizing simultaneous activation of RF and ultrasonic energy modalities as described in connection with FIGS. 92 and 93;

FIG. 95 is a boxplot graphic comparison of the burst pressure of a carotid artery seal made utilizing: (1) simultaneous application of RF and ultrasonic energy and (2) application of RF energy only as described in connection with FIGS. 92-94;

FIG. 96 is a boxplot graphic comparison of the burst pressure of a carotid artery bundle seal made utilizing: (1) simultaneous application of RF and ultrasonic energy and (2) application of RF energy only as described in connection with FIGS. 92-94;

FIG. 97 is a boxplot graphic comparison of the burst pressure of a thyrocervical artery seal made utilizing: (1) simultaneous application of RF and ultrasonic energy and (2) application of RF energy only as described in connection with FIGS. 92-94;

FIG. 98 is a boxplot graphic comparison of the burst pressure of a carotid artery bundle seal made utilizing simultaneous application of: (1) RF and lower ultrasonic energy and (2) RF energy and higher ultrasonic energy as described in connection with FIGS. 92-94;

FIG. 99 is a boxplot graphic comparison of the burst pressure of a carotid artery bundle seal made utilizing simultaneous application of RF and ultrasonic energy at different termination impedances as described in connection with FIGS. 92-94;

FIG. 100 is an example of a vessel with a partial seal made utilizing simultaneous application of RF and ultrasonic energy and a partial transection made utilizing ultrasonic energy;

FIG. 101 is a graphical depiction of an RF tissue impedance function represented as RF tissue impedance (Ohms) as a function of time (Sec) and an ultrasonic current function represented as ultrasonic current (mA) as a function of time (Sec) during a “seal only” modality;

FIG. 102 is logic flow diagram of one aspect of a technique for simultaneous activation of RF and ultrasonic energy and modulating the ultrasonic energy to achieve a seal only process;

FIG. 103 is a graphical depiction of an RF tissue impedance function represented as RF tissue impedance (Ohms) as a function of time (Sec) and an ultrasonic current function represented as ultrasonic current (mA) as a function of time (Sec) during a “seal and cut” modality;

FIG. 104 is logic flow diagram of one aspect of a technique for simultaneous activation of RF and ultrasonic energy and modulating the ultrasonic energy to achieve a seal and cut process;

FIG. 105A is a graphical depiction of an ultrasonic current functions represented as ultrasonic current I_h(Amperes) delivered to the ultrasonic transducer as a function of RF tissue impedance Z (Ohms) for various n values;

FIG. 105B is a graphical depiction of an ultrasonic current functions represented as ultrasonic current I_h(Amperes) delivered to the ultrasonic transducer as a function of RF tissue impedance Z (Ohms) for various n values;

FIG. 106 is a graphical depiction of multiple ultrasonic functions represented as functions of time; and

FIG. 107 is a graphical depiction of constant RF power that was inputted into Equation 9 with RF energy terminated at 500 Ohm terminal impedance.

DESCRIPTION

Before explaining various forms of surgical instruments in detail, it should be noted that the illustrative forms are not limited in application or use to the details of construction and arrangement of parts illustrated in the accompanying drawings and description. The illustrative forms may be implemented or incorporated in other forms, variations and modifications, and may be practiced or carried out in various ways. Further, unless otherwise indicated, the terms and expressions employed herein have been chosen for the purpose of describing the illustrative forms for the convenience of the reader and are not for the purpose of limitation thereof.

Various forms are directed to improved ultrasonic and/or electrosurgical (RF) instruments configured for effecting tissue dissecting, cutting, and/or coagulation during surgical procedures. In one form, a combined ultrasonic and electrosurgical instrument may be configured for use in open surgical procedures, but has applications in other types of surgery, such as laparoscopic, endoscopic, and robotic-assisted procedures. Versatile use is facilitated by selective use of ultrasonic and RF energy.

The various forms will be described in combination with an ultrasonic instrument as described herein. Such description is provided by way of example, and not limitation, and is not intended to limit the scope and applications thereof. For example, any one of the described forms is useful in combination with a multitude of ultrasonic instruments including those described in, for example, U.S. Pat. Nos. 5,938,633; 5,935,144; 5,944,737; 5,322,055; 5,630,420; and 5,449,370.

As will become apparent from the following description, it is contemplated that forms of the surgical instruments described herein may be used in association with an oscillator unit of a surgical system, whereby ultrasonic energy from the oscillator unit provides the desired ultrasonic actuation for the present surgical instrument. It is also contemplated that forms of the surgical instrument described herein may be used in association with a signal generator unit of a surgical system, whereby electrical energy in the form of radio frequencies (RF), for example, is used to provide feedback to the user regarding the surgical instrument. The ultrasonic oscillator and/or the signal generator unit may be non-detachably integrated with the surgical instrument or may be provided as separate components, which can be electrically attachable to the surgical instrument.

One form of the present surgical apparatus is particularly configured for disposable use by virtue of its straightforward construction. However, it is also contemplated that other forms of the present surgical instrument can be configured for non-disposable or multiple uses. Detachable connection of the present surgical instrument with an associated oscillator and signal generator unit is presently disclosed for single-patient use for illustrative purposes only. However, non-detachable integrated connection of the present surgical instrument with an associated oscillator and/or signal generator unit is also contemplated. Accordingly, various forms of the presently described surgical instruments may be configured for single use and/or multiple use with either detachable and/or non-detachable integral oscillator and/or signal generator unit, without limitation, and all combinations of such configurations are contemplated to be within the scope of the present disclosure.

The surgical instruments disclosed herein are related to surgical instruments described in the following commonly owned applications and filed Jun. 9, 2016: U.S. patent application Ser. No. 15/177,439, titled “Surgical System Wth User Adaptable Techniques” by Stulen et al., U.S. patent application Ser. No. 15/177,449, titled “Surgical System With User Adaptable Techniques Employing Multiple Energy Modalities Based On Tissue Parameters” by Wiener et al., U.S. patent application Ser. No. 15/177,456, titled “Surgical System With User Adaptable Techniques Based On Tissue Impedance” by Yates et al., and U.S. paten application Ser. No. 15/177,466, titled “Surgical System With User Adaptable Techniques Employing Simultaneous Energy Modalities Based On Tissue Parameters” by Yates et al., each of which is incorporated herein by reference in its entirety.

With reference to FIGS. 1-5, one form of a surgical system 10 including an ultrasonic surgical instrument is illustrated. FIG. 1 illustrates one form of a surgical system 100 comprising a generator 102 and various surgical instruments 104, 106, 108 usable therewith. FIG. 2 is a diagram of the ultrasonic surgical instrument 104 of FIG. 1.

FIG. 1 illustrates a generator 102 configured to drive multiple surgical instruments 104, 106, 108. The first surgical instrument 104 comprises a handpiece 105, an ultrasonic transducer 120, a shaft 126, and an end effector 122. The end effector 122 comprises an ultrasonic blade 128 acoustically coupled to the transducer 120 and a clamp arm 140. The handpiece 105 comprises a trigger 143 to operate the clamp arm 140 and a combination of the toggle buttons 134a, 134b, 134c to energize and drive the ultrasonic blade 128 or other function. The toggle buttons 134a, 134b, 134c can be configured to energize the ultrasonic transducer 120 with the generator 102.

Still with reference to FIG. 1, the generator 102 also is configured to drive a second surgical instrument 106. The second surgical instrument 106 is an RF electrosurgical instrument and comprises a handpiece 107, a shaft 127, and an end effector 124. The end effector 124 comprises electrodes in the clamp arms 143 and return through the ultrasonic blade 149. The electrodes are coupled to and energized by a bipolar energy source within the generator 102. The handpiece 107 comprises a trigger 147 to operate the clamp arm 145 and an energy button 135 to actuate an energy switch to energize the electrodes in the end effector 124.

Still with reference to FIG. 1, the generator 102 also is configures to drive a combination electrosurgical and ultrasonic instrument 108. The combination electrosurgical and ultrasonic multifunction surgical instrument 108 comprises a handpiece 109, a shaft 129, and an end effector 125. The end effector comprises an ultrasonic blade 149 and a clamp arm 145. The ultrasonic blade 149 is acoustically coupled to the ultrasonic transducer 120. The handpiece 109 comprises a trigger 147 to operate the clamp arm 145 and a combination of the toggle buttons 137a, 137b, 137c to energize and drive the ultrasonic blade 149 or other function. The toggle buttons 137a, 137b, 137c can be configured to energize the ultrasonic transducer 120 with the generator 102 and energize the ultrasonic blade 149 with a bipolar energy source also contained within the generator 102.

Wth reference to both FIGS. 1 and 2, the generator 102 is configurable for use with a variety of surgical devices. According to various forms, the generator 102 may be configurable for use with different surgical devices of different types including, for example, the ultrasonic surgical instrument 104, the electrosurgical or RF surgical devices, such as, the RF electrosurgical instrument 106, and the multifunction surgical instrument 108 that integrate electrosurgical RF and ultrasonic energies delivered simultaneously from the generator 102. Although in the form of FIG. 1, the generator 102 is shown separate from the surgical instruments 104, 106, 108, in one form, the generator 102 may be formed integrally with either of the surgical instrument 104, 106, 108 to form a unitary surgical system. The generator 102 comprises an input device 110 located on a front panel of the generator 102 console. The input device 110 may comprise any suitable device that generates signals suitable for programming the operation of the generator 102. The generator 102 also may comprise one or more output devices 112.

The generator 102 is coupled to an ultrasonic transducer 120 via a cable 144. The ultrasonic transducer 120 and a waveguide extending through a shaft 126 (waveguide not shown in FIG. 2) may collectively form an ultrasonic drive system driving an ultrasonic blade 128 of an end effector 122. The end effector 122 further may comprise a clamp arm 140 to clamp tissue between the clamp arm 140 and the ultrasonic blade 128. In one form, the generator 102 may be configured to produce a drive signal of a particular voltage, current, and/or frequency output signal that can be stepped or otherwise modified with high resolution, accuracy, and repeatability.

Still with reference to FIG. 2, It will be appreciated that a surgical instrument 104 may comprise any combination of the toggle buttons 134a, 134b, 134c. For example, the surgical instrument 104 could be configured to have only two toggle buttons: a toggle button 134a for producing maximum ultrasonic energy output and a toggle button 134c for producing a pulsed output at either the maximum or less than maximum power level. In this way, the drive signal output configuration of the generator 102 could be 5 continuous signals and 5 or 4 or 3 or 2 or 1 pulsed signals. In certain forms, the specific drive signal configuration may be controlled based upon, for example, EEPROM settings in the generator 102 and/or user power level selection(s).

In certain forms, a two-position switch may be provided as an alternative to a toggle button 134c. For example, a surgical instrument 104 may include a toggle button 134a for producing a continuous output at a maximum power level and a two-position toggle button 134b. In a first detented position, toggle button 134b may produce a continuous output at a less than maximum power level, and in a second detented position the toggle button 134b may produce a pulsed output (e.g., at either a maximum or less than maximum power level, depending upon the EEPROM settings).

Still with reference to FIG. 2, forms of the generator 102 may enable communication with instrument-based data circuits. For example, the generator 102 may be configured to communicate with a first data circuit 136 and/or a second data circuit 138. For example, the first data circuit 136 may indicate a burn-in frequency slope, as described herein. Additionally or alternatively, any type of information may be communicated to second data circuit for storage therein via a data circuit interface (e.g., using a logic device). Such information may comprise, for example, an updated number of operations in which the instrument has been used and/or dates and/or times of its usage. In certain forms, the second data circuit may transmit data acquired by one or more sensors (e.g., an instrument-based temperature sensor). In certain forms, the second data circuit may receive data from the generator 102 and provide an indication to a user (e.g., an LED indication or other visible indication) based on the received data. The second data circuit 138 contained in the multifunction surgical instrument 108 of a surgical device. In some forms, the second data circuit 138 may be implemented in a many similar to that of the first data circuit 136 described herein. An instrument interface circuit may comprise a second data circuit interface to enable this communication. In one form, the second data circuit interface may comprise a tri-state digital interface, although other interfaces also may be used. In certain forms, the second data circuit may generally be any circuit for transmitting and/or receiving data. In one form, for example, the second data circuit may store information pertaining to the particular surgical instrument with which it is associated. Such information may include, for example, a model number, a serial number, a number of operations in which the surgical instrument has been used, and/or any other type of information. In some forms, the second data circuit 138 may store information about the electrical and/or ultrasonic properties of an associated transducer 120, end effector 122, or ultrasonic drive system. Various processes and techniques described herein may be executed by a generator. It will be appreciated, however, that in certain example forms, all or a part of these processes and techniques may be performed by internal logic 139 of the multifunction surgical instrument 108.

FIG. 3 is a diagram of the surgical system 100 of FIG. 1. In various forms, the generator 102 may comprise several separate functional elements, such as modules and/or blocks. Different functional elements or modules may be configured for driving the different kinds of surgical instruments 104, 106, 108. For example, an ultrasonic generator drive circuit 114 may drive ultrasonic devices such as the ultrasonic surgical instrument 104 via a cable 142. An electrosurgery/RF generator drive circuit 116 may drive the electrosurgical instrument 106 via a cable 144. For example, the respective drive circuits 114, 116 may generate respective drive signals for driving the surgical instruments 104, 106, 108. In various forms, the ultrasonic generator drive circuit 114 (e.g., ultrasonic drive circuit) and/or the electrosurgery/RF generator drive circuit 116 (e.g., RF drive circuit) each may be formed integrally with the generator 102. Alternatively, one or more of the drive circuits 114, 116 may be provided as a separate circuit module electrically coupled to the generator 102. (The drive circuits 114 and 116 are shown in phantom to illustrate this option.) Also, in some forms, the electrosurgery/RF generator drive circuit 116 may be formed integrally with the ultrasonic generator drive circuit 114, or vice versa. Also, in some forms, the generator 102 may be omitted entirely and the drive circuits 114, 116 may be executed by processors or other hardware within the respective surgical instruments 104, 106, 108.

In other forms, the electrical outputs of the ultrasonic generator drive circuit 114 and the electrosurgery/RF generator drive circuit 116 may be combined into a single drive circuit to provide a single electrical signal capable of driving the multifunction surgical instrument 108 simultaneously with electrosurgical RF and ultrasonic energies via a cable 146. The multifunction surgical instrument 108 comprises an ultrasonic transducer 120 coupled to an ultrasonic blade 149 and one or more electrodes in the end effector 124 to receive electrosurgical RF energy. In such implementations, the combined RF/ultrasonic signal is coupled to the multifunction surgical instrument 108. The multifunction surgical instrument 108 comprises signal processing components to split the combined RF/ultrasonic signal such that the RF signal can be delivered to the electrodes in the end effector 124 and the ultrasonic signal can be delivered to the ultrasonic transducer 120.

In accordance with the described forms, the ultrasonic generator drive circuit 114 may produce a drive signal or signals of particular voltages, currents, and frequencies, e.g., 55,500 cycles per second (Hz). The drive signal or signals may be provided to the ultrasonic surgical instrument 104, and specifically to the transducer 120, which may operate, for example, as described herein. The transducer 120 and a waveguide extending through the shaft 126 (waveguide not shown in FIG. 2) may collectively form an ultrasonic drive system driving an ultrasonic blade 128 of an end effector 122. In one form, the generator 102 may be configured to produce a drive signal of a particular voltage, current, and/or frequency output signal that can be stepped or otherwise modified with high resolution, accuracy, and repeatability.

The generator 102 may be activated to provide the drive signal to the transducer 120 in any suitable manner. For example, the generator 102 may comprise a foot switch 130 coupled to the generator 102 via a foot switch cable 132. A clinician may activate the transducer 120 by depressing the foot switch 130. In addition, or instead of the foot switch 130 some forms of the ultrasonic surgical instrument 104 may utilize one or more switches positioned on the hand piece that, when activated, may cause the generator 102 to activate the transducer 120. In one form, for example, the one or more switches may comprise a pair of toggle buttons 134a, 134b (FIG. 2), for example, to determine an operating mode of the surgical instrument 104. When the toggle button 134a is depressed, for example, the ultrasonic generator 102 may provide a maximum drive signal to the transducer 120, causing it to produce maximum ultrasonic energy output. Depressing toggle button 134b may cause the ultrasonic generator 102 to provide a user-selectable drive signal to the transducer 120, causing it to produce less than the maximum ultrasonic energy output. The surgical instrument 104 additionally or alternatively may comprise a second switch (not shown) to, for example, indicate a position of a jaw closure trigger for operating jaws of the end effector 122. Also, in some forms, the ultrasonic generator 102 may be activated based on the position of the jaw closure trigger, (e.g., as the clinician depresses the jaw closure trigger to close the jaws, ultrasonic energy may be applied).

Additionally or alternatively, the one or more switches may comprises a toggle button 134c that, when depressed, causes the generator 102 to provide a pulsed output. The pulses may be provided at any suitable frequency and grouping, for example. In certain forms, the power level of the pulses may be the power levels associated with toggle buttons 134a, 134b (maximum, less than maximum), for example.

In accordance with the described forms, the electrosurgery/RF generator drive circuit 116 may generate a drive signal or signals with output power sufficient to perform bipolar electrosurgery using radio frequency (RF) energy. In bipolar electrosurgery applications, the drive signal may be provided, for example, to electrodes of the electrosurgical instrument 106, for example. Accordingly, the generator 102 may be configured for therapeutic purposes by applying electrical energy to the tissue sufficient for treating the tissue (e.g., coagulation, cauterization, tissue welding).

The generator 102 may comprise an input device 110 (FIG. 1) located, for example, on a front panel of the generator 102 console. The input device 110 may comprise any suitable device that generates signals suitable for programming the operation of the generator 102. In operation, the user can program or otherwise control operation of the generator 102 using the input device 110. The input device 110 may comprise any suitable device that generates signals that can be used by the generator (e.g., by one or more processors contained in the generator) to control the operation of the generator 102 (e.g., operation of the ultrasonic generator drive circuit 114 and/or electrosurgery/RF generator drive circuit 116). In various forms, the input device 110 includes one or more of buttons, switches, thumbwheels, keyboard, keypad, touch screen monitor, pointing device, remote connection to a general purpose or dedicated computer. In other forms, the input device 110 may comprise a suitable user interface, such as one or more user interface screens displayed on a touch screen monitor, for example. Accordingly, by way of the input device 110, the user can set or program various operating parameters of the generator, such as, for example, current (I), voltage (V), frequency (f), and/or period (T) of a drive signal or signals generated by the ultrasonic generator drive circuit 114 and/or electrosurgery/RF generator drive circuit 116.

The generator 102 also may comprise an output device 112 (FIGS. 1, 3), such as an output indicator, located, for example, on a front panel of the generator 102 console. The output device 112 includes one or more devices for providing a sensory feedback to a user. Such devices may comprise, for example, visual feedback devices (e.g., a visual feedback device may comprise incandescent lamps, light emitting diodes (LEDs), graphical user interface, display, analog indicator, digital indicator, bar graph display, digital alphanumeric display, LCD display screen, LED indicators), audio feedback devices (e.g., an audio feedback device may comprise speaker, buzzer, audible, computer generated tone, computerized speech, voice user interface (VUI) to interact with computers through a voice/speech platform), or tactile feedback devices (e.g., a tactile feedback device comprises any type of vibratory feedback, haptic actuator).

Although certain modules, circuits, and/or blocks of the generator 102 may be described by way of example, it can be appreciated that a greater or lesser number of modules, circuits, and/or blocks may be used and still fall within the scope of the forms. Further, although various forms may be described in terms of modules, circuits, and/or blocks to facilitate description, such modules, circuits, and/or blocks may be implemented by one or more hardware components, e.g., processors, Digital Signal Processors (DSPs), Programmable Logic Devices (PLDs), Application Specific Integrated Circuits (ASICs), circuits, registers and/or software components, e.g., programs, subroutines, logic and/or combinations of hardware and software components. Also, in some forms, the various modules described herein may be implemented utilizing similar hardware positioned within the surgical instruments 104, 106, 108 (i.e., the generator 102 may be omitted).

In one form, the ultrasonic generator drive circuit 114 and electrosurgery/RF drive circuit 116 may comprise one or more embedded applications implemented as firmware, software, hardware, or any combination thereof. The drive circuits 114, 116 may comprise various executable modules such as software, programs, data, drivers, application program interfaces (APIs), and so forth. The firmware may be stored in nonvolatile memory (NVM), such as in bit-masked read-only memory (ROM) or flash memory. In various implementations, storing the firmware in ROM may preserve flash memory. The NVM may comprise other types of memory including, for example, programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or battery backed random-access memory (RAM) such as dynamic RAM (DRAM), Double-Data-Rate DRAM (DDRAM), and/or synchronous DRAM (SDRAM).

In one form, the drive circuits 114, 116 comprise a hardware component implemented as a processor for executing program instructions for monitoring various measurable characteristics of the surgical instruments 104, 106, 108 and generating a corresponding output control signals for operating the surgical instruments 104, 106, 108. In forms in which the generator 102 is used in conjunction with the surgical instrument 104, the output control signal may drive the ultrasonic transducer 120 in cutting and/or coagulation operating modes. Electrical characteristics of the surgical instrument 104 and/or tissue may be measured and used to control operational aspects of the generator 102 and/or provided as feedback to the user. In forms in which the generator 102 is used in conjunction with the electrosurgical instrument 106, the output control signal may supply electrical energy (e.g., RF energy) to the end effector 124 in cutting, coagulation and/or desiccation modes. Electrical characteristics of the electrosurgical instrument 106 and/or tissue may be measured and used to control operational aspects of the generator 102 and/or provide feedback to the user. In various forms, as previously discussed, the hardware component may be implemented as a DSP, PLD, ASIC, circuits, and/or registers. In one form, the processor may be configured to store and execute computer software program instructions to generate the output signal functions for driving various components of the surgical instruments 104, 106, 108, such as the ultrasonic transducer 120 and the end effectors 122, 124.

FIG. 4 illustrates an equivalent circuit 150 of an ultrasonic transducer, such as the ultrasonic transducer 120 shown in FIGS. 1-3, according to one form. The circuit 150 comprises a first “motional” branch having a serially connected inductance L_s, resistance R_sand capacitance C_sthat define the electromechanical properties of the resonator, and a second capacitive branch having a static capacitance C_o. Drive current I_gmay be received from a generator at a drive voltage V_g, with motional current I_mflowing through the first branch and current I_g-I_mflowing through the capacitive branch. Control of the electromechanical properties of the ultrasonic transducer may be achieved by suitably controlling I_gand V_g. As explained above, conventional generator architectures may include a tuning inductor L_t(shown in phantom in FIG. 4) for tuning out in a parallel resonance circuit the static capacitance Co at a resonant frequency so that substantially all of generator's current output I_gflows through the motional branch. In this way, control of the motional branch current I_mis achieved by controlling the generator current output I_g. The tuning inductor L_tis specific to the static capacitance C_oof an ultrasonic transducer, however, and a different ultrasonic transducer having a different static capacitance requires a different tuning inductor L_t. Moreover, because the tuning inductor L_tis matched to the nominal value of the static capacitance Co at a resonant frequency, accurate control of the motional branch current I_mis assured only at that frequency, and as frequency shifts down with transducer temperature, accurate control of the motional branch current is compromised.

Forms of the generator 102 shown in FIGS. 1-3 do not rely on a tuning inductor L_tto monitor the motional branch current I_m. Instead, the generator 102 may use the measured value of the static capacitance C_oin between applications of power for a specific ultrasonic surgical instrument 104 (along with drive signal voltage and current feedback data) to determine values of the motional branch current I_mon a dynamic and ongoing basis (e.g., in real-time). Such forms of the generator 102 are therefore able to provide virtual tuning to simulate a system that is tuned or resonant with any value of static capacitance C_oat any frequency, and not just at the resonant frequency dictated by a nominal value of the static capacitance C_o.

FIG. 5 is a simplified block diagram of a generator 200 which is one form of the generator 102 shown in FIGS. 1-3 for proving inductorless tuning as described herein, among other benefits. Additional details of the generator 102 are described in commonly assigned U.S. patent application Ser. No. 12/896,360, titled “Surgical Generator For Ultrasonic And Electrosurgical Devices,” now U.S. Pat. No. 9,060,775, the disclosure of which is incorporated herein by reference in its entirety. Wth reference to FIG. 5, the generator 200 may comprise a patient isolated stage 202 in communication with a non-isolated stage 204 via a power transformer 206. A secondary winding 208 of the power transformer 206 is contained in the isolated stage 202 and may comprise a tapped configuration (e.g., a center-tapped or a non-center-tapped configuration) to define drive signal outputs 210a, 210b, 210c for outputting drive signals to different surgical devices, such as, for example, an ultrasonic surgical instrument 104 and an electrosurgical instrument 106 (as shown in FIGS. 1-3). In particular, the drive signal outputs 210a, 210c may output an ultrasonic drive signal (e.g., a 420V RMS drive signal) to an ultrasonic surgical instrument 104, and the drive signal outputs 210b, 210c may output an electrosurgical RF drive signal (e.g., a 100V RMS drive signal) to an electrosurgical instrument 106, with the output 210b corresponding to the center tap of the power transformer 206.

In certain forms, the ultrasonic and electrosurgical drive signals may be provided simultaneously to distinct surgical instruments and/or to a single surgical instrument having the capability to deliver both ultrasonic and electrosurgical energy to tissue, such as multifunction surgical instrument 108 (FIGS. 1 and 3). It will be appreciated that the electrosurgical signal, provided either to a dedicated electrosurgical instrument and/or to a combined multifunction ultrasonic/electrosurgical instrument may be either a therapeutic or sub-therapeutic level signal. For example, the ultrasonic and radio frequency signals can be delivered separately or simultaneously from a generator with a single output port in order to provide the desired output signal to the surgical instrument, as will be discussed in more detail below. Accordingly, the generator can combine the ultrasonic and electrosurgical RF energies and deliver the combined energies to the multifunction ultrasonic/electrosurgical instrument. Bipolar electrodes can be placed on one or both jaws of the end effector. One jaw may be driven by ultrasonic energy in addition to electrosurgical RF energy, working simultaneously. The ultrasonic energy may be employed to dissect tissue while the electrosurgical RF energy may be employed for vessel sealing.

The non-isolated stage 204 may comprise a power amplifier 212 having an output connected to a primary winding 214 of the power transformer 206. In certain forms the power amplifier 212 may be comprise a push-pull amplifier. For example, the non-isolated stage 204 may further comprise a logic device 216 for supplying a digital output to a digital-to-analog converter (DAC) 218, which in turn supplies a corresponding analog signal to an input of the power amplifier 212. In certain forms the logic device 216 may comprise a programmable gate array (PGA), a field-programmable gate array (FPGA), programmable logic device (PLD), among other logic circuits, for example. The logic device 216, by virtue of controlling the input of the power amplifier 212 via the DAC 218, may therefore control any of a number of parameters (e.g., frequency, waveform shape, waveform amplitude) of drive signals appearing at the drive signal outputs 210a, 210b, 210c. In certain forms and as discussed below, the logic device 216, in conjunction with a processor (e.g., a digital signal processor discussed below), may implement a number of digital signal processing (DSP)-based and/or other control techniques to control parameters of the drive signals output by the generator 200.

Power may be supplied to a power rail of the power amplifier 212 by a switch-mode regulator 220. In certain forms the switch-mode regulator 220 may comprise an adjustable buck regulator, for example. The non-isolated stage 204 may further comprise a first processor such as DSP processor 222, which in one form may comprise a DSP processor such as an Analog Devices ADSP-21469 SHARC DSP, available from Analog Devices, Norwood, MA, for example, although in various forms any suitable processor may be employed. In certain forms the DSP processor 222 may control operation of the switch-mode power converter 220 responsive to voltage feedback data received from the power amplifier 212 by the DSP processor 222 via an analog-to-digital converter (ADC) 224. In one form, for example, the DSP processor 222 may receive as input, via the ADC 224, the waveform envelope of a signal (e.g., an RF signal) being amplified by the power amplifier 212. The DSP processor 222 may then control the switch-mode regulator 220 (e.g., via a pulse-width modulated (PWM) output) such that the rail voltage supplied to the power amplifier 212 tracks the waveform envelope of the amplified signal. By dynamically modulating the rail voltage of the power amplifier 212 based on the waveform envelope, the efficiency of the power amplifier 212 may be significantly improved relative to a fixed rail voltage amplifier schemes.

In certain forms, the logic device 216, in conjunction with the DSP processor 222, may implement a direct digital synthesizer (DDS) control scheme to control the waveform shape, frequency and/or amplitude of drive signals output by the generator 200. In one form, for example, the logic device 216 may implement a DDS control technique by recalling waveform samples stored in a dynamically-updated look-up table (LUT), such as a RAM LUT, which may be embedded in an FPGA. This control technique is particularly useful for ultrasonic applications in which an ultrasonic transducer, such as the ultrasonic transducer 120 (FIGS. 1-3), may be driven by a clean sinusoidal current at its resonant frequency. Because other frequencies may excite parasitic resonances, minimizing or reducing the total distortion of the motional branch current may correspondingly minimize or reduce undesirable resonance effects. Because the waveform shape of a drive signal output by the generator 200 is impacted by various sources of distortion present in the output drive circuit (e.g., the power transformer 206, the power amplifier 212), voltage and current feedback data based on the drive signal may be input into a technique, such as an error control technique implemented by the DSP processor 222, which compensates for distortion by suitably pre-distorting or modifying the waveform samples stored in the LUT on a dynamic, ongoing basis (e.g., in real-time). In one form, the amount or degree of pre-distortion applied to the LUT samples may be based on the error between a computed motional branch current and a desired current waveform shape, with the error being determined on a sample-by-sample basis. In this way, the pre-distorted LUT samples, when processed through the drive circuit, may result in a motional branch drive signal having the desired waveform shape (e.g., sinusoidal) for optimally driving the ultrasonic transducer. In such forms, the LUT waveform samples will therefore not represent the desired waveform shape of the drive signal, but rather the waveform shape that is required to ultimately produce the desired waveform shape of the motional branch drive signal when distortion effects are taken into account.

The non-isolated stage 204 may further comprise an ADC 226 and an ADC 228 coupled to the output of the power transformer 206 via respective isolation transformers 230, 232 for respectively sampling the voltage and current of drive signals output by the generator 200. In certain forms, the ADCs 226, 228 may be configured to sample at high speeds (e.g., 80 MSPS) to enable oversampling of the drive signals. In one form, for example, the sampling speed of the ADCs 226, 228 may enable approximately 200× (depending on frequency) oversampling of the drive signals. In certain forms, the sampling operations of the ADC 226, 228 may be performed by a singe ADC receiving input voltage and current signals via a two-way multiplexer. The use of high-speed sampling in forms of the generator 200 may enable, among other things, calculation of the complex current flowing through the motional branch (which may be used in certain forms to implement DDS-based waveform shape control described herein), accurate digital filtering of the sampled signals, and calculation of real power consumption with a high degree of precision. Voltage and current feedback data output by the ADCs 226, 228 may be received and processed (e.g., FIFO buffering, multiplexing) by the logic device 216 and stored in data memory for subsequent retrieval by, for example, the DSP processor 222. As noted above, voltage and current feedback data may be used as input to a technique for pre-distorting or modifying LUT waveform samples on a dynamic and ongoing basis. In certain forms, this may require each stored voltage and current feedback data pair to be indexed based on, or otherwise associated with, a corresponding LUT sample that was output by the logic device 216 when the voltage and current feedback data pair was acquired. Synchronization of the LUT samples and the voltage and current feedback data in this manner contributes to the correct timing and stability of the pre-distortion technique.

In certain forms, the voltage and current feedback data may be used to control the frequency and/or amplitude (e.g., current amplitude) of the drive signals. In one form, for example, voltage and current feedback data may be used to determine impedance phase. The frequency of the drive signal may then be controlled to minimize or reduce the difference between the determined impedance phase and an impedance phase setpoint (e.g., 0°), thereby minimizing or reducing the effects of ultrasonic distortion and correspondingly enhancing impedance phase measurement accuracy. The determination of phase impedance and a frequency control signal may be implemented in the DSP processor 222, for example, with the frequency control signal being supplied as input to a DDS control technique implemented by the logic device 216.

In another form, for example, the current feedback data may be monitored in order to maintain the current amplitude of the drive signal at a current amplitude setpoint. The current amplitude setpoint may be specified directly or determined indirectly based on specified voltage amplitude and power setpoints. In certain forms, control of the current amplitude may be implemented by control technique, such as, for example, a PID control technique, in the DSP processor 222. Variables controlled by the control technique to suitably control the current amplitude of the drive signal may include, for example, the scaling of the LUT waveform samples stored in the logic device 216 and/or the full-scale output voltage of the DAC 218 (which supplies the input to the power amplifier 212) via a DAC 234.

The non-isolated stage 204 may further comprise a second processor such as UI processor 236 for providing, among other things user interface (UI) functionality. In one form, the UI processor 236 may comprise an Atmel AT91SAM9263 processor having an ARM 926EJ-S core, available from Atmel Corporation, San Jose, CA, for example. Examples of UI functionality supported by the UI processor 236 may include audible and visual user feedback, communication with peripheral devices (e.g., via a Universal Serial Bus (USB) interface), communication with the foot switch 130, communication with an input device 118 (e.g., a touch screen display) and communication with an output device 112 (e.g., a speaker), as shown in FIG. 3, for example. The UI processor 236 may communicate with the DSP processor 222 and the logic device 216 (e.g., via serial peripheral interface (SPI) buses). Although the UI processor 236 may primarily support UI functionality, it also may coordinate with the DSP processor 222 to implement hazard mitigation in certain forms. For example, the UI processor 236 may be programmed to monitor various aspects of user input and/or other inputs (e.g., touch screen inputs, foot switch 130 inputs (FIG. 3), temperature sensor inputs) and may disable the drive output of the generator 200 when an erroneous condition is detected.

In certain forms, both the DSP processor 222 and the UI processor 236, for example, may determine and monitor the operating state of the generator 200. For the DSP processor 222, the operating state of the generator 200 may dictate, for example, which control and/or diagnostic processes are implemented by the DSP processor 222. For the UI processor 236, the operating state of the generator 200 may dictate, for example, which elements of a user interface (e.g., display screens, sounds) are presented to a user. The respective DSP and UI processors 222, 236 may independently maintain the current operating state of the generator 200 and recognize and evaluate possible transitions out of the current operating state. The DSP processor 222 may function as the master in this relationship and determine when transitions between operating states are to occur. The UI processor 236 may be aware of valid transitions between operating states and may confirm if a particular transition is appropriate. For example, when the DSP processor 222 instructs the UI processor 236 to transition to a specific state, the UI processor 236 may verify that requested transition is valid. In the event that a requested transition between states is determined to be invalid by the UI processor 236, the UI processor 236 may cause the generator 200 to enter a failure mode.

The non-isolated stage 204 may further comprise a controller 238 for monitoring input devices 110 (e.g., a capacitive touch sensor used for turning the generator 200 on and off, a capacitive touch screen, e.g., as shown in FIGS. 1 and 3). In certain forms, the controller 238 may comprise at least one processor and/or other controller device in communication with the UI processor 236. In one form, for example, the controller 238 may comprise a processor (e.g., a Mega168 8-bit controller available from Atmel) configured to monitor user input provided via one or more capacitive touch sensors. In one form, the controller 238 may comprise a touch screen controller (e.g., a QT5480 touch screen controller available from Atmel) to control and manage the acquisition of touch data from a capacitive touch screen.

In certain forms, when the generator 200 is in a “power off” state, the controller 238 may continue to receive operating power (e.g., via a line from a power supply of the generator 200. In this way, the controller 238 may continue to monitor an input device 110 (e.g., a capacitive touch sensor located on a front panel of the generator 200) for turning the generator 200 on and off. When the generator 200 is in the power off state, the controller 238 may wake the power supply (e.g., enable operation of one or more DC/DC voltage converters of the power supply) if activation of the “on/off” input device 110 by a user is detected. The controller 238 may therefore initiate a sequence for transitioning the generator 200 to a “power on” state. Conversely, the controller 238 may initiate a sequence for transitioning the generator 200 to the power off state if activation of the “on/off” input device 110 is detected when the generator 200 is in the power on state. In certain forms, for example, the controller 238 may report activation of the “on/off” input device 110 to the UI processor 236, which in turn implements the necessary process sequence for transitioning the generator 200 to the power off state. In such forms, the controller 238 may have no independent ability for causing the removal of power from the generator 200 after its power on state has been established.

In certain forms, the controller 238 may cause the generator 200 to provide audible or other sensory feedback for alerting the user that a power on or power off sequence has been initiated. Such an alert may be provided at the beginning of a power on or power off sequence and prior to the commencement of other processes associated with the sequence.

In certain forms, the isolated stage 202 may comprise an instrument interface circuit 240 to, for example, provide a communication interface between a control circuit of a surgical device (e.g., a control circuit comprising hand piece switches) and components of the non-isolated stage 204, such as, for example, the programmable logic device 216, the DSP processor 222 and/or the UI processor 236. The instrument interface circuit 240 may exchange information with components of the non-isolated stage 204 via a communication link that maintains a suitable degree of electrical isolation between the stages 202, 204, such as, for example, an infrared (IR)-based communication link. Power may be supplied to the instrument interface circuit 240 using, for example, a low-dropout voltage regulator powered by an isolation transformer driven from the non-isolated stage 204.

In one form, the instrument interface circuit 240 may comprise a logic device 242 (e.g., logic circuit, programmable logic circuit, PGA, FPGA, PLD) in communication with a signal conditioning circuit 242. The signal conditioning circuit 244 may be configured to receive a periodic signal from the logic circuit 242 (e.g., a 2 kHz square wave) to generate a bipolar interrogation signal having an identical frequency. The interrogation signal may be generated, for example, using a bipolar current source fed by a differential amplifier. The interrogation signal may be communicated to a surgical device control circuit (e.g., by using a conductive pair in a cable that connects the generator 200 to the surgical device) and monitored to determine a state or configuration of the control circuit. The control circuit may comprise a number of switches, resistors and/or diodes to modify one or more characteristics (e.g., amplitude, rectification) of the interrogation signal such that a state or configuration of the control circuit is uniquely discernable based on the one or more characteristics. In one form, for example, the signal conditioning circuit 244 may comprises an ADC for generating samples of a voltage signal appearing across inputs of the control circuit resulting from passage of interrogation signal therethrough. The logic device 242 (or a component of the non-isolated stage 204) may then determine the state or configuration of the control circuit based on the ADC samples.

In one form, the instrument interface circuit 240 may comprise a first data circuit interface 246 to enable information exchange between the logic circuit 242 (or other element of the instrument interface circuit 240) and a first data circuit disposed in or otherwise associated with a surgical device. In certain forms, for example, a first data circuit 136 (FIG. 2) may be disposed in a cable integrally attached to a surgical device hand piece, or in an adaptor for interfacing a specific surgical device type or model with the generator 200. The first data circuit 136 may be implemented in any suitable manner and may communicate with the generator according to any suitable protocol including, for example, as described herein with respect to the first circuit 136. In certain forms, the first data circuit may comprise a non-volatile storage device, such as an electrically erasable programmable read-only memory (EEPROM) device. In certain forms and referring again to FIG. 5, the first data circuit interface 246 may be implemented separately from the logic device 242 and comprise suitable circuitry (e.g., discrete logic devices, a processor) to enable communication between the programmable logic device 242 and the first data circuit. In other forms, the first data circuit interface 246 may be integral with the logic device 242.

In certain forms, the first data circuit 136 (FIG. 2) may store information pertaining to the particular surgical device with which it is associated. Such information may include, for example, a model number, a serial number, a number of operations in which the surgical device has been used, and/or any other type of information. This information may be read by the instrument interface circuit 1098 (e.g., by the logic device 242), transferred to a component of the non-isolated stage 204 (e.g., to logic device 216, DSP processor 222 and/or UI processor 236) for presentation to a user via an output device 112 (FIGS. 1 and 3) and/or for controlling a function or operation of the generator 200. Additionally, any type of information may be communicated to first data circuit 136 for storage therein via the first data circuit interface 246 (e.g., using the logic device 242). Such information may comprise, for example, an updated number of operations in which the surgical device has been used and/or dates and/or times of its usage.

As discussed previously, a surgical instrument may be detachable from a hand piece (e.g., as shown in FIGS. 1 and 2, the transducer 120 and the shaft 126 is detachable from the handpiece 105 of the ultrasonic surgical instrument 104) to promote instrument interchangeability and/or disposability. In such cases, conventional generators may be limited in their ability to recognize particular instrument configurations being used and to optimize control and diagnostic processes accordingly. The addition of readable data circuits to surgical device instruments to address this issue is problematic from a compatibility standpoint, however. For example, designing a surgical device to remain backwardly compatible with generators that lack the requisite data reading functionality may be impractical due to, for example, differing signal schemes, design complexity, and cost. Forms of instruments discussed herein address these concerns by using data circuits that may be implemented in existing surgical instruments economically and with minimal design changes to preserve compatibility of the surgical devices with current generator platforms.

Wth reference to FIGS. 1-3 and 5, additionally, forms of the generator 200 may enable communication with instrument-based data circuits. For example, the generator 200 may be configured to communicate with a second data circuit 138 contained in the ultrasonic surgical instrument 104 (e.g., and/or the other surgical instruments 106, 108). In some forms, the second data circuit 138 may be implemented in a many similar to that of the first data circuit 136 described herein. The instrument interface circuit 240 may comprise a second data circuit interface 248 to enable this communication. In one form, the second data circuit interface 248 may comprise a tri-state digital interface, although other interfaces also may be used. In certain forms, the second data circuit may generally be any circuit for transmitting and/or receiving data. In one form, for example, the second data circuit may store information pertaining to the particular surgical instrument with which it is associated. Such information may include, for example, a model number, a serial number, a number of operations in which the surgical instrument has been used, and/or any other type of information. In some forms, the second data circuit 138 may store information about the electrical and/or ultrasonic properties of an associated transducer 120, end effector 122, or ultrasonic drive system. For example, the first data circuit 136 may indicate a burn-in frequency slope, as described herein. Additionally or alternatively, any type of information may be communicated to second data circuit for storage therein via the second data circuit interface 248 (e.g., using the logic device 242). Such information may comprise, for example, an updated number of operations in which the instrument has been used and/or dates and/or times of its usage. In certain forms, the second data circuit may transmit data acquired by one or more sensors (e.g., an instrument-based temperature sensor). In certain forms, the second data circuit may receive data from the generator 200 and provide an indication to a user (e.g., an LED indication or other visible indication) based on the received data.

In certain forms, the second data circuit and the second data circuit interface 248 may be configured such that communication between the logic device 242 and the second data circuit can be effected without the need to provide additional conductors for this purpose (e.g., dedicated conductors of a cable connecting a hand piece to the generator 200). In one form, for example, information may be communicated to and from the second data circuit using a 1-wire bus communication scheme implemented on existing cabling, such as one of the conductors used transmit interrogation signals from the signal conditioning circuit 244 to a control circuit in a hand piece. In this way, design changes or modifications to the surgical device that might otherwise be necessary are minimized or reduced. Moreover, because different types of communications implemented over a common physical channel can be frequency-band separated, the presence of a second data circuit may be “invisible” to generators that do not have the requisite data reading functionality, thus enabling backward compatibility of the surgical device instrument.

In certain forms, the isolated stage 202 may comprise at least one blocking capacitor 250-1 connected to the drive signal output 210b to prevent passage of DC current to a patient. A single blocking capacitor may be required to comply with medical regulations or standards, for example. While failure in single-capacitor designs is relatively uncommon, such failure may nonetheless have negative consequences. In one form, a second blocking capacitor 250-2 may be provided in series with the blocking capacitor 250-1, with current leakage from a point between the blocking capacitors 250-1, 250-2 being monitored by, for example, an ADC 252 for sampling a voltage induced by leakage current. The samples may be received by the logic device 242, for example. Based changes in the leakage current (as indicated by the voltage samples in the form of FIG. 5), the generator 200 may determine when at least one of the blocking capacitors 250-1, 250-2 has failed. Accordingly, the form of FIG. 5 provides a benefit over single-capacitor designs having a single point of failure.

In certain forms, the non-isolated stage 204 may comprise a power supply 254 for outputting DC power at a suitable voltage and current. The power supply may comprise, for example, a 400 W power supply for outputting a 48 VDC system voltage. The power supply 254 may further comprise one or more DC/DC voltage converters 256 for receiving the output of the power supply to generate DC outputs at the voltages and currents required by the various components of the generator 200. As discussed above in connection with the controller 238, one or more of the DC/DC voltage converters 256 may receive an input from the controller 238 when activation of the “on/off” input device 110 (FIG. 3) by a user is detected by the controller 238 to enable operation of, or wake, the DC/DC voltage converters 256.

Wth reference back to FIG. 1, having described operational details of various forms of the surgical system 100 operations for the above surgical system 100 may be further described generally in terms of a process for cutting and coagulating tissue employing a surgical instrument comprising an input device 110 and the generator 102. Although a particular process is described in connection with the operational details, it can be appreciated that the process merely provides an example of how the general functionality described herein can be implemented by the surgical system 100. Further, the given process does not necessarily have to be executed in the order presented herein unless otherwise indicated. As previously discussed, the input devices 110 may be employed to program the output (e.g., impedance, current, voltage, frequency) of the surgical instruments 104, 106, 108.

FIG. 6 illustrates a generator 300 comprising one form of drive system 302, according to one aspect of the present disclosure. The generator 300 is similar to the generators 102, 200 described in connection with in FIGS. 1 and 5. The generator 300 produces an ultrasonic electrical signal for driving an ultrasonic transducer, also referred to as a drive signal. The drive system 302 is flexible and can create an ultrasonic electrical output drive signal 304 at a desired frequency and power level setting for driving an ultrasonic transducer 306. In various forms, the generator 300 may comprise several separate functional elements, such as modules and/or blocks. Although certain modules, circuits, and/or blocks may be described by way of example, it can be appreciated that a greater or lesser number of modules, circuits, and/or blocks may be used and still fall within the scope of the forms. Further, although various forms may be described in terms of modules, circuits, and/or blocks to facilitate description, such modules, circuits, and/or blocks may be implemented by one or more hardware components, e.g., processors, Digital Signal Processors (DSPs), Programmable Logic Devices (PLDs), Application Specific Integrated Circuits (ASICs), circuits, registers and/or software components, e.g., programs, subroutines, logic and/or combinations of hardware and software components.

In one form, the drive system 302 of the generator 300 may comprise one or more embedded applications implemented as firmware, software, hardware, or any combination thereof. The drive system 302 may comprise various executable modules such as software, programs, data, drivers, application program interfaces (APIs), and so forth. The firmware may be stored in nonvolatile memory (NVM), such as in bit-masked read-only memory (ROM) or flash memory. In various implementations, storing the firmware in ROM may preserve flash memory. The NVM may comprise other types of memory including, for example, programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or battery backed random-access memory (RAM) such as dynamic RAM (DRAM), Double-Data-Rate DRAM (DDRAM), and/or synchronous DRAM (SDRAM).

In one form, the drive system 302 comprises a hardware component implemented as a processor 308 for executing program instructions for monitoring various measurable characteristics of the ultrasonic surgical instrument 104 (FIG. 1) and generating various functions as an output signal for driving the ultrasonic transducer 306 in cutting and/or coagulation operating modes. It will be appreciated by those skilled in the art that the generator 300 and the drive system 302 may comprise additional or fewer components and only a simplified version of the generator 300 and the drive system 302 are described herein for conciseness and clarity. In various forms, as previously discussed, the hardware component may be implemented as a DSP, PLD, ASIC, circuits, and/or registers. In one form, the processor 308 may be configured to store and execute computer software program instructions to generate the output signal functions for driving various components of the ultrasonic surgical instrument 104 (FIG. 1), such as an ultrasonic transducer 306, an end effector, and/or a blade 340.

In one form, under control of one or more software program routines, the processor 308 executes the methods in accordance with the described forms to generate a function formed by a stepwise waveform of drive signals comprising current (I), voltage (V), and/or frequency (f) for various time intervals or periods (T). The stepwise waveforms of the drive signals may be generated by forming a piecewise linear combination of constant functions over a plurality of time intervals created by varying the generator 300 drive signals, e.g., output drive current (I), voltage (V), and/or frequency (f). The time intervals or periods (T) may be predetermined (e.g., fixed and/or programmed by the user) or may be variable. Variable time intervals may be defined by setting the drive signal to a first value and maintaining the drive signal at that value until a change is detected in a monitored characteristic. Examples of monitored characteristics may comprise, for example, transducer impedance, tissue impedance, tissue heating, tissue transection, tissue coagulation, and the like. The ultrasonic drive signals generated by the generator 300 include, without limitation, ultrasonic drive signals capable of exciting the ultrasonic transducer 306 in various vibratory modes such as, for example, the primary longitudinal mode and harmonics thereof as well flexural and torsional vibratory modes.

In one form, the executable modules comprise one or more technique(s) 310 stored in memory that when executed causes the processor 308 to generate a function formed by a stepwise waveform of drive signals comprising current (I), voltage (V), and/or frequency (f) for various time intervals or periods (T). The stepwise waveforms of the drive signals may be generated by forming a piecewise linear combination of constant functions over two or more time intervals created by varying the generator 300 output drive current (I), voltage (V), and/or frequency (f). The drive signals may be generated either for predetermined fixed time intervals or periods (T) of time or variable time intervals or periods of time in accordance with the one or more technique(s) 310. Under control of the processor 308, the generator 300 varies (e.g., increment or decrement over time) the current (I), voltage (V), and/or frequency (f) up or down at a particular resolution for a predetermined period (T) or until a predetermined condition is detected, such as a change in a monitored characteristic (e.g., transducer impedance, tissue impedance). The steps can change in programmed increments or decrements. If other steps are desired, the generator 300 can increase or decrease the step adaptively based on measured system characteristics.

In operation, the user can program the operation of the generator 300 using the input device 312 located on the front panel of the generator 300 console. The input device 312 may comprise any suitable device that generates signals 314 that can be applied to the processor 308 to control the operation of the generator 300. In various forms, the input device 312 includes buttons, switches, thumbwheels, keyboard, keypad, touch screen monitor, pointing device, remote connection to a general purpose or dedicated computer. In other forms, the input device 312 may comprise a suitable user interface. Accordingly, by way of the input device 312, the user can set or program the current (I), voltage (V), frequency (f), and/or period (T) for programming the output function of the generator 300. The processor 308 then displays the selected power level by sending a signal on line 316 to an output indicator 318.

In various forms, the output indicator 318 may provide visual, audible, and/or tactile feedback to the surgeon to indicate the status of a surgical procedure, such as, for example, when tissue cutting and coagulating is complete based on a measured characteristic of the ultrasonic surgical instrument 104 (FIG. 1), e.g., transducer impedance, tissue impedance, or other measurements as subsequently described. By way of example, and not limitation, visual feedback comprises any type of visual indication device including incandescent lamps or light emitting diodes (LEDs), graphical user interface, display, analog indicator, digital indicator, bar graph display, digital alphanumeric display. By way of example, and not limitation, audible feedback comprises any type of buzzer, computer generated tone, computerized speech, voice user interface (VUI) to interact with computers through a voice/speech platform. By way of example, and not limitation, tactile feedback comprises any type of vibratory feedback provided through an instrument housing handle assembly.

In one form, the processor 308 may be configured or programmed to generate a digital current drive signal 320 and a digital frequency signal 322. These drive signals 320, 322 are applied to a direct digital synthesizer (DDS) circuit 324 to adjust the amplitude and the frequency (f) of the output drive signal 304 to the ultrasonic transducer 306. The output of the DDS circuit 324 is applied to an amplifier 326 whose output is applied to a transformer 328. The output of the transformer 328 is the output drive signal 304 applied to the ultrasonic transducer 306, which is coupled to the blade 340 by way of a waveguide.

In one form, the generator 300 comprises one or more measurement modules or components that may be configured to monitor measurable characteristics of the ultrasonic surgical instrument 104 (FIG. 1). In the illustrated form, the processor 308 may be employed to monitor and calculate system characteristics. As shown, the processor 308 measures the impedance Z of the ultrasonic transducer 306 by monitoring the current supplied to the transducer 306 and the voltage applied to the ultrasonic transducer 306. In one form, a current sense circuit 330 is employed to sense the current supplied to the ultrasonic transducer 306 and a voltage sense circuit 332 is employed to sense the output voltage applied to the ultrasonic transducer 306. These signals may be applied to the analog-to-digital converter 336 (ADC) via an analog multiplexer 334 circuit or switching circuit arrangement. The analog multiplexer 334 routes the appropriate analog signal to the ADC 336 for conversion. In other forms, multiple ADCs 336 may be employed for each measured characteristic instead of the multiplexer 334 circuit. The processor 308 receives the digital output 338 of the ADC 336 and calculates the transducer impedance Z based on the measured values of current and voltage. The processor 308 adjusts the output drive signal 304 such that it can generate a desired power versus load curve. In accordance with programmed techniques 310, the processor 308 can vary the drive signal 320, e.g., the current or frequency, in any suitable increment or decrement in response to the transducer impedance Z.

Having described operational details of various forms of the surgical system 100 shown in FIG. 1, operations for the above surgical system 100 may be further described in terms of a process for cutting and coagulating a blood vessel employing a surgical instrument comprising the input device 110 and the transducer impedance measurement capabilities of the drive system 302 described with reference to FIG. 6. Although a particular process is described in connection with the operational details, it can be appreciated that the process merely provides an example of how the general functionality described herein can be implemented by the surgical system 100. Further, the given process does not necessarily have to be executed in the order presented herein unless otherwise indicated.

FIG. 7 illustrates one aspect of a drive system of a generator 400 comprising a tissue impedance module 442. The drive system 402 generates the ultrasonic electrical drive signal 404 to drive the ultrasonic transducer 406. In one aspect, the tissue impedance module 442 may be configured to measure the impedance Zt of tissue grasped between the blade 440 and the clamp arm assembly 444. The tissue impedance module 442 comprises an RF oscillator 446, a voltage sensing circuit 448, and a current sensing circuit 450. The voltage and current sensing circuits 448, 450 respond to the RF voltage Vrf applied to the blade 440 electrode and the RF current irf flowing through the blade 440 electrode, the tissue, and the conductive portion of the clamp arm assembly 444. The sensed current Irf and the sensed voltage Vrf from the current sense circuit 430 and the voltage sense circuit 432 are converted to digital form by the ADC 436 via the analog multiplexer 434. The processor 408 receives the digitized output 438 of the ADC 436 and determines the tissue impedance Zt by calculating the ratio of the RF voltage Vrf to current Irf measured by the voltage sensing circuit 448 and the current sense circuit 450.

In one form, the processor 408 may be configured or programmed to generate a digital current signal 420 and a digital frequency signal 422. These signals 420, 422 are applied to a direct digital synthesizer (DDS) circuit 424 to adjust the amplitude and the frequency (f) of the current output signal 404 to the transducer 406. The output of the DDS circuit 424 is applied to an amplifier 426 whose output is applied to a transformer 428. The output of the transformer 428 is the signal 404 applied to the ultrasonic transducer 406, which is coupled to the blade 440 by way of a waveguide.

In one aspect, the transection of the inner muscle layer and the tissue may be detected by sensing the tissue impedance Zt. Accordingly, detection of the tissue impedance Zt may be integrated with an automated process for separating the inner muscle layer from the outer adventitia layer prior to transecting the tissue without causing a significant amount of heating, which normally occurs at resonance.

In one form, the RF voltage Vrf applied to the blade 440 electrode and the RF current Irf flowing through the blade 440 electrode, the tissue, and the conductive portion of the clamp arm assembly 444 are suitable for vessel sealing and/or dissecting. Thus, the RF power output of the generator 400 can be selected for non-therapeutic functions such as tissue impedance measurements as well as therapeutic functions such as vessel sealing and/or dissection. It will be appreciated, that in the context of the present disclosure, the ultrasonic and the RF electrosurgical energies can be supplied by the generator either individually or simultaneously.

In operation, the user can program the operation of the generator 400 using the input device 412 located on the front panel of the generator 400 console. The input device 412 may comprise any suitable device that generates signals 414 that can be applied to the processor 408 to control the operation of the generator 400. In various forms, the input device 412 includes buttons, switches, thumbwheels, keyboard, keypad, touch screen monitor, pointing device, remote connection to a general purpose or dedicated computer. In other forms, the input device 412 may comprise a suitable user interface. Accordingly, by way of the input device 412, the user can set or program the current (I), voltage (V), frequency (f), and/or period (T) for programming the function output of the generator 400. The processor 408 then displays the selected power level by sending a signal on line 416 to an output indicator 418.

In various forms, feedback is provided by the output indicator 418. The output indicator 418 is particularly useful in applications where the tissue being manipulated by the end effector is out of the user's field of view and the user cannot see when a change of state occurs in the tissue. The output indicator 418 communicates to the user that a change in tissue state has occurred. As previously discussed, the output indicator 418 may be configured to provide various types of feedback to the user including, without limitation, visual, audible, and/or tactile feedback to indicate to the user (e.g., surgeon, clinician) that the tissue has undergone a change of state or condition of the tissue. By way of example, and not limitation, as previously discussed, visual feedback comprises any type of visual indication device including incandescent lamps or LEDs, graphical user interface, display, analog indicator, digital indicator, bar graph display, digital alphanumeric display. By way of example, and not limitation, audible feedback comprises any type of buzzer, computer generated tone, computerized speech, VUI to interact with computers through a voice/speech platform. By way of example, and not limitation, tactile feedback comprises any type of vibratory feedback provided through the instrument housing handle assembly. The change of state of the tissue may be determined based on transducer and tissue impedance measurements as previously described, or based on voltage, current, and frequency measurements.

In one form, the various executable modules (e.g., algorithms 410) comprising computer readable instructions can be executed by the processor 408 portion of the generator 400. In various forms, the operations described with respect to the techniques may be implemented as one or more software components, e.g., programs, subroutines, logic; one or more hardware components, e.g., processors, DSPs, PLDs, ASICs, circuits, registers; and/or combinations of software and hardware. In one form, the executable instructions to perform the techniques may be stored in memory. When executed, the instructions cause the processor 408 to determine a change in tissue state provide feedback to the user by way of the output indicator 418. In accordance with such executable instructions, the processor 408 monitors and evaluates the voltage, current, and/or frequency signal samples available from the generator 400 and according to the evaluation of such signal samples determines whether a change in tissue state has occurred. As further described below, a change in tissue state may be determined based on the type of ultrasonic instrument and the power level that the instrument is energized at. In response to the feedback, the operational mode of the ultrasonic surgical instrument may be controlled by the user or may be automatically or semi-automatically controlled.

As noted above, a single output generator can deliver both RF and ultrasonic energy through a single port and these signals can be delivered separately or simultaneously to the end effector to treat tissue. A single output port generator can include a single output transformer with multiple taps to provide power, either RF or ultrasonic energy, to the end effector depending on the type of treatment of tissue being performed. For example, the generator can deliver energy with higher voltage and lower current to drive an ultrasonic transducer, with lower voltage and higher current as required to drive electrodes for sealing tissue, or with a coagulation waveform for spot coagulation using either monopolar or bipolar electrosurgical electrodes. The output waveform from the generator can be steered, switched, or filtered to provide the desired frequency to the end effector of the surgical instrument.

FIG. 8 illustrates an example of a generator 500 for delivering multiple energy modalities to a surgical instrument. The generator 500 is similar to the generator 102 described in connection with FIG. 1 and includes functionalities of the generators 200, 300, 400 shown in FIGS. 5-7. For conciseness and clarity of disclosure, hereinbelow, the various logic flow diagrams are described in connection with the generator 500, which is a high level block diagram representation. Accordingly, the reader is directed to the description of the functional blocks of the generators 200, 300, 400 in FIGS. 5-7 for additional details that may be necessary to understand and practice the logic flow diagrams described hereinbelow in connection with the generator 500.

Turning back to FIG. 8, the generator 500 provides radio frequency and ultrasonic signals for delivering energy to a surgical instrument. The radio frequency and ultrasonic signals may be provided alone or in combination and may be provided simultaneously. As noted above, at least one generator output can deliver multiple energy modalities (e.g., ultrasonic, bipolar or monopolar RF, irreversible and/or reversible electroporation, and/or microwave energy, among others) through a single port and these signals can be delivered separately or simultaneously to the end effector to treat tissue. The generator 500 comprises a processor 502 coupled to a waveform generator 504. The processor 502 and waveform generator 504 are configured to generate a variety of signal waveforms based on information stored in a memory coupled to the processor 502, not shown for clarity of disclosure. The digital information associated with a waveform is provided to the waveform generator 504 which includes one or more digital-to-analog (DAC) converters to convert the digital input into an analog output. The analog output is fed to an amplifier 1106 for signal conditioning and amplification. The conditioned and amplified output of the amplifier 506 is coupled to a power transformer 508. The signals are coupled across the power transformer 508 to the secondary side, which is in the patient isolation side. A first signal of a first energy modality is provided to the surgical instrument between the terminals labeled ENERGY1 and RETURN. A second signal of a second energy modality is coupled across a capacitor 510 and is provided to the surgical instrument between the terminals labeled ENERGY2 and RETURN. It will be appreciated that more than two energy modalities may be output and thus the subscript “n” may be used to designate that up to n ENERGYn terminals may be provided, where n is a positive integer greater than 1. It also will be appreciated that up to “n” return paths RETURNn may be provided without departing from the scope of the present disclosure.

A first voltage sensing circuit 512 is coupled across the terminals labeled ENERGY1 and the RETURN path to measure the output voltage therebetween. A second voltage sensing circuit 524 is coupled across the terminals labeled ENERGY2 and the RETURN path to measure the output voltage therebetween. A current sensing circuit 514 is disposed in series with the RETURN leg of the secondary side of the power transformer 508 as shown to measure the output current for either energy modality. If different return paths are provided for each energy modality, then a separate current sensing circuit should be provided in each return leg. The outputs of the first and second voltage sensing circuits 512, 524 are provided to respective isolation transformers 516, 522 and the output of the current sensing circuit 514 is provided to another isolation transformer 518. The outputs of the isolation transformers 516, 518, 522 in the on the primary side of the power transformer 508 (non-patient-isolated side) are provided to a one or more analog-to-digital converters 526 (ADC). The digitized output of the ADC 526 is provided to the processor 502 for further processing and computation. The output voltages and output current feedback information can be employed to adjust the output voltage and current provided to the surgical instrument and to compute output impedance, among other parameters. Input/output communications between the processor 502 and patient isolated circuits is provided through an interface circuit 520. Sensors also may be in electrical communication with the processor 502 by way of the interface 520.

In one aspect, the impedance may be determined by the processor 502 by dividing the output of either the first voltage sensing circuit 512 coupled across the terminals labeled ENERGY1/RETURN or the second voltage sensing circuit 524 coupled across the terminals labeled ENERGY2/RETURN by the output of the current sensing circuit 514 disposed in series with the RETURN leg of the secondary side of the power transformer 508. The outputs of the first and second voltage sensing circuits 512, 524 are provided to separate isolations transformers 516, 522 and the output of the current sensing circuit 514 is provided to another isolation transformer 516. The digitized voltage and current sensing measurements from the ADC 526 are provided the processor 502 for computing impedance. As an example, the first energy modality ENERGY1 may be ultrasonic energy and the second energy modality ENERGY2 may be RF energy. Nevertheless, in addition to ultrasonic and bipolar or monopolar RF energy modalities, other energy modalities include irreversible and/or reversible electroporation and/or microwave energy, among others. Also, although the example illustrated in FIG. 8 shows a single return path RETURN may be provided for two or more energy modalities, in other aspects multiple return paths RETURNn may be provided for each energy modality ENERGYn. Thus, as described herein, the ultrasonic transducer impedance may be measured by dividing the output of the first voltage sensing circuit 512 by the current sensing circuit 514 and the tissue impedance may be measured by dividing the output of the second voltage sensing circuit 524 by the current sensing circuit 514.

As shown in FIG. 8, the generator 500 comprising at least one output port can include a power transformer 508 with a single output and with multiple taps to provide power in the form of one or more energy modalities, such as ultrasonic, bipolar or monopolar RF, irreversible and/or reversible electroporation, and/or microwave energy, among others, for example, to the end effector depending on the type of treatment of tissue being performed. For example, the generator 500 can deliver energy with higher voltage and lower current to drive an ultrasonic transducer, with lower voltage and higher current to drive RF electrodes for sealing tissue, or with a coagulation waveform for spot coagulation using either monopolar or bipolar RF electrosurgical electrodes. The output waveform from the generator 500 can be steered, switched, or filtered to provide the frequency to the end effector of the surgical instrument. The connection of an ultrasonic transducer to the generator 500 output would be preferably located between the output labeled ENERGY1 and RETURN as shown in FIG. 8. An In one example, a connection of RF bipolar electrodes to the generator 500 output would be preferably located between the output labeled ENERGY2 and RETURN. In the case of monopolar output, the preferred connections would be active electrode (e.g., pencil or other probe) to the ENERGY2 output and a suitable return pad connected to the RETURN output.

In other aspects, the generators 102, 200, 300, 400, 500 described in connection with FIGS. 1-3 and 5-8, the ultrasonic generator drive circuit 114, and/or electrosurgery/RF drive circuit 116 as described in connection with FIG. 3 may be formed integrally with any one of the surgical instruments 104, 106, 108 described in connection with FIGS. 1 and 2. Accordingly, any of the processors, digital signal processors, circuits, controllers, logic devices, ADCs, DACs, amplifiers, converters, transformers, signal conditioners, data interface circuits, current and voltage sensing circuits, direct digital synthesis circuits, multiplexer (analog or digital), waveform generators, RF generators, memory, and the like, described in connection with any one of the generators 102, 200, 300, 400, 500 can be located within the surgical instruments 104, 106, 108 or may be located remotely from the surgical instruments 104, 106, 108 and coupled to the surgical instruments via wired and/or wireless electrical connections.

Examples of waveforms representing energy for delivery from a generator are illustrated in FIGS. 9-13. FIG. 9 illustrates an example graph 600 showing first and second individual waveforms representing an RF output signal 602 and an ultrasonic output signal 604 superimposed on the same time and voltage scale for comparison purposes. These output signals 602, 604 are provided at the ENERGY output of the generator 500 shown in FIG. 8. Time (t) is shown along the horizontal axis and voltage (V) is shown along the vertical axis. The RF output signal 602 has a frequency of about 330 kHz RF and a peak-to-peak voltage of ±1V. The ultrasonic output signal 604 has a frequency of about 55 kHz and a peak-to-peak voltage of ±1V. It will be appreciated that the time (t) scale along the horizontal axis and the voltage (V) scale along the vertical axis are normalized for comparison purposes and may be different actual implementations, or represent other electrical parameters such as current.

FIG. 10 illustrates an example graph 610 showing the sum of the two output signals 602, 604 shown in FIG. 9. Time (t) is shown along the horizontal axis and voltage (V) is shown along the vertical axis. The sum of the RF output signal 602 and the ultrasonic output signal 604 shown in FIG. 9 produces a combined output signal 612 having a 2V peak-to-peak voltage, which is twice the amplitude of the original RF and ultrasonic signals shown (1V peak-to-peak) shown in FIG. 9. An amplitude of twice the original amplitude can cause problems with the output section of the generator, such as distortion, saturation, clipping of the output, or stresses on the output components. Thus, the management of a single combined output signal 612 that has multiple treatment components is an important aspect of the generator 500 shown in FIG. 8. There are a variety of ways to achieve this management. In one form, one of the two RF or ultrasonic output signals 602, 604 can be dependent on the peaks of the other output signal.

For example, FIG. 11 illustrates an example graph 620 showing a combined output signal 622 representative of a dependent sum of the output signals 602, 604 shown in FIG. 9. Time (t) is shown along the horizontal axis and voltage (V) is shown along the vertical axis. As shown in FIG. 11, the RF output signal 602 component of FIG. 9 depends on the peaks of the ultrasonic output signal 604 component of FIG. 9 such that the amplitude of the RF output signal component of the dependent sum combined output signal 622 is reduced when an ultrasonic peak is anticipated. As shown in the example graph 620 in FIG. 11, the peaks have been reduced from 2 to 1.5. In another form, one of the output signals is a function of the other output signal.

For example, FIG. 11 illustrates an example graph 630 showing an output signal 632 representative of a dependent sum of the output signals 602, 604 shown in FIG. 9. Time (t) is shown along the horizontal axis and voltage (V) is shown along the vertical axis. As shown in FIG. 12, the RF output signal is a function of the ultrasonic output signal. This provides a hard limit on the amplitude of the output. As shown in FIG. 12, the ultrasonic output signal is extractable as a sine wave while the RF output signal has distortion but not in a way to affect the coagulation performance of the RF output signal.

A variety of other techniques can be used for compressing and/or limiting the waveforms of the output signals. It should be noted that the integrity of the ultrasonic output signal 604 (FIG. 9) can be more important than the integrity of the RF output signal 602 (FIG. 9) as long as the RF output signal 602 has low frequency components for safe patient levels so as to avoid neuro-muscular stimulation. In another form, the frequency of an RF waveform can be changed on a continuous basis in order to manage the peaks of the waveform. Waveform control is important as more complex RF waveforms, such as a coagulation-type waveform 644, as illustrated in the graph 640 shown in FIG. 13, are implemented with the system. Again, time (t) is shown along the horizontal axis and voltage (V) is shown along the vertical axis.

FIGS. 14-42 (26-54) illustrate various configurations of sensors, circuits, and techniques for measuring tissue parameters to facilitate executing the various adaptive tissue identification and treatment technique described herein. FIG. 14 illustrates one aspect of an end effector 700 comprising RF data sensors 706, 708a, 708b located on the clamp arm 702. The end effector 700 comprises a clamp arm 702 and an ultrasonic blade 704. The clamp arm 702 is shown clamping tissue 710 located between the clamp arm 702 and the ultrasonic blade 704. A first sensor 706 is located in a center portion of the clamp arm 702. Second and third sensors 708a, 708b are located on lateral portions of the clamp arm 702. The sensors 706, 708a, 708b are mounted or formed integrally with on a flexible circuit 712 (shown more particularly in FIG. 15 and more particularly segmented flexible circuits 800, 900 shown in FIGS. 17 and 18) configured to be fixedly mounted to the clamp arm 702.

The end effector 700 is an example end effector for the multifunction surgical instrument 108 shown in FIGS. 1 and 2. The sensors 706, 708a, 708b are electrically connected to an energy source, such as for example, the generator 500 shown in FIG. 8. The sensors 706, 708a, 708b are powered by suitable sources within the generator and the signals generated by the sensors 706, 708a, 708b are provided to analog and/or digital processing circuits of the generator 500.

In one aspect, the first sensor 706 is a force sensor to measure a normal force F₃applied to the tissue 710 by the clamp arm 702. The second and third sensors 708a, 708b include one or more elements to apply RF energy to the tissue 710, measure tissue impedance, down force F₁, transverse forces F₂, and temperature, among other parameters. Electrodes 709a, 709b are electrically coupled to the generator and apply RF energy to the tissue 710. In one aspect, the first sensor 706 and the second and third sensors 708a, 708b are strain gauges to measure force or force per unit area. It will be appreciated that the measurements of the down force F₁, the lateral forces F₂, and the normal force F₃may be readily converted to pressure by determining the surface area upon which the force sensors 706, 708a, 708b are acting upon. Additionally, as described with particularity herein, the flexible circuit 712 may comprise temperature sensors embedded in one or more layers of the flexible circuit 712. The one or more temperature sensors may be arranged symmetrically or asymmetrically and provide tissue 710 temperature feedback to control circuits of the generator.

FIG. 15 illustrates one aspect of the flexible circuit 712 shown in FIG. 14 in which the sensors 706, 708a, 708b may be mounted to or formed integrally therewith. The flexible circuit 712 is configured to fixedly attach to the clamp arm 702. As shown particularly in FIG. 15, asymmetric temperature sensors 714a, 714b are mounted to the flexible circuit 712 to enable measuring the temperature of the tissue 710 (FIG. 14).

FIG. 16 is a cross-sectional view of the flexible circuit 712 shown in FIG. 15. The flexible circuit 712 comprises multiple layers and is fixedly attached to the clamp arm 702. A top layer of the flexible circuit 712 is an electrode 709a, which is electrically coupled to an energy source, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), to apply RF energy to the tissue 710 (FIG. 14). A layer of electrical insulation 718 is provided below the electrode 709a layer to electrically isolate the sensors 714a, 706, 708a from the electrode 709a. The temperature sensors 714a are disposed below the layer of electrical insulation 718. The first force (pressure) sensor 706 is located below the layer containing the temperature sensors 714a and above a compressive layer 720. The second force (pressure) sensor 708a is located below the compressive layer 720 and above the clamp arm 702 frame.

FIG. 17 illustrates one aspect of a segmented flexible circuit 800 configured to fixedly attach to a clamp arm 804 of an end effector. The segmented flexible circuit 800 comprises a distal segment 802a and lateral segments 802b, 802c that include individually addressable sensors to provide local tissue control, as described herein in connection with FIGS. 14-16, for example. The segments 802a, 802b, 802c are individually addressable to treat tissue and to measure tissue parameters based on individual sensors located within each of the segments 802a, 802b, 802c. The segments 802a, 802b, 802c of the segmented flexible circuit 800 are mounted to the clamp arm 804 and are electrically coupled to an energy source, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), via electrical conductive elements 806. A Hall effect sensor 808, or any suitable magnetic sensor, is located on a distal end of the clamp arm 804. The Hall effect sensor 808 operates in conjunction with a magnet to provide a measurement of an aperture defined by the clamp arm 804, which otherwise may be referred to as a tissue gap, as shown with particularity in FIG. 19.

FIG. 18 illustrates one aspect of a segmented flexible circuit 900 configured to mount to a clamp arm 904 of an end effector. The segmented flexible circuit 1900 comprises a distal segment 902a and lateral segments 902b, 902c that include individually addressable sensors for tissue control, as described herein in connection with FIGS. 14-17, for example. The segments 902a, 902b, 902c are individually addressable to treat tissue and to read individual sensors located within each of the segments 902a, 902b, 902c. The segments 902a, 902b, 902c of the segmented flexible circuit 900 are mounted to the clamp arm 904 and are electrically coupled to an energy source, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), via electrical conductive elements 906. A Hall effect sensor 908, or other suitable magnetic sensor, is provided on a distal end of the clamp arm 904. The Hall effect sensor 908 operates in conjunction with a magnet to provide a measurement of an aperture defined by the clamp arm 904 of the end effector or tissue gap as shown with particularity in FIG. 19. In addition, a plurality of lateral asymmetric temperature sensors 910a, 910b are mounted on or formally integrally with the segmented flexible circuit 900 to provide tissue temperature feedback to control circuits in the generator.

FIG. 19 illustrates one aspect of an end effector 1000 configured to measure a tissue gap G_T. The end effector 1000 comprises a jaw member 1002 and a clamp arm 904. The flexible circuit 900 as described in FIG. 18, is mounted to the clamp arm 904. The flexible circuit 900 comprises a Hall effect sensor 908 that operates with a magnet 1004 mounted to the jaw member 1002 to measure the tissue gap G_T. This technique can be employed to measure the aperture defined between the clamp arm 904 and the jaw member 1002. The jaw member 1002 may be an ultrasonic blade.

FIG. 20 illustrates one aspect of a left-right segmented flexible circuit 1100. The left-right segmented flexible circuit 1100 comprises a plurality of segments L1-L5 on the left side of the left-right segmented flexible circuit 1100 and a plurality of segments R1-R5 on the right side of the left-right segmented flexible circuit 1100. Each of the segments L1-L5 and R1-R5 comprise temperature sensors and force sensors to sense tissue parameters locally within each segment L1-L5 and R1-R5. The left-right segmented flexible circuit 1100 are configured to influence the RF treatment energy based on tissue parameters sensed locally within each of the segments L1-L5 and R1-R5.

FIG. 21 illustrates one aspect of an end effector 1200 comprising segmented flexible circuit 1100 as shown in FIG. 20. The end effector 1200 comprises a clamp arm 1202 and an ultrasonic blade 1204. The segmented flexible circuit 1100 is mounted to the clamp arm 1202. Each of the sensors disposed within the segments 1-5 are configured to detect the presence of tissue positioned between the clamp arm 1202 and the ultrasonic blade 1204 and represent tissue zones 1-5. In the configuration shown in FIG. 21, the end effector 1200 is shown in an open position ready to receive or grasp tissue between the clamp arm 1202 and the ultrasonic blade 1204.

FIG. 22 illustrates the end effector 1200 shown in FIG. 21 with the clamp arm 1202 clamping tissue 1206 between the clamp arm 1202 and the ultrasonic blade 1204. As shown in FIG. 22, the tissue 1206 is positioned between segments 1-3 and represents tissue zones 1-3. Accordingly, tissue 1206 is detected by the sensors in segments 1-3 and the absence of tissue (empty) is detected in section 1208 by segments 4-5. The information regarding the presence and absence of tissue 1206 positioned within certain segments 1-3 and 4-5, respectively, is communicated to a control circuit of the generator, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8). The generator 500 is configured to energize only the segments 1-3 where tissue 1206 is detected and does not energize the segments 4-5 where tissue is not detected. It will be appreciated that the segments 1-5 may contain any suitable temperature, force/pressure, and/or Hall effect magnetic sensors to measure tissue parameters of tissue located within certain segments 1-5 and electrodes to deliver RF energy to tissue located in certain segments 1-5.

FIG. 23 illustrates graphs 1300 of energy applied by the right and left side of an end effector based on locally sensed tissue parameters. As discussed herein, the clamp arm of an end effector may comprise temperature sensors, force/pressure sensors, Hall effector sensors, among others, along the right and left sides of the clamp arm as shown, for example, in FIGS. 14-22. Thus, RF energy can be selectively applied to tissue positioned between the clam jaw and the ultrasonic blade. The top graph 1302 depicts power P_Rapplied to a right side segment of the clamp arm versus time (t) based on locally sensed tissue parameters. Thus, the generator, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), is configured to measure the sensed tissue parameters and to apply power P_Rto a right side segment of the clamp arm. The generator 500 delivers an initial power level P₁to the tissue via the right side segment and then decreases the power level to P₂based on local sensing of tissue parameters (e.g., temperature, force/pressure, thickness) in one or more segments. The bottom graph 1304 depicts power P_Lapplied to a left side segment of the clamp arm versus time (t) based on locally sensed tissue parameters. The generator 500 delivers an initial power level of P₁to the tissue via the left side segment and then increases the power level to P₃based local sensing of tissue parameters (e.g., temperature, force/pressure, thickness). As depicted in the bottom graph 1304, the generator is configured to re-adjust the energy delivered P₃based on sensing of tissue parameters (e.g., temperature, force/pressure, thickness).

FIG. 24 illustrates a graph 1400 depicting one aspect of adjustment of threshold due to the measurement of a secondary tissue parameter such as continuity, temperature, pressure, and the like. The horizontal axis of the graph 1400 is time (t) and the vertical axis is tissue impedance (Z). The curve 1412 represents the change of tissue impedance (Z) over time (t) as different energy modalities are applied to the tissue. With reference also to FIGS. 20-22, the original threshold 1402 is applied when tissue is detected in all five segments 1-5 (tissue zones 1-5) and the adjusted threshold 1404 is applied when the tissue is detected in tissue segments 1-3 (tissue zones 1-3). Accordingly, once the tissue is located in particulars segments (zones) the control circuit in the generator adjusts the threshold accordingly.

As shown in FIG. 24, the curve 1412 includes three separate sections 1406, 1408, 1410. The first section 1406 of the curve 1412 represents the time when RF energy is applied to the tissue in tissue zones 1-3 until the tissue impedance drops below the adjusted threshold 1404. At that point 1414, which may indicate that a tissue seal is completed, the energy modality applied to tissue zones 1-3 is changed from RF energy to ultrasonic energy. The ultrasonic energy is then applied in the second and third sections 1408, 1410 and the impedance rises exponentially until the tissue is severed or cut.

FIG. 25 is a cross-sectional view of one aspect of a flexible circuit 1500 comprising RF electrodes and data sensors embedded therein. The flexible circuit 1500 can be mounted to the right or left portion of an RF clamp arm 1502, which is made of electrically conductive material such as metal. Below the RF clamp arm 1502 down force/pressure sensors 1506a, 1506b are embedded below a laminate layer 1504. A transverse force/pressure sensor 1508 is located below the down force/pressure sensor 1506a, 1506b layer and a temperature sensor is 1510 is located below the transverse force/pressure sensor 1508. An electrode 1512 electrically coupled to the generator and configured to apply RF energy to the tissue 1514 is located below the temperature sensor 1510.

FIG. 26 is a cross-sectional view of one aspect of an end effector 1600 configured to sense force or pressure applied to tissue located between a clamp arm and an ultrasonic blade. The end effector 1600 comprises a clamp jaw 1602 and a flexible circuit 1604 fixedly mounted to the clamp arm 1602. The clamp arm 1602 applies forces F₁and F₂to the tissue 1606 of variable density and thickness, which can be measure by first and second force/pressure sensors 1608, 1610 located in different layers of the flexible circuit 1604. A compressive layer 1612 is sandwiched between the first and second force/pressure sensors 1608, 1610. An electrode 1614 is located on outer portion of the flexible circuit 1604 which contacts the tissue. As described herein, other layers of the flexible circuit 1604 may comprise additional sensors such temperature sensors, thickness sensors, and the like.

FIGS. 27-29 illustrate various schematic diagrams of flexible circuits of the signal layer, sensor wiring, and an RF energy drive circuit. FIG. 27 is a schematic diagram of one aspect of a signal layer of a flexible circuit 1700. The flexible circuit 1700 comprises multiple layers (˜4 to ˜6, for example). One layer will supply the integrated circuits with power and another layer with ground. Two additional layers will carry the RF power RF1 and RF2 separately. An analog multiplexer switch 1702 has eight bidirectional translating switches that can be controlled through the I²C bus. The SCL/SDA upstream pair fans out to eight downstream pairs, or channels. Any individual SCn/SDn channel or combination of channels can be selected, determined by the contents of a programmable control register. The upstream pairs SCL/SDA are connected to a control circuit in the generator. There are six down stream sensors, three on each side of the clamp arm. A first side 1704a comprises a first thermocouple 1706a, a first pressure sensor 1708a, and a first Hall effect sensor 1710a. A second side 1704b comprises a second thermocouple 1706b, a second pressure sensor 1708b, and a second Hall effect sensor 1710b. FIG. 28 is a schematic diagram 1750 of sensor wiring for the flexible circuit 1700 shown in FIG. 27.

FIG. 29 is a schematic diagram of one aspect of an RF energy drive circuit 1800. The RF energy drive circuit 1800 comprises an analog multiplexer 1702 described in connection with FIG. 27. The analog multiplexer multiplexes various signals from the upstream channels SCL/SDA. A current sensor 1802 is coupled in series with the return or ground leg of the power supply circuit to measure the current supplied by the power supply. An FET temperature sensor 1804 provided the ambient temperature. A pulse width modulation (PWM) watchdog timer 1808 automatically generates a system reset if the main program neglects to periodically service it. It is provided to automatically reset the RF energy drive circuit 1800 when it hangs because of a software or hardware fault.

A drive circuit 1806 provides left and right RF energy outputs. The digital signal is provided to the SCL/SDA inputs of the analog multiplexer 1702 from a control circuit of the generator. A digital-to-analog converter (DAC) converts the digital input to an analog output to drive a pulse width modulation (PWM) circuit 1812 coupled to an oscillator 1814. The PWM circuit 1812 provides a first gate drive signal 1816a to a first transistor output stage 1818a to drive a first RF (Left) energy output. The PWM circuit 1812 also provides a second gate drive signal 1816b to a second transistor output stage 1818 to drive a second RF (Right) energy output.

The circuits 1700, 1750, 1800 described in connection with FIGS. 27-29 are electrically coupled to the generators 200, 300, 400, 500 shown in FIGS. 5-7. For example, the circuits 1700, 1750, 1800 may be coupled to the generator 200 via the signal conditioning circuit 244 and may be coupled to the generator 500 through the interface circuit 520.

FIG. 30 is a graphical representation 1900 of measuring tissue gap at a preset time. A first graph 1902 represents tissue impedance Z versus time (t) where the horizontal axis represents time (t) and the vertical axis represents tissue impedance Z. A second graph 1904 represents change in tissue gap Δ_gapversus time (t) where the horizontal axis represents time (t) and the vertical axis represents change in tissue gap Δ_gap. A third graph 1906 represents force F versus time (t) where the horizontal axis represents time (t) and the vertical axis represents force F. Wth a constant force F applied to tissue and impedance Z interrogation to define a wait period, energy modality (e.g., RF and ultrasonic) and motor control parameters, displacement at a time provides velocity. With reference to the three graphs 1902, 1904, 1906, impedance sensing energy is applied during a first period 1908 to determine the tissue type such as thin mesentery tissue (solid line), intermediate thickness vessel tissue (dashed line), or thick uterus/bowel tissue (dash-dot line).

As shown in the third graph 1906, the clamp arm initially applies a force which ramps up from zero exponentially until it reaches a constant force 1924. The preset time t₁is selected such that it occurs some time after the clamp arm force reaches a constant force 1924. As shown in the first and second graphs 1902, 1904, from the time the clamp force is applied to the mesentery tissue until the preset time t₁is reached, the change in tissue gap Δ_gapcurve 1912 decreases exponentially and the tissue impedance curve 1918 also decreases until the preset time t₁is reached. From the preset time t₁, a short delay 1928 is applied before treatment energy is applied to the mesentery tissue at t_E1.

As shown in the first and second graphs 1902, 1904, from the time the clamp force is applied to the vessel tissue until the preset time t₁is reached, the change in tissue gap Δ_gapcurve 1916 also decrease exponentially and the tissue impedance curve 1920 also decreases until the preset time t₁is reached. From the preset time t₁, a medium delay 1930 is applied before treatment energy is applied to the vessel tissue at t_E2.

As shown in the first and second graphs 1902, 1904, from the time the clamp force is applied to the uterus/bowel tissue until the preset time t₁is reached, the change in tissue gap Δ_gapcurve 1914 drops exponentially and the tissue impedance curve 1914 also drops until the preset time t₁is reached. From the preset time t₁, a short delay 1928 is applied before treatment energy is applied to the mesentery tissue at t_E1.

FIG. 31 is a time to preset force 2008 versus time graph 2000 for thin, medium, and thick tissue types. The horizontal axis represents time (t) and the vertical axis represents force (F) applied by the clamp arm to the tissue. The graph 2000 depicts three curves, one for thin tissue 2002 shown in solid line, one for medium thickness tissue 2004 shown in dash-dot line, and thick tissue 2006 in dashed line. The graph 2000 depicts measuring time at a preset force as an alternative to tissue gap to control delayed energy mode and other control parameters. Accordingly, the time to preset force 2008 for thick tissue 2006 is t_1a, the time to preset force 2008 for medium thickness tissue 2004 is t_1b, and the time to preset force 2008 for thin tissue 2002 is t_1c.

Once the force reaches the preset force 2008, energy is applied to the tissue. For thin tissue 2002 the time to preset t_1c>0.5 seconds and then RF energy is applied for an energizing period t_eof about 1-3 seconds. For thick tissue 2006 the time to preset t_1a<0.5 seconds and then RF energy is applied for an energizing period t_eof about 5-9 seconds. For medium thickness tissue 2004 the time to preset t_1bis about 0.5 seconds and then RF energy is applied for an energizing period t_eof about 3 to 5 seconds.

FIG. 32 is a graphical depiction of a graph 2100 of three curves 2102, 2104, 2106, where the first curve 2102 represents power (P), voltage (V_RF), and current (I_RF) versus tissue impedance (Z), the second curve 2104 and third curve 2106 represent tissue impedance (Z) versus time (t). The first curve 2102 illustrates the application of power (P) for thick tissue impedance range 2110 and thin tissue impedance range 2112. As the tissue impedance Z increases, the current I_RFdecrease and the voltage V_RFincreases. The power curve P increases until it reaches a maximum power output 2108 which coincides with the intersection 2114 of the current I_RFand voltage V_RFcurves.

The second curve 2104 represents the measured tissue impedance Z versus time (t). The tissue impedance threshold limit 2120 is the cross over limit for switching between the RF and ultrasonic energy modalities. For example, as shown in FIG. 32, RF energy is applied while the tissue impedance is above the tissue impedance threshold limit 2120 and ultrasonic energy 2124 is applied while the tissue impedance is below the tissue impedance threshold limit 2120. Accordingly, with reference back to the second curve 2104, the tissue impedance of the thin tissue curve 2116 remains above the tissue impedance threshold limit 2120, thus only RF energy modality is applied to the tissue. On the other hand, RF energy modality is applied to the tick tissue while the impedance is above the tissue impedance threshold limit 2120 and ultrasonic energy is applied to the tissue when the impedance is below the tissue impedance threshold limit 2120. Accordingly, the energy modality switches from RF to ultrasonic when the tissue impedance falls below the tissue impedance threshold limit 2120 and the energy modality switches from ultrasonic to RF when the tissue impedance rises above the tissue impedance threshold limit 2120.

FIG. 33 is a plan view of one aspect of an end effector 2200. The end effector 2200 comprises a clamp arm 2202 and a shaft 2204. The clamp arm 2202 pivots about pivot point 2206 and defines a pivot angle. FIG. 34 is a side view of the end effector 2200 shown in FIG. 33 with a partial cut away view to expose the underlying structure of the clamp arm 2202 and an ultrasonic blade 2208. An electrode 2210 is fixedly mounted to the clamp arm 2202. The electrode 2210 is electrically coupled to the generator and is configured to apply RF energy to tissue located between the clamp arm 2202 and the ultrasonic blade 2208. FIG. 35 is partial sectional view of the end effector shown in FIGS. 33, 34 to expose the ultrasonic blade and right and left electrodes 2210a, 2210b, respectively.

FIG. 36 is a cross-sectional view taken at section 36-36 of the end effector 2200 shown in FIG. 33. The end effector 2200 comprises an ultrasonic blade 2208 acoustically coupled to an ultrasonic transducer which is electrically driven by the generator. The clamp arm 2202 comprises an electrode 2210a on the right side and an electrode 2210b on the left side (from the perspective of the operator). The right side electrode 2210a defines a first width W₁and defines a first gap G₁between the electrode 2210a and the ultrasonic blade 2208. The left side electrode 2210b defines a second width W₂and defines a second gap G₂between the electrode 2210b and the ultrasonic blade 2208. In one aspect the first width W₁is less than the second width W₂and the first gap G₁is less than the second gap G₂. Wth reference also to FIG. 35, a soft polymeric pad 2212 is located between the ultrasonic blade 2208 and the clamp arm 2202. A high density polymeric pad 2214 is located adjacent the soft polymeric pad 2212 to prevent the ultrasonic blade 2208 from shorting the electrodes 2210a, 2210b. In one aspect, the soft polymeric pads 2212, 2214 can be made of polymers known under the tradename TEFLON (polytetrafluoroethylene polymers and copolymers), for example.

FIG. 37 is cross-sectional view taken at section 37-37 of the end effector 2200 shown in FIG. 33. At the plane where section 37-37 the end effector 2200 is thinner and has more curvature than section 36-36. The right side electrode 2210a defines a third width W₃and defines a third gap G₃between the electrode 2210a and the ultrasonic blade 2208. The left side electrode 2210b defines a fourth width W₄and defines a fourth gap G₄between the electrode 2210b and the ultrasonic blade 2208. In one aspect the third width W₃is less than the fourth width W₄and the third gap G₃is less than the fourth gap G₄.

FIG. 38 is a cross-sectional view taken at section 36-36 of the end effector 2200 shown in FIG. 33, except that the ultrasonic blade 2208′ has a different geometric configuration. The end effector 2200′ comprises an ultrasonic blade 2208′ cacoustically coupled to an ultrasonic transducer which is electrically driven by the generator. The clamp arm 2202′ comprises an electrode 2210a′ on the right side and an electrode 2210b′ on the left side (from the perspective of the operator). The right side electrode 2210a′ defines a first width W₁and defines a first gap G₁between the electrode 2210a′ and the ultrasonic blade 2208′. The left side electrode 2210b′ defines a second width W₂and defines a second gap G₂between the electrode 2210b′ and the ultrasonic blade 2208′. In one aspect the first width W₁is less than the second width W₂and the first gap G₁is less than the second gap G₂. A high density polymeric pad 2214′ is located adjacent the soft polymeric pad 2212′ to prevent the ultrasonic blade 2208′ from shorting the electrodes 2210a′, 2210b′. In one aspect, the soft polymeric pads 2212′, 2214′ can be made of polymers known under the tradename TEFLON (polytetrafluoroethylene polymers and copolymers), for example.

FIG. 39 is cross-sectional view taken at section 37-37 of the end effector 2200 shown in FIG. 33, except that the ultrasonic blade 2208′ has a different geometric configuration. At the plane where section 37-37 the end effector 2200′ is thinner and has more curvature than the end effector 2200′ at section 36-36. The right side electrode 2210a′ defines a third width W₃and defines a third gap G₃between the electrode 2210a′ and the ultrasonic blade 2208′. The left side electrode 2210b′ defines a fourth width W₄and defines a fourth gap G₄between the electrode 2210b′ and the ultrasonic blade 2208′. In one aspect the third width W₃is less than the fourth width W₄and the third gap G₃is less than the fourth gap G₄.

FIG. 40 is a cross-sectional view taken at section 36-36 of the end effector 2200 shown in FIG. 33, except that the ultrasonic blade 2208″ has a different geometric configuration. The end effector 2200″ comprises an ultrasonic blade 2208″ cacoustically coupled to an ultrasonic transducer which is electrically driven by the generator. The clamp arm 2202″ comprises an electrode 2210a″ on the right side and an electrode 2210b″ on the left side (from the perspective of the operator). The right side electrode 2210a″ defines a first width W₁and defines a first gap G₁between the electrode 2210a″ and the ultrasonic blade 2208″. The left side electrode 2210b″ defines a second width W₂and defines a second gap G₂between the electrode 2210b″ and the ultrasonic blade 2208″. In one aspect the first width W₁is less than the second width W₂and the first gap G₁is less than the second gap G₂. A high density polymeric pad 2214″ is located adjacent the soft polymeric pad 2212″ to prevent the ultrasonic blade 2208″ from shorting the electrodes 2210a″, 2210b″. In one aspect, the polymeric pads 2212″, 2214″ can be made of polymers known under the tradename TEFLON (polytetrafluoroethylene polymers and copolymers), for example.

FIG. 41 is cross-sectional view taken at section 37-37 of the end effector 2200 shown in FIG. 33, except that the ultrasonic blade 2208″ has a different geometric configuration. At the plane where section 37-37 the end effector 2200″ is thinner and has more curvature than the end effector 2200″ at section 36-36. The right side electrode 2210a″ defines a third width W₃and defines a third gap G₃between the electrode 2210a″ and the ultrasonic blade 2208″. The left side electrode 2210b″ defines a fourth width W₄and defines a fourth gap G₄between the electrode 2210b″ and the ultrasonic blade 2208″. In one aspect the third width W₃is less than the fourth width W₄and the third gap G₃is less than the fourth gap G₄.

The surgical instruments described herein also can include features to allow the energy being delivered by the generator to be dynamically changed based on the type of tissue being treated by an end effector of a surgical instrument and various characteristics of the tissue. In one aspect, a technique for controlling the power output from a generator, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), that is delivered to the end effector of the surgical instrument can include an input that represents the tissue type to allow the energy profile from the generator to be dynamically changed during the procedure based on the type of tissue being effected by the end effector of the surgical instrument.

As disclosed herein, techniques for controlling a generator based on the tissue type may be provided. Various techniques can be used to select a power profile to allow the energy being delivered from the generator to dynamically change based on the tissue type being treated by the surgical instrument.

FIG. 42A illustrates an end effector 2300 comprising a clamp arm 2302 and an ultrasonic blade 2304, where the clamp arm 2302 includes electrodes 2306. The end effector 2300 can be employed in one of the surgical instruments 104, 106, 108 referred to in FIGS. 1-3. In addition to the end effector 122, 124, 125, the surgical instruments 104, 106, 108 include a handpiece 105, 107, 109 and a shaft 126, 127, 129, respectively. The end effectors 122, 124, 125 may be used to compress, cut, and/or seal tissue. Referring to FIG. 42A, the end effector 2300, similar to the end effectors 122, 124, 125 shown in FIGS. 1-3, may be positioned by a physician to surround tissue 2308 prior to compression, cutting, or stapling. As shown in FIG. 42A, no compression may be applied to the tissue while preparing to use the end effector 2300. As shown in FIG. 42A, the tissue 2308 is not under compression between the clamp arm 2302 and the ultrasonic blade 2304.

Referring now to FIG. 42B, by engaging the trigger on the handle of a surgical instrument, the physician may use the end effector 2300 to compress the tissue 2308. In one aspect, the tissue 2308 may be compressed to its maximum threshold, as shown in FIG. 42B. As shown in FIG. 42A, the tissue 2308 is under maximum compression between the clamp arm 2302 and the ultrasonic blade 2304.

Referring to FIG. 43A, various forces may be applied to the tissue 2308 by the end effector 2300. For example, vertical forces F1 and F2 may be applied by the clamp arm 2302 and the ultrasonic blade 2304 of the end effector 2300 as tissue 2308 is compressed between the two. Referring now to FIG. 43B, various diagonal and/or lateral forces also may be applied to the tissue 2308 when compressed by the end effector 2300. For example, a force F3 may be applied. For the purposes of operating a medical device such as the surgical instruments 104, 106, 108 it may be desirable to sense or calculate the various forms of compression being applied to the tissue by the end effector. For example, knowledge of vertical or lateral compression may allow the end effector to more precisely or accurately apply a staple operation or may inform the operator of the surgical instrument such that the surgical instrument can be used more properly or safely.

In one form, a strain gauge can be used to measure the force applied to the tissue 2308 by the end effector shown in FIGS. 42A-B and 43A-B. A strain gauge can be coupled to the end effector 2300 to measure the force on the tissue 2308 being treated by the end effector 2300. Wth reference now also to FIG. 44, in the aspect illustrated in FIG. 44, a system 2400 for measuring forces applied to the tissue 2308 comprises a strain gauge sensor 2402, such as, for example, a micro-strain gauge, is configured to measure one or more parameters of the end effector 2300 such as, for example, the amplitude of the strain exerted on a clamp arm of an end effector, such as the clamp arm 2302 of FIGS. 43A-B, during a clamping operation, which can be indicative of the tissue compression. The measured strain is converted to a digital signal and provided to a processor 2410 of a microcontroller 2408. A load sensor 2404 can measure the force to operate the ultrasonic blade 2304 to cut the tissue 2308 captured between the clamp arm 2302 and the ultrasonic blade 2304 of the end effector 2300. A magnetic field sensor 2406 can be employed to measure the thickness of the captured tissue 2308. The measurement of the magnetic field sensor 2406 also may be converted to a digital signal and provided to the processor 2410.

Further to the above, a feedback indicator 2414 also can be configured to communicate with the microcontroller 2408. In one aspect, the feedback indicator 2414 can be disposed in the handle of a surgical instrument, such as those shown in FIGS. 1-3. Alternatively, the feedback indicator 2414 can be disposed in a shaft assembly of a surgical instrument, for example. In any event, the microcontroller 2408 may employ the feedback indicator 2414 to provide feedback to an operator of the surgical instrument with regard to the adequacy of a manual input such as, for example, a selected position of a firing trigger that is used to cause the end effector to clamp down on tissue. To do so, the microcontroller 2408 may assess the selected position of the clamp arm 2302 and/or firing trigger. The measurements of the tissue 2308 compression, the tissue 2308 thickness, and/or the force required to close the end effector 2300 on the tissue, as respectively measured by the sensors 2402, 2404, 2406, can be used by the microcontroller 2408 to characterize the selected position of the firing trigger and/or the corresponding value of the speed of end effector. In one instance, a memory 2412 may store a technique, an equation, and/or a look-up table which can be employed by the microcontroller 2408 in the assessment.

The generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), surgical instruments 104, 106, 108 (FIGS. 1-3), and end effectors 122, 124, 125, 700, 800, 900, 1000, 1100, 1200, 2200, 2200′, 2200″, 2300 (FIGS. 1-3, 14-22, 33-43B) described herein may be employed alone or in combination to perform surgical procedures in accordance with the techniques and processes described hereinbelow. Nevertheless, for conciseness and clarity, the surgical procedures are described with reference to the multifunction surgical instrument 108 and the generator 500. The multifunction surgical instrument 108 comprises an end effector 125 which includes a clamp arm 145 and an ultrasonic blade 149. The end effector 125 may be configured with any of the structural or functional features of any one of the end effectors 122, 124, 125, 700, 800, 900, 1000, 1100, 1200, 2200, 2200′, 2200″, 2300 to provide electrodes to apply RF energy to tissue, temperature sensors, force/pressure sensors, and gap measurement sensors, as described hereinabove.

Techniques for Determining Tissue Coefficient of Friction/Tissue Coefficient of Coagulation

In one aspect, the present disclosure provides a technique for determining a tissue coefficient of friction/tissue coefficient of coagulation to control the power output from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). The power delivered to an end effector of a surgical instrument can vary based on a tissue coefficient of friction. The energy profile from the generator can be adjusted based on the tissue coefficient of friction and dynamically switched during the procedure between RF and ultrasonic energy modalities based on the tissue impedance to treat the tissue clamped between a clamp arm and an ultrasonic blade of the end effector of the surgical instrument. For conciseness and clarity of disclosure, the techniques for determining a tissue coefficient of friction will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

The following description provides techniques for determining a tissue coefficient of friction μ. In order to accurately calculate the tissue coefficient of friction μ of the tissue 2308, the force applied to the tissue 2308 must be in a certain range to ensure that there is sufficient contact between the tissue 2308 and the end effector 2300 and that therapeutic amounts of energy are being delivered to the end effector 2300. For example, in one aspect, a minimum load on the tissue 2308 can be 1.5 lbs. to ensure that there is enough contact between the tissue 2308 and the end effector 2300, and a maximum load on the tissue 2308 can be 2.2 lbs. to ensure that a therapeutic amount of energy is being used. These values can be used with a power level 1. In addition, the force is measured using any of the above measurement components and techniques at various loads on the tissue 2308. At least two measurements can be taken at two different loads. For example, power can be measured at 1.76 lbs. (800 grams) and 2.2 lbs. (1000 grams) in order to graph power versus force. It can be more accurate, however, to take measurements at a plurality of loads and store the values in a buffer. In one form, a buffer can be filled with values for each incremental gram between 2400 grams and 1000 grams and can use various rules, such as the first in first out rule, to store the values until the slope value is maximized. A new regression can be performed each time a new value is added to the buffer and a value is dropped from the buffer. Various other methods can be used as well to calculate the slope value.

A functional model for heating of tissue can be represented in a simple frictional model:

{dot over (Q)}=μ·ν·N Equation 1

where {dot over (Q)} is the rate of heat generation, ν is the rms velocity of the ultrasonic motion at the tip of the blade, and N is the normal force driving tissue against the ultrasonic blade. The tissue coefficient of friction, μ, is the proportionality constant that makes the statement true and it relates to tissue properties. It is therefore referred to as the tissue coefficient of friction μ and may be referred to interchangeably as the tissue coefficient of coagulation. As is known in the art, friction is the force resisting the relative motion of solid surfaces, fluid layers, and material elements sliding against each other.

In practice, {dot over (Q)} is the measured amount power equal to the product of the rms values of current and voltage when driven at zero phase. The velocity is the product of the rms displacement, d, times the radian frequency or ν=2πf·d. In the case of an ultrasonic surgical system this is the frequency at resonance which equals 55.5 kHz for the ultrasonic system. Furthermore d is proportional to the current driving the system, which is set by the level on the generator. The factor ν is readily calculated. N is the normal force which is either set by the instrument design at full trigger closure or can be measured with a force gage/strain gage. Since {dot over (Q)}, ν, and N are calculable from known parameters, then can be estimated by rearranging Equation 1:

$μ = \frac{\dot{Q}}{v \cdot N}$

Note that removing the quiescent power from {dot over (Q)} and updating the frequency f as the resonance drifts lower, will increase the repeatability and accuracy of the estimated tissue coefficient of friction μ. In order to determine the type of tissue being treated by the end effector of the surgical instrument, a tissue coefficient of friction μ can be calculated. The calculated tissue coefficient of friction is compared to a database of tissue coefficients of friction that correlates each tissue coefficient of friction with a tissue type, as will be discussed in more detail below. The calculated tissue coefficient of friction and its related tissue type are used by a technique to control the energy being delivered from the generator to the surgical instrument. In one form, the tissue coefficient of friction μ is described by the above where {dot over (Q)} is the rate of heat generation, ν is the velocity of the ultrasonic motion of the end effector, and N is the force applied to the tissue by the end effector. The velocity ν of the ultrasonic motion is a known value from the settings of the generator. Since the value ν is a known value, the tissue coefficient of friction μ can be calculated using the slope of a graph of heat generation versus force on the tissue.

The force applied to the tissue by the end effector can be measured in a variety of ways using different type of components to measure force. This force measurement can be used, for example in the equation above, to determine the tissue coefficient of friction of the tissue being treated to determine its tissue type.

Looking at the equation {dot over (Q)}=μ·ν·N the product of the tissue coefficient of friction and velocity, μ·ν, is the slope of the relation of heat generation and normal load. Because ν is known, μ can be determined by the slope of a graph of heat generation versus normal load. An example of a graph 2500 of power (Watts) shown along the vertical axis versus force (g) shown along the horizontal axis as measured with a plurality of plotted data points is illustrated in FIGS. 45-46. FIG. 45 illustrates graphs 2500 for a porcine carotid curves 2502, 2504 at two different power levels, porcine bowel curve 2506, and dry chamois curve 2508. The data for a carotid artery at Level 3 is also shown. These are single measurements and there are no means and standard deviations to test for differences. While ideally the values of the tissue coefficient of friction μ at Levels 1 and 3 should be the same, the values at 0.30 and 0.35 are sufficiently close to believe that μ is an intrinsic property of the tissue.

FIG. 46 illustrates the same graphs 2500′ as FIG. 45, but only the sections of each graph that are substantially linear. The linear sections 2502′, 2504′, 2506′, 2508′ of each curve 2502, 2504, 2506, 2508 (FIG. 45) are located in the region of the curve where the force was greater than the initial low level of force used. Each of the linear sections 2502′, 2504′, 2506′, 2508′ can be modeled as a regression line in the form of:

y=mx+b Equation 2

where y is the dependent variable (Power [Watts]), x is the independent variable (Force [g]), m is the slope of the line, and b is the y-intercept.

Each of the linear sections 2502′, 2504′, 2506′, 2508′ also are characterized by R-squared (R²), where R²is a statistical measure of how close the data are to the fitted regression line y. It is also known as the coefficient of determination, or the coefficient of multiple determination for multiple regression. The definition of R²is the percentage of the response variable variation that is explained by the linear model y. In other words:

R²=Explained variation/Total variation

R²is always between 0 and 100% where 0% indicates that the model explains none of the variability of the response data around its mean and 100% indicates that the model explains all the variability of the response data around its mean. In general, the higher the R², the better the model fits the data.

In the example illustrated in FIG. 46, the regression line and R²for the linear section 2502′ representing porcine carotid tissue at power level 1 are:

y=0.0137x+0.2768
R²=0.9902

The regression line and R²for the linear section 2504′ representing porcine carotid tissue at power level 3 are:

y=0.0237x+8.9847
R²=0.978

The regression line and R²for the linear section 906′ representing bowel tissue at power level 1 are:

y=0.0085x+10.587
R²=0.9147

The regression line and R²for the linear section 2508′ representing chamois tissue at power level 1 are:

y=0.034x+0.0735
R²=0.9949

The calculated tissue coefficient of friction μ is compared to a database of tissue coefficients of friction that correlated each coefficient with a tissue type. For example, Table 1 includes example tissue coefficients of friction μ as calculated from the plots of power and force illustrated in FIGS. 45-46 for each of the porcine carotid curves 2502, 2504 at two different power levels, porcine bowel curve 2506, and dry chamois curve 2508.

TABLE 1

Coefficient of

Tissue Type
Power Level
Friction μ

Porcine carotid
1
0.30

Porcine carotid
3
0.35

Porcine bowel
1
0.19

Dry chamois
1
0.75

Assumptions: Ultrasonic bade amplitude is nominally 75 μm p-p at level 5 and the frequency f is 55.5 kHz. It will be appreciated that the power levels referenced above are specific to the LCS product and level 5 of the GEN11 generator available from Ethicon Endo-Surgery, Inc. that is compatible with devices known under the tradename HARMONIC and ENSEAL, also available from Ethicon Endo-Surgery, Inc.

It should be noted that the tissue coefficient of friction μ for the porcine carotid tissue at various power levels should be the same as the tissue coefficient of friction μ is a value intrinsic to the tissue. The values of 0.30 and 0.35 for the calculated tissue coefficients of friction μ are substantially close enough to show that the tissue coefficient of friction μ is intrinsic to the tissue itself.

One technique for determining the slope is to measure power delivered at two loads. Assuming Level 1 is used for this calculation, then the power could be measured at nominally 800 grams (1.76 lbs) and 1000 grams (2.2 lbs). However just using the two points can be inaccurate. It is better to fill a buffer of approximately 201 points for every gram in the 800 to 1000 gram range inclusive. The buffer could be slide advanced using a first-in-first-out (FIFO) rule until the R²value is maximized. A new regression would be performed each time a new point is added and an old point is dropped. Other schemes can be envisioned as well. The calculated slope is then compared with known values for specific tissue types. For example if the calculated slope is in the region of 0.30 to 0.35, then an artery is determined to be in the jaws. If the values are in the range of 0.15 to 0.20 then a section of bowel is determined to be in the jaws. In one technique, the R²value may be used as an indication of specificity. For example if R²is less than 0.90, for example, then an indication is given that a determination cannot be made. R²values in the range of 0.60 to 1.00 may be used to indicate that a determination of tissue type can be made and preferably tis threshold may be about 0.90.

In practice, sampling would be done on a time basis and both power and force would be sampled. These configurations are captured in the logic flow diagram of FIG. 47. The technique can be implemented in the generator software and/or the surgical instrument software.

It will be appreciated that using the averages for power and force at two positions can improve the accuracy of a two-point slope calculation. For accuracy it may be necessary to measure closure force (and moment) in addition to power.

The benefits of using the tissue coefficient of friction μ as a means to characterize tissue is discussed hereinbelow in connection with FIG. 48. Accordingly, the tissue coefficient of friction μ can be used to discriminate tissues and can be calculated using a technique for including steps to determine that a selection cannot be made.

FIG. 47 illustrates a logic flow diagram 2600 of one form of a method for dynamically changing the energy delivered to a surgical instrument based on a determination of tissue type being treated by the instrument. As described herein, the logic flow diagram 2600 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 2600 shown in FIG. 47, a characterization mode of the system is started by the processor 502 in which the type of tissue being treated by the surgical instrument is determined 2602 by the processor 502. The end effector 125 is positioned such that tissue is positioned within the clamp arm 145 and the ultrasonic blade 149 of the end effector 125. The clamp arm 145 is used to apply a force to the tissue. The force of the end effector 125 on the tissue is measured and compared 2604 by the processor 502 to a threshold minimum force. If the force applied to the tissue is below a minimum threshold force, the force applied to the tissue is increased 2606 and is again measured and compared 2604 by the processor 502 to the threshold minimum force.

Once the force on the tissue has reached the minimum threshold force, the processor 502 samples 2608 the force applied to the tissue and the power delivered to the end effector 125 by the generator 500 and saves 2612 the samples in a buffer. The processor 502 determines 2610 whether the buffer is full. Samples are saved 2612 in the buffer until the buffer is full, and then the processor 502 utilizes the samples to plot 2614 points on a graph of force versus power. This information is used by the processor 502 to calculate and store 2616 the slope and R²values in a database. See FIG. 46, for example, for a graphical representation of the linear sections of power versus force plots including the coefficient of determination R². Once stored in the database, the processor 502 compares the force values to a maximum force threshold and determines 2618 when the force reaches a maximum threshold value. Until the force reaches the maximum threshold value, the processor 502 continues along the NO branch and continues sampling 2608 the next samples of power and force. The processor 502 repeats until the force reaches the maximum threshold.

Once the force has reached the maximum threshold, the samples are no longer taken and stored and the processor 502 continues along the YES branch to select 2620 the slope with the highest R²value and to calculate the tissue coefficient of friction μ. Next, the processor 502 determines 2622 if the maximum slope value R²is greater than a predetermined threshold. If R²is less than the predetermined threshold, then the confidence level is low and the slope value cannot be used to calculate the tissue coefficient of friction μ and identify the tissue type and the processor 502 continues along the YES branch to display 2624 a message indicating that the tissue type has not been identified. In one aspect, the threshold may be selected in the range of 0.6 to 1.00 and may preferably be set to about 0.90, for example. In other aspects, the threshold may be selected using more sophisticated, statistical tests applied to determine the level confidence R². If R²is greater than or equal to the predetermined threshold, the calculated tissue coefficient of friction μ can be used to identify the tissue and the processor 502 continues along the NO branch where the processor 502 compares 2626 the calculated tissue coefficient of friction μ to a database 2628 of stored tissue coefficients of friction μ which the stored tissue coefficients of friction μ correspond to tissue types. The tissue type is selected 2630 and displayed and used to specify 2632 the power delivery profile for delivering energy from the generator 500 to the end effector 125 of the surgical instrument 108. Normal operation mode is entered 2634 such that the tissue type and related power delivery profile are used to control the end effector 125 for treating the tissue.

In one aspect, the tissue coefficient of friction μ and its rate may be employed to determine tissue type and power delivery profile. For example, It has been shown in preliminary work that μ is significantly different between porcine bowel, artery and chamois. Furthermore the μ values were initial flat but did change as time progressed presumably because of the temperature rise as heat was added. From these observations, μ can be used as a tissue differentiator and can be done at lower current to avoid rapid changes in μ when the purpose is to characterize the tissue. Also, another parameter of interest would be the rate of change of the tissue coefficient of friction μ for fixed conditions of {dot over (Q)}, ν, and N. It will be appreciated that {dot over (μ)} is not simply differentiating the equation

$μ = \frac{\dot{Q}}{v \cdot N}$

with respect time, because the change is due to changes in the tissue itself. For example the μ for chamois rapidly rises when heat is delivered compare with carotid arteries or bowel, because it is dry. The rate of change is likely dependent on the percentage of water content in the tissue. In one aspect, the present disclosure provides a technique to estimate both the tissue coefficient of friction μ and the rate of change of the tissue coefficient of friction μ and compare them with table of know values stored in a database, for example. The tissue selection can be based on the values closet to the estimated values. The power delivery profile could then be optimize for that tissue and delivered to the surgical instrument 108. Estimating the tissue coefficient of friction μ and the rate of change of the tissue coefficient of friction μ may be able to further differentiate tissue types. Another aspect of the present disclosure includes tracking the tissue coefficient of friction μ as the seal/transection progresses. Key changes in this parameter may signal a need to modify the power delivery profile.

FIG. 48 illustrates a logic flow diagram 2700 of another form of a method for dynamically changing the energy delivered to a surgical instrument 108 based on a determination of tissue type being treated by the surgical instrument 108. As described herein, the logic flow diagram 2700 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 2700 shown in FIG. 48 and the surgical system 100 of FIG. 1, the processor 502 initiates a power evaluation mode of the system to determine 2702 the power profile for the generator 500. The end effector 125 of the surgical instrument 108 is then engaged with the tissue to be treated and the end effector 125 of the surgical instrument 108 is activated 2704 with energy delivered from the generator 500. The tissue coefficient of friction μ and the processor 502 measures 2706 the rate of change (e.g., rate of rise) of the tissue coefficient of friction μ over a short period of time. The processor 502 compares 2708 the measured tissue coefficient of friction μ and the rate of change of the tissue coefficient of friction μ to values stored in a tissue information database 2714.

If the system is in learning mode, in which the tissue information database 2714 information regarding tissue type and tissue coefficients of friction μ are being updated, the tissue type can be visually identified 2710. The processor 502 updates 2712 the tissue information database 2714 of tissue coefficient of friction μ and tissue type information to increase the accuracy of the tissue information database 2714.

If the system is not in learning mode, then the processor 502 selects 2716 a power delivery profile based on the determined tissue and surgical instrument type 2718 being used. During the treatment of the tissue, the processor 502 continues to calculate and monitor 2720 the tissue coefficient of friction μ and the rate of change of the tissue coefficient of friction μ to allow the processor 502 to dynamically update the power delivery profile. If an error is found, the power delivery profile is modified 2724. The processor 502 then determines 2722 if the correct pattern of power and delivery profile is being used. If no error is found, the current power delivery profile continues 2726. Otherwise, the processor 502 modifies 2724 the power and delivery profile. The processor 502 continues the process of verification and correction of the power delivery profile during the entire surgical procedure to optimize the energy being delivered to the surgical instrument 108 based on the type of tissue being treated.

Techniques for Controlling a Generator Based on the Hydration Level of Tissue

In one aspect, the present disclosure provides a technique for controlling the power output from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). The power delivered to the end effector of the surgical instrument can be controlled based on the hydration level of the tissue to allow the energy profile from the generator to be dynamically changed based on the hydration level of the tissue being treated by the end effector of the surgical instrument. For conciseness and clarity of disclosure, the techniques for controlling the power output from a generator based on the hydration level of tissue will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

In order to determine the hydration level of the tissue being treated by the end effector 125 of the surgical instrument 108, the tissue coefficient of friction μ as described herein can be used. As explained above, a force measurement is taken using any of the methods described herein to calculate the tissue coefficient of friction μ to determine the hydration level of the tissue. The calculated tissue coefficient of friction μ is compared to a database of tissue coefficients of friction μ that correlate each tissue coefficient with a hydration level of the tissue. The calculated tissue coefficient of friction μ and its related tissue hydration level are used by the technique to control the energy being delivered from the generator 500 to the surgical instrument 108.

The hydration level of the tissue can be indicative of a variety of conditions within the tissue. During a coagulation cycle in which RF energy is being used to coagulate the tissue, a decrease in the tissue hydration level can indicate that the tissue is nearing the end of the coagulation cycle. In addition, the hydration level of the tissue can vary during the coagulation cycle such that the RF energy being delivered from the generator 500 can dynamically change during the coagulation cycle based on the calculated hydration levels during the cycle. For example, as a coagulation cycle progresses, the hydration level of the tissue will decrease such that the technique used to control the energy delivered from the generator 500 can decrease the power as the cycle progresses. Thus, the hydration level of the tissue can be an indicator of the progress through a coagulation cycle of the tissue by the end effector of the surgical instrument 108.

FIG. 49 illustrates a logic flow diagram 5900 of one form of a method for dynamically changing the energy delivered to a surgical instrument 108 based on a determination of the hydration level of tissue being treated by the surgical instrument 108. As described herein, the logic flow diagram 5900 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. With reference now to the logic flow diagram 5900 shown in FIG. 49, the processor 502 determines the hydration level of the tissue by measuring the tissue coefficient of friction μ as described herein. Initially, the end effector 125 of the surgical instrument 108 is closed on tissue and the end effector 125 is activated 5902 with energy from the generator 500. The processor 502 measures 5904 the tissue coefficient of friction μ, as described herein. The processor 502 compares 5906 the tissue coefficient of friction μ and the rate of change of the tissue coefficient of friction μ to values stored in a database to determine the hydration level of the tissue. The processor 502 selects 5908 a power delivery profile based on the hydration level of the tissue. The processor 502 monitors 5910 the tissue coefficient of friction μ and the rate of change of the tissue coefficient of friction it during treatment of the tissue to monitor the changes in the tissue hydration level. This allows the processor 502 to dynamically change 5912 the power delivery profile, such that power delivered from the generator 500 can dynamically change during tissue treatment.

Techniques for Switching Between RF and Ultrasonic Energy Based on Tissue Type

In another aspect, the present disclosure provides a technique for controlling energy delivered by a generator and/or a surgical instrument by dynamically switching between RF and ultrasonic energy. The technique includes controlling the power output from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). In one aspect, RF and ultrasonic energy can be dynamically switched based on the type of tissue being treated by an end effector of a surgical instrument and various characteristics of the tissue. The power delivered to the end effector of the surgical instrument can include an input that represents the tissue type to allow the energy profile from the generator to be dynamically changed between RF and ultrasonic energy during the procedure based on the type of tissue being effected by the end effector of the surgical instrument. For conciseness and clarity of disclosure, techniques for dynamically switching between different energy modalities, such as, for example RF energy and ultrasonic energy, will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

In order to determine the type of tissue being treated by the end effector 125 of the surgical instrument 108, a tissue coefficient of friction μ and/or the rate of change of the tissue coefficient of friction μ can be calculated and compared to a database of tissue coefficient of friction μ that correlates each tissue coefficient of friction μ with a tissue type, as explained above. The calculated tissue coefficient of friction μ and its related tissue type are used by a technique to control the type (RF or ultrasonic) and power level of energy being delivered from the generator 500 to the surgical instrument 108. Tissue types include, without limitation, tissue with a muscular structure, tissue with a vascular structure, tissue with a thin mesentery structure.

FIG. 50 illustrates a logic flow diagram 2900 of one aspect of a method of dynamically changing the between RF energy delivered from the ENERGY2/RETURN output of the generator 500 and ultrasonic energy delivered from the ENERGY1/RETURN output of the generator 500 to the surgical instrument 108 based on a determination of tissue type being treated by the surgical instrument 108. As described herein, the logic flow diagram 2900 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 2900 shown in FIG. 50, the processor 502 initiates a characterization mode of the generator 500 to determine 2902 the type of tissue being treated by the surgical instrument 108. The end effector 125 is positioned such that tissue is positioned between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125. The end effector 1255 applies a force to the tissue. The force applied to the tissue by the end effector 125 is measured and compared 2904 by the processor 502 to a threshold minimum force. If the processor 502 determines that the force applied to the tissue is below a minimum threshold force, the force applied to the tissue is increased 2906. Once the force on the tissue has reached the minimum threshold force, the processor 502 samples 2908 the force applied to the tissue and the power delivered to the end effector 125 by the generator 500 and stores the samples in a buffer.

The processor 502 determines 2901 if the buffer is full. If the buffer is not full, the processor 502 enters 2912 the most recent samples into the buffer. If the buffer is full, the processor 502 enters the most recent samples into the buffer and drops 2914 the first point (e.g., FIFO method for organizing and manipulating a data buffer). The processor 502 calculates and stores 2916 the slope and R²values and the force is tested to determine 2918 if the force applied to the tissue is greater than a maximum force threshold. If the force applied to the tissue is not greater than the maximum threshold, the processor 502 samples 2908 the force applied to the tissue and the power delivered to the end effector 125 by the generator 500 and saves the samples in a buffer. The processor 502 repeats until the force applied to the tissue is greater than the maximum threshold. The processor 502 selects the slope with the highest R²and calculates 2920 the tissue coefficient of friction μ. If the processor 502 determines 2922 that R²is less than a predetermined threshold, the processor 502 continues along the YES branch and the system displays 2924 that the tissue type was not identified. If R²is greaten than or equal to the threshold, the processor 502 continues along the NO branch and compares 2926 the calculated tissue coefficient of friction μ to values stored in a tissue information database 2928.

In one aspect, the threshold may be selected in the range of 0.6 to 1.00 and may preferably be set to about 0.90, for example. In other aspects, the threshold may be selected using more sophisticated, statistical tests applied to determine the level confidence R². In one aspect, the threshold may be selected between 0.6 to 1.00 and may preferably be set to about 0.90. In other aspects, the threshold may be selected using more sophisticated, statistical tests applied to determine the level confidence R². The processor 502 then selects 2930 and displays the tissue type and specifies 2932 the power delivery profile for delivering either ultrasonic energy (ENERGY1/RETURN) or RF energy (ENERGY2/RETURN) from the generator 500 to the end effector 125 of the surgical instrument 108. Normal operation mode is entered 2934 such that the tissue type and related power delivery profile are used to control the end effector for treating the tissue. Using the tissue type determined in accordance with the logic flow diagram 2900, the processor 502 can provide optimized energy delivery for that particular tissue. Tissue types that are determined to be more vascular or muscular would require more RF energy at the beginning of the cycle to provide more sealing energy either before the application of the ultrasonic energy or at a higher ratio of RF vs. ultrasonic energy. And tissue types that are less vascular would require less RF energy at the beginning of the cycle and the system would change the energy delivery toward a cutting profile using ultrasonic energy. Energy may be applied to the tissue until the tissue meets or exceeds a predetermined threshold impedance, which may be referred to as the termination impedance, and which is the tissue impedance that corresponds to the impedance of tissue when the tissue seal is complete.

Techniques for Dynamically Changing the Energy Delivered from a Generator Based on Aperture Defined by the End Effector and Energy Parameters

In one aspect, the present disclosure provides a technique for dynamically changing the energy delivered from a generator based on an aperture defined by an end effector. According to one aspect, the techniques for dynamically changing the energy delivered from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). For conciseness and clarity of disclosure, techniques for dynamically changing energy delivered from a generator based on an aperture defined by an end effector and energy parameters will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

The energy profile from the generator 500 can be dynamically changed during the procedure between RF and ultrasonic energy based on the aperture defined by the end effector 125 that is clamping on a tissue. This allows the generator 500 to switch from RF energy to ultrasonic energy based on the amount of clamping force exerted by the end effector 125 on the tissue being treated by the surgical instrument 108. The aperture defined by the clamp arm 145 is related to the creation of a proper coagulation seal, for example, when RF energy is being delivered from the generator 500 to the end effector 125 of the surgical instrument 108, such that RF energy should be used when there is a sufficient closure of the end effector 108 on the tissue. Thus, when the aperture defined by the end effector 108 is too large and there is not a sufficient clamping force exerted on the tissue for proper coagulation, only ultrasonic energy is delivered to the ultrasonic blade 149 of the end effector 125 through the ENERGY1/RETURN output of the generator 500.

For example, misleading information regarding various tissue measurements and/or characteristics can be transmitted to the generator 500 for use in the techniques for controlling the energy delivered depending on the aperture defined by the end effector 125. One such measurement that can be affected by the aperture defined by the end effector 125 is tissue impedance. Tissue impedance measured by an instrument as described herein will depend on several factors including the clamping force or pressure applied by the end effector 125 and the distance between electrodes in the case of RF energy or the clamp arm 145 aperture in the case of ultrasonic energy. Many techniques that determine the end of the coagulation cycle depend on the tissue impedance. A clamp arm 145 that is not fully closed on the ultrasonic blade 149 can lead to a tissue impedance determination that may not properly represent the condition of the tissue. An incorrect tissue impedance determination can lead to early termination of a coagulation cycle as the generator 500 may switch from RF to ultrasonic energy before a proper coagulation seal has been achieved. In one aspect, the tissue impedance may be determined by the processor 502 by dividing the output of the second voltage sensing circuit 524 coupled across the terminals labeled ENERGY2/RETURN by the output of the current sensing circuit 514 is disposed in series with the RETURN leg of the secondary side of the power transformer 508 as shown in FIG. 8. The outputs of the voltage sensing circuit 512 are provided to an isolation transformer and ADC 516 and the output of the current sensing circuit 514 is provided to another isolation transformer and ADC 518 to provide the voltage and current measurement is digital form to the processor 502.

The aperture defined by the end effector 125 can be determined using a variety of techniques. In various aspects, the aperture defined by the end effector 125 may be determined by detecting the pivot angle of the end effector 125. This can be accomplished using a potentiometer, a Hall effect sensor (in a manner described in connection with FIG. 19), an optical encoder, an optical IR sensor, an inductance sensor, or combinations thereof. In another aspect, the proximity of first and second components of an end effector is measured to determine the aperture defined by the end effector using, for example, the Hall effect sensor, an optical encoder, an optical IR sensor, an inductance sensor, or combinations thereof. In another aspect, the surgical instrument 108 may be configured to detect the aperture defined by the end effector 125 by measuring a change in a tissue impedance of the tissue interacting with the end effector. In another aspect, the surgical instrument 108 may be configured to detect the aperture defined by the end effector 125 by measuring a load applied by the end effector 125 on the tissue as ultrasonic energy is pulsed to the end effector 125. In another aspect, the surgical instrument 108 includes a switch or other mechanism for closing the end effector 125 that can detect the aperture defined by the end effector 125. In another aspect, the aperture defined by the end effector 125 may be determined based on linear displacement or stroke of the closure mechanism located either in the shaft 129 or the handle 109 of the surgical instrument 108. In another form, the aperture defined by the end effector 125 may be determined by the angular displacement of the trigger mechanism located in the handle 109 of the surgical instrument 108.

FIG. 51 is a logic flow diagram 3000 of one aspect of a technique for dynamically changing the energy delivered from a generator based on aperture defined by the end effector and energy parameters. As described herein, the logic flow diagram 3000 may be implemented in the generator 500, the surgical instrument 108, or a combination thereof. With reference now to the logic flow diagram 3000 shown in FIG. 51 and the surgical system 100 of FIG. 1 with the combination electrosurgical and ultrasonic multifunction surgical instrument 108 and the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), the aperture defined by the end effector 125 is determined as described herein. Initially, the end effector 125 of the surgical instrument 108 is closed on tissue, as shown in FIGS. 42A-B, 43A-B, and the end effector 125 is activated 3002 with energy from the generator 500, for example. The aperture defined by the end effector 125 is determined 3004 by the processor 502 using any of the techniques described herein. Once the aperture defined by the end effector 125 is determined 3004, the processor 502 signals the waveform generator 504 to delivery energy from the generator 500 and controls switching the output of the generator 500 between RF energy ENERGY2 and ultrasonic energy (ENERGY1/RETURN) based on the determined aperture defined by the end effector 125. Accordingly, the processor 502 selects 3006 a power delivery profile based on the aperture defined by the end effector 125. The processor 502 continues to monitor 3008 the aperture defined by the end effector 125 during the tissue treatment process and dynamically changes 3010 the energy delivered from the generator 500 based on the changing aperture defined by the end effector 125.

In another aspect, a technique for controlling the power output from the generator, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or the surgical instrument 108, such as the surgical instrument 108 (FIGS. 1-3) that is delivered to the end effector 125 of the surgical instrument 108 can include an input that includes energy parameters based on an aperture defined by the end effector 125 of the surgical instrument 108. The energy profile from the generator 500 can be dynamically changed during the procedure between RF and ultrasonic energy using the energy parameters based on the aperture defined by the end effector 125 that is clamping on tissue as shown in FIGS. 42A-B, 43A-B. This allows the generator 500 to switch from RF energy ENERGY2 to ultrasonic energy (ENERGY1/RETURN) based on the clamping force applied by the end effector 125 to the tissue being treated by the surgical instrument 108. As explained above, the aperture defined by the clamp arm 145 is related to creating a proper coagulation seal, for example, when RF energy is being delivered from the generator 500 to the end effector 125 of the surgical instrument 108, such that RF energy should be used when there is a sufficient closure of the end effector 125 on the tissue. Thus, when the aperture defined by the end effector 125 is too large and the clamping force applied to the tissue is insufficient for proper coagulation, only ultrasonic energy is delivered to the end effector 125 by the generator 500.

The aperture defined by the end effector 125 can be determined using any of the methods described herein. For example, the surgical instrument 108 can include an aperture defined by a sensor located in the end effector 125 that can be fed through a connector to the ASIC in the handle 109 of the surgical instrument 108. The surgical instrument 108 also can include a sensor in the handle 109 of the surgical instrument 108 that is configured to detect the aperture defined by the end effector 125.

Energy parameters are configured to be loaded into the generator 500, and can include a plurality of different parameters, including but not limited to voltage, current, power, and one or more techniques for use in treating tissue. These parameters can be related to the RF energy and ultrasonic energy that can be delivered from the generator 500. The energy parameters can include information such as maximum and/or minimum values to be used to control the energy delivered from the generator 500. The energy parameters can be stored in a variety of locations, including an EEPROM on the surgical instrument or some other non-volatile memory. In addition, there can be multiple sets of energy parameters. For example, there can be a first set of energy parameters that are used to optimize tissue transection, and a second set of energy parameters that are used to optimize tissue spot coagulation. It will be understood that there can be any number of set of energy parameters that correspond to various types of tissue treatments to allow the generator to switch between the various sets of energy parameters based on the necessary tissue treatments.

When the end effector 125 of the surgical instrument 108 is activated, one or more of the various techniques described herein are used to detect the aperture defined by the end effector 108. In one aspect, when the end effector 125 is closed around the tissue, the generator 500 can utilize the energy parameters for optimizing tissue transection. When the end effector 125 has a larger aperture and is not clamped on the tissue, the generator 500 can utilize the energy parameters for optimizing spot coagulation of the tissue.

FIG. 52 is a logic flow diagram 3200 of one aspect of a technique for dynamically changing the energy delivered from a generator based on aperture defined by the end effector and energy parameters. As described herein, the logic flow diagram 3200 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 3100 shown in FIG. 52, with the combination electrosurgical and ultrasonic instrument 108 and the generator 500, initially the aperture defined by the end effector 125 is determined by the processor 502 as described herein. The end effector 125 of the surgical instrument 108 is closed on tissue, as shown in FIGS. 42A-B, 43A-B, and the end effector 125 is activated with energy from the generator 500. The aperture defined by the end effector 125 is determined 3104 using any of the techniques described herein. The processor 502 signals the waveform generator 504 to deliver energy from the generator 500 to the end effector 125 and switch the generator 500 output between to switch between RF and ultrasonic energy based on the aperture defined by the end effector 125 by using one of the sets of energy parameters that was previously loaded into the generator 500. Accordingly, energy parameters are communicated 3106 to the generator 500 based on the previously determined 3104 aperture defined by the end effector 125. The processor 502 monitors 3108 the aperture defined by the end effector 125 during the tissue treatment process such that the energy delivered from the generator 500 can be dynamically communicated 3110 by the processor 502 during the tissue treatment process based on the changing aperture defined by the end effector 125. This allows the generator 500 to dynamically switch between the various sets of energy parameters based on the changing aperture defined by the end effector 125.

It will be understood that various combinations of information can be used to determine which set of energy parameters are to be used during tissue treatment. For example, the aperture defined by the end effector and calculated tissue impedance can be used to determine which set of energy parameters are needed to control the energy being delivered from the generator.

Techniques for Dynamic Sensing of Tissue

In one aspect, the present disclosure provides dynamic tissue sensing techniques. In one aspect, the dynamic tissue sensing techniques may be implemented with a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). For conciseness and clarity of disclosure, the dynamic tissue sensing techniques will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

Upon measuring the tissue thickness and the normal force on the ultrasonic blade as shown in and described in connection with FIGS. 42A-B, 43A-B, and measuring the tissue coefficient of friction μ, in one aspect a technique is provided that pulses to measure the tissue coefficient of friction μ at set time intervals and based on the measured coefficient μ over time, adjusts the power delivered by any one of and the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or the surgical instrument (FIGS. 1-3), in order to transect or “cut” tissue efficiently and with good hemostasis. In one aspect, a sensing technique is configured to monitor tissue friction and determine the tissue coefficient of friction μ, as described herein, throughout a cut and modulates energy delivered during the cut based on change in the tissue coefficient of friction μ over time.

FIG. 53 is a logic flow diagram 3200 of one aspect of a dynamic tissue sensing technique. As described herein, the logic flow diagram 3200 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 3200 shown in FIG. 53, case specific details for knowledge of tissue type are input 322 into the generator 500. The end effector 125 of the surgical instrument 108 is closed on the tissue, as shown in FIGS. 42A-B, 43A-B, and the tissue coefficient of friction μ is checked 3204 by the processor 502 and power is delivered 3206 to the tissue according to known normal force N, tissue coefficient of friction and tissue thickness as determined by processor 502 as described herein. The processor 502 compares 3208 the rate of change of μ/|μ| to known values of μ. In one aspect, a look-up table for predefined μ/Power Delivery Ratios may be utilized by the processor 502. The processor 502 adjusts 3210 the power delivered by the generator 500 higher or lower based on Δμ. When μ reaches 3212 a known or predetermined threshold, the processor 502 checks 3214 the clamp arm 145 of the end effector 125 for closure against the ultrasonic blade 149. In one aspect, this can be determined based on known normal force N and known production normal force N_pthat represents a closed end effector jaw. When the jaw closure is complete, the processor 502 control the delivery 3216 of short bursts of power to complete the tissue transection or cut until the cut is completed 3218.

Accordingly, by measuring the tissue coefficient of friction the processor 502 pulses to measure the tissue coefficient of friction μ at set time intervals and based on the measured coefficient μ over time, and adjusts the power delivered by generator 500 to the tissue in order to transect or “cut” tissue efficiently and with good hemostasis. In one aspect, the sensing technique monitors and periodically determines the tissue coefficient of friction as described herein, while making the cut and modulates the energy delivered by the generator during the cut based on change in the tissue coefficient of friction Δμ over time.

Techniques for Sealing or Sealing and Cutting Lame Vessels and Tissue-Bundles

In one aspect, the present disclosure provides a technique for sealing or sealing and cutting large vessels/tissue bundles by controlling the power delivered to an end effector from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). In accordance with the resent technique, the power delivered to an end effector of a surgical instrument can be varied based on the size of vessels and tissue bundles interacting with the end effector. For conciseness and clarity of disclosure, the techniques for sealing or sealing and cutting large vessels/tissue bundles will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

A technique for controlling the power output from a generator 500 that is delivered to the end effector 125 of a surgical instrument 108 can include an input that represents a state of coagulation of the tissue to allow the energy profile from the generator 500 to be dynamically changed during the tissue treatment process between RF and ultrasonic energy based on the state of coagulation of the tissue being treated by the end effector 125 of the surgical instrument 108 or the size of the vessels or tissue interacting with the end effector 108. This allows the processor 502 to control the generator 500 to switch from RF energy (ENERGY2/RETURN) when a tissue seal is complete to ultrasonic energy (ENERGY1/RETURN) to cut the tissue and complete a procedure. Also, this technique allows the generator 500 to switch to ultrasonic energy at the initial stages of treatment when either the vessel or tissue bundle is too large to seal with RF energy alone. Thus, ultrasonic energy is applied until the size of the vessel or tissue bundle is sufficiently reduced to enable the RF to complete a proper seal. It will be appreciated that the switch between a first form of energy and a second form of energy, and vice versa, can be done by first turning OFF the first form of energy and thereafter turning on the second form of energy. Alternatively, the switch between a first form of energy and a second form of energy, and vice versa, can be done by transitioning from the first form of energy to the second form of energy, and vice versa, such that for brief period both the first and second forms of energy are turned ON simultaneously while one form ramps up and the other ramps down. Thus, according to the latter approach, the RF and ultrasonic energies can be blended during the transition rather than “one then the other” approach.

In one aspect, the present disclosure provides techniques to improve the capability of the generator 500 to quickly and efficiently seal or seal and cut large vessels or large tissue bundles that present an initial extremely low impedance to the generator 500. These techniques shorten transaction times when sealing or sealing and cutting big tissue bundles that present low RF impedance to the generator 500. When RF energy is applied to tissue with real low impedance, due to electrical current capacity limitations (maximum output current capability) of the generator 500, the maximum power that can be delivered into tissue is limited, which results in very long transaction cycles. Note that the current limitation is not unique to the generators described herein and are applicable to other generators.

In one aspect, the state of coagulation of the tissue can be determined using a variety of techniques, In one aspect, the state of coagulation of the tissue is determined using a calculated tissue impedance and comparing it to a threshold to find the termination impedance, as explained above. The calculated tissue impedance, as described herein, is used by a technique to control the energy being delivered from the generator 500 to the surgical instrument 108.

In another aspect, the state of coagulation is determined using a “vector machine” or other techniques. In another aspect, the state of coagulation is determined using neural networks that are configured to take a plurality of factors into account. As discussed herein, a neural network refers to a series of techniques that attempt to identify underlying relationships in a set of data by using a process that mimics the way the human brain operates. Neural networks have the ability to adapt to changing input so that the network produces the best possible result without the need to redesign the output criteria. For example, the neural networks can take into account the tissue impedance as measured using the RF signal, the initial tissue impedance as measured using the RF signal, the energy that went into the transection, for example, in joules, the transection time, the initial aperture of the jaw, the current aperture of the jaw, and/or the rate of change of the tissue impedance. One example of a neural network 5500 for controlling a generator is described hereinbelow in connection with FIG. 82.

FIG. 54 is a logic flow diagram 3300 of one aspect of a process for sealing or sealing and cutting large vessels or large tissue bundles. As described herein, the logic flow diagram 3300 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 3300 shown in FIG. 54 and the surgical system 10 of FIG. 1, the state of coagulation of the tissue is determined as described herein. The generator 500 is configured to deliver RF energy (ENERGY2/RETURN) and ultrasonic energy (ENERGY1/RETURN) to switch between the RF and ultrasonic energy according to various techniques. The end effector 125 of the surgical instrument 108 is advanced and the tissue is clamped 3302 between the clamp arm 145 and the ultrasonic blade 149. The end effector 125 is activated with RF energy from the generator 500 and RF energy is delivered 3304 to the tissue to effect a seal employing a process such as a composite load curve (CLC) control process described in connection with the logic diagram 5400 shown FIG. 81. With reference back to FIG. 54, the processor 502 determines 3306 the state of coagulation to determine if a state of completion of coagulation of the tissue has been achieved, at which time the processor 502 signals the waveform generator 504 and amplifier 506 to switch from RF energy for coagulating tissue to ultrasonic energy for cutting tissue. If the desired tissue of coagulation or seal has not been achieved, the processor 502 continues along the NO branch and RF energy is continued to be delivered. When the proper state of coagulation has been reached, the processor 502 continues along the YES branch and the RF energy is switched 3308 to ultrasonic energy to cut the tissue. The tissue is released 3310 from the end effector 215 once the tissue cut is completed with the ultrasonic energy.

Also disclosed herein are techniques for dynamically changing the energy delivered from a generator based on end effector aperture. According to one aspect, a technique for controlling the power output from a generator, such as the generator 500 of FIG. 8, that is delivered to the end effector of a surgical instrument, such as surgical instrument 108 (FIGS. 1-3) can include an input that represents the aperture of the end effector 125 of the surgical instrument 108. The energy profile from the generator 500 can be dynamically changed during the procedure between RF and ultrasonic energy based on the size of the aperture defined by the end effector 125 clamping the tissue. This allows the generator 500 to switch from RF energy to ultrasonic energy based on the amount that the end effector 125 is clamping on the tissue being treated by the surgical instrument 108. The aperture of the clamp arm 145 is related to the creation of a proper coagulation seal, for example, when RF energy is delivered from the generator 500 to the end effector 125 of the surgical instrument 108, such that RF energy is used when there is sufficient closure of the end effector 125 on the tissue. Thus, if the aperture defined by the end effector is too large and there is insufficient clamp on the tissue for proper coagulation, only ultrasonic energy is delivered to the end effector 125.

For example, false information regarding various tissue measurements and/or characteristics can be transmitted to the generator 500 for controlling the energy delivered depending on the aperture defined by the end effector 125. One such measurement that can be affected by the aperture defined by the end effector 125 is tissue impedance. An incorrect tissue impedance determination can lead to early termination of a coagulation “sealing” cycle as the generator 500 may switch from RF to ultrasonic energy before a proper coagulation seal has been achieved.

The aperture defined by the end effector 125 can be determined using a variety of techniques. In one form, the aperture defined by the end effector 125 is determined by detecting the pivot angle of the end effector 125. This can be accomplished using a potentiometer, a Hall effect sensor, an optical encoder, an optical IR sensor, an inductance sensor, or a combination thereof. In another form, the proximity of first and second components of an end effector 125 is measured to determine the aperture defined by the end effector 125 using, for example, a Hall effect sensor, an optical IR, inductance sensor, or combination thereof. In another form, a surgical instrument 125 is configured to detect the aperture defined by the end effector 125 by measuring a change in a tissue impedance of the tissue interacting with the end effector 125. In another form, a surgical instrument is configured to detect the aperture defined by the end effector 125 by measuring a load applied by the end effector 125 on the tissue as ultrasonic energy is pulsed to the end effector 125. In another form, the surgical instrument includes a switch or other mechanism for closing the end effector 125 that can detect the aperture defined by the end effector 125. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

FIG. 55 is a logic flow diagram 3400 of one aspect of a process for sealing or sealing and cutting large vessels or large tissue bundles by dynamically changing energy being delivered from the generator 500 during the treatment of the tissue based on the changing aperture defined by the end effector. As described herein, the logic flow diagram 3400 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 3400 shown in FIG. 55, the processor 502 determines the aperture defined by the end effector 125 as described above. The processor 502 then determines the state of coagulation of the tissue as described herein. The generator 500 or the surgical instrument 108 may be configured to deliver RF energy (ENERGY2/RETURN) and ultrasonic energy (ENERGY1/RETURN) to switch between the RF and ultrasonic energy according to various techniques. The end effector 125 of the surgical instrument 108 is advanced and the tissue and the end effector 125 of the surgical instrument 108 is closed 3402 on tissue and the end effector 125 is activated with energy from the generator 500. The processor 502 determines 3404 the aperture defined by the end effector 125 using any of the techniques described above. The processor 502 signals the energy delivered from the generator 500 to the end effector 125 and controls when the generator 500 switches between RF and ultrasonic energy based on the aperture defined by the end effector 125. Accordingly, the processor 502 selects 3406 the generator 500 power delivery profile based on the aperture defined by the end effector 125. The processor 502 monitors 3408 the aperture defined by the end effector 125 during the tissue treatment process to dynamically change 3410 the energy delivered from the generator 500 during the tissue treatment process based on the changing aperture defined by the end effector 125.

In another aspect, a technique for controlling the power delivered from the generator 500 to the end effector 125 of the surgical instrument 108 can include an input that includes energy parameters based on an aperture of the end effector 125 of the surgical instrument 108. During the tissue treatment process, the processor 502 can dynamically change the energy output profile of the generator 500 between RF energy and ultrasonic energy using energy parameters based on the aperture defined by the end effector 125 clamping the tissue. This allows the generator 500 to switch from RF energy to ultrasonic energy based on how much clamping force the end effector is applying to the tissue during the treatment process. As explained above, the aperture of the clamp arm 145 is related to creating a proper coagulation seal. For example, RF energy should be delivered by the generator 500 to the end effector 125 only when there is sufficient closure of the end effector 125 on the tissue. Thus, when the aperture defined by the end effector 125 is too large and there is insufficient clamping force on the tissue for proper coagulation, only ultrasonic energy should be delivered to the end effector 125.

The aperture defined by the end effector 125 can be determined using any of the methods described above. For example, the surgical instrument 108 can include an aperture sensor in the end effector 125 that can be fed through a connector to the ASIC in the handle 109 of the surgical instrument 108. The surgical instrument 108 also can include a sensor in the handle 109 of the surgical instrument 108 that is configured to detect the aperture defined by the end effector 125.

Energy parameters are configured to be loaded into the generator 500, and can include a plurality of different parameters, including but not limited to voltage, current, power, and one or more techniques for use in treating tissue. These parameters can be related to the RF energy and ultrasonic energy that can be delivered from the generator 500. The energy parameters can include information such as maximum and/or minimum values to be used to control the energy delivered from the generator 500. The energy parameters can be stored in a variety of locations, including an EEPROM on the surgical instrument 108 or some other non-volatile memory. In addition, there can be multiple sets of energy parameters. For example, the processor 502 can use a first set of energy parameters to optimize tissue transection, and a second set of energy parameters to optimize tissue spot coagulation. It will be understood that there can be any number of set of energy parameters that correspond to various types of tissue treatments to allow the generator 500 to switch between the various sets of energy parameters based on the necessary tissue treatments.

When the end effector 125 of the surgical instrument 108 is activated, the processor 502 utilizes the various techniques described above to detect the aperture defined by the end effector 125. In one aspect, when the end effector 125 is closed around the tissue, the generator 500 can utilize the energy parameters for optimizing tissue transection. When the end effector 125 has a larger aperture and is not clamped on the tissue, the generator 500 can utilize the energy parameters for optimizing spot coagulation of the tissue.

FIG. 56 is a logic flow diagram 3500 of one aspect of a process for sealing or sealing and cutting large vessels or large tissue bundles by dynamically communicating energy parameters to the generator 500 during the tissue treatment process based on the changing aperture defined by the end effector 125 of the surgical instrument 108. As described herein, the logic flow diagram 3500 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. With reference now to the logic flow diagram 3500 shown in FIG. 56, the processor 502 determines the aperture defined by the end effector 125 as described above. The generator 500 is configured to deliver RF energy (ENERGY2/RETURN) and ultrasonic energy (ENERGY1/RETURN) and to switch between the RF and ultrasonic energy according to various techniques. The end effector 125 of the surgical instrument 108 is advanced, the end effector 125 of the surgical instrument 108 is closed 3502 on the tissue. and the end effector 125 is activated with energy from the generator 500. The processor 502 determines 3504 the aperture defined by the end effector 125 using any of the techniques described above. The processor 502 signals the energy delivered from the generator 500 and to switch between RF and ultrasonic energy based on the aperture defined by the end effector 125 based on sets of energy parameters previously loaded into the generator 500. Accordingly, energy parameters are communicated 3506 to the generator 500 based on the measured aperture defined by the end effector 125. The aperture defined by the end effector 125 is monitored 3508 during the tissue treatment process such that the energy delivered from the generator 500 can be dynamically changed during the tissue treatment process based on the changing aperture defined by the end effector 125. Accordingly, the processor 502 dynamically communicates 3510 energy parameters to the generator 500 based on the measured aperture defined by the end effector 125. This allows the generator 500 to dynamically switch between various sets of energy parameters based on the changing aperture defined by the end effector 125.

It will be understood that various combinations of information can be used to determine which set of energy parameters are to be used during the tissue treatment process. For example, the aperture defined by the end effector 125 and calculated tissue impedance can be used by the processor 502 to determine which set of energy parameters are needed to control the energy being delivered from the generator 500. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

In another aspect, a technique for controlling the power output from the generator 500 and delivered to the end effector 125 of the surgical instrument 108 can include an input that includes inputs related to the size of the tissue being treated by the end effector 125 of the surgical instrument 108. During the tissue treatment process, the processor 502 dynamically changes the energy delivered from the generator 500 between RF energy and ultrasonic energy to achieve dissection and coagulation of large vessels and large tissue bundles based on a determination of the effectiveness of the RF energy in coagulating the large vessels or large tissue bundles. A determination of the effectiveness of the RF energy in coagulating a tissue includes a calculation of tissue impedance, as explained above, of the large tissue interacting with the end effector 125, which is used to determine the type of energy delivered by the generator 500 to the end effector 125.

FIG. 57 is a logic flow diagram 3600 of a technique to seal or seal and cut vessels using RF and ultrasonic energy in conjunction with tissue impedance measurements and the aperture defined by the clamp arm measurements. As described herein, the logic flow diagram 3600 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 3600 shown in FIG. 57, the end effector 125 is advanced and the clamp arm 145 is closed 3602 on tissue located between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125. The end effector 125 is then activated with RF energy (ENERGY2/RETURN) from the generator 500 to form a seal. The processor 502 determines 3604 the tissue impedance and the aperture defined by the end effector 125 as described herein. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

The aperture defined by the end effector 125 and the processor 502 determines 3604 the tissue impedance using any of the techniques described herein. The processor 502 compares 3606 the tissue impedance values to stored threshold values and determines 3608 whether or not these values are greater than the threshold values. If either the tissue impedance or the aperture defined by the end effector 125 is less than the threshold value, the processor 502 continuous along the NO branch and RF energy (ENERGY2/RETURN) continues to be delivered from the generator 500 to the end effector 125. If the tissue impedance and the aperture defined by the end effector 125 are greater than the threshold value, the processor 502 continues along the YES branch and switches 3610 the to delivering ultrasonic energy (ENERGY1/RETURN) from the generator 500. This allows the large vessels and large tissue bundles to be reduced in size or shrunk with ultrasonic energy to a size that would allow the RF energy to form a more optimal seal.

The processor 502 determines 3612 the aperture defined by the end effector 125 using any of the techniques described herein. The processor 502 then compares 3614 these aperture values to stored threshold aperture values and determines whether or not these aperture values represent that the tissue has been shrunk by the ultrasonic energy to a size that would allow the RF energy to properly seal the tissue. If the processor 502 determines that tissue is too large for RF energy sealing, the processor 502 continues along the NO branch and ultrasonic energy continues to be delivered from the generator 500 to the end effector 125 to continue shrinking the tissue. If the processor 502 determines that the tissue is has been shrunk to an appropriate size suitable for sealing with RF energy, the processor 502 continues along the YES branch and switches 3616 the energy delivered from the generator 500 to RF energy. The processor 502 signals can optionally switch back 3618 to delivering ultrasonic energy upon determining that the RF energy has completed the tissue seal.

FIG. 58 is a logic flow diagram 3700 of one aspect of a process for sealing or sealing and cutting large vessels or large tissue bundles. As described herein, the logic flow diagram 3700 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 3700 shown in FIG. 58, tissue is initially grasped 3702 by the end effector 125 between the clamp arm 145 and the ultrasonic blade 149. RF energy (ENERGY2/RETURN) is delivered 3704 to the end effector 125. The processor 502 monitors 3706 the tissue impedance Z_Tand jaw aperture A_jfor a predetermined period T_o, which may be selected from a range of 0.5 to 2.0 seconds, and preferably about 1.5 seconds, for example. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

Until the predetermined period T_oelapses 3708, the processor 502 continues along the NO branch and the generator 500 continues to deliver RF energy and the processor 502 continues to monitor (measure) tissue impedance Z_Tand jaw aperture A_j. At the end of the time period T_o, if tissue impedance Z_Thas not increased to a value equal to or greater than a predetermined threshold and the jaw aperture is equal to or less than a predetermined threshold, the processor 502 proceeds along the YES branch and switches 3710 the generator 500 to ultrasonic energy mode. Ultrasonic energy is delivered 3712 to the tissue while the processor 502 monitors the tissue impedance Z_Tand jaw aperture A_juntil the tissue shrinks to a size that is suitable for sealing with RF energy. The processor 502 compares 3714 the jaw aperture A_jto a threshold jaw aperture and if it is less than or equal to the threshold the processor 502 continues along the YES branch assuming that the tissue is sized for sealing by RF energy. The processor 502 switches the generator 500 to RF energy mode and delivers 3716 RF energy to complete the seal while the processor 502 monitors the tissue impedance Z_Tto determine 3718 if the seal is complete. If the seal is complete and seal-only is desired, the processor 502 completes 3720 the operation. If the seal is complete and seal and cut is desired, the processor 502 switches the generator 500 to ultrasonic energy mode and delivers 3722 ultrasonic energy to cut the sealed tissue. Upon cutting the tissue, the processor 502 completes 3720 the operation.

FIG. 59 is a logic flow diagram 3800 of a technique to seal or seal and cut vessels using RF and ultrasonic energy in conjunction with tissue impedance measurements. As described herein, the logic flow diagram 3800 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 3800 shown in FIG. 59, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. The processor 502 signals the waveform generator 504 and amplifier 506 to deliver 3802 RF energy (ENERGY2/RETURN) to the end effector 125 of the surgical instrument 108 interacting with tissue to create a tissue seal using the RF energy. The processor 502 calculates 3804 a first tissue impedance Z_T1of the tissue interacting with the end effector 125 at the start of the period T_oof the delivery of the RF energy and then calculates 3806 a second tissue impedance Z_T2of the tissue interacting with the end effector after the RF energy is delivered for a predetermined period T₁. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

The processor 502 compares Z_T1to Z_T2. If Z_T2is less than or equal to Z_T1, after RF energy is delivered for a period of T₁, there may be a short circuit or the tissue impedance is too low for RF energy to deliver power to the tissue. Accordingly, the processor 502 proceeds along the YES branch and controls the waveform generator 504 and amplifier 506 to stop 3810 delivering RF energy to the end effector 125 and start delivering 3812 ultrasonic energy to the end effector 125 until Z_T2is greater than Z_T1. Once Z_T2exceeds Z_T1, the processor 502 continues along the NO branch and controls the waveform generator 504 and amplifier 506 to continue 3814 delivering RF energy to the end effector 125 until the tissue is sealed 3816. Once the tissue is sealed, the processor 502 continues along the YES branch and the controls the waveform generator 504 and amplifier 506 to stop delivering RF energy to the end effector 125 and to start delivering 3820 ultrasonic energy to cut the tissue. If the tissue is not sealed, the processor 502 continues along the NO branch and the generator 500 continues delivering RF energy to the end effector until the tissue seal is completed.

In another aspect, a technique for controlling the power output from the generator 500 delivered to the end effector 125 of the surgical instrument 108 can include an input that includes inputs related to the size of the tissue being treated by the end effector 125 of the surgical instrument 108. The energy delivered from the generator 500 can be dynamically changed during the procedure between RF and ultrasonic energy to achieve dissection and coagulation of a large tissue based on a determination of the effectiveness of the RF energy in coagulating the large tissue. A determination of the effectiveness of the RF energy in coagulating a tissue includes a calculation of tissue impedance, as explained above, of the large tissue interacting with the end effector 125, which is used to determine the type of energy being delivered by the generator 500 to the end effector 125.

FIG. 60 is a logic flow diagram 3900 of a technique to seal or seal and cut vessels using RF and ultrasonic energy in conjunction with tissue impedance measurements and the aperture defined by the clamp jaw measurements. As described herein, the logic flow diagram 3900 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 3900 shown in FIG. 60, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. The processor 502 signals the waveform generator 504 and amplifier 506 to deliver 3902 RF energy (ENERGY2/RETURN) to the end effector 125 of the surgical instrument 108 interacting with tissue to create a tissue seal using the RF energy. The processor 502 calculates 3904 a first tissue impedance Z_T1of the tissue interacting with the end effector 125 at the start of a period T_oof delivery of the RF energy and then calculates 3906 a second tissue impedance Z_T2of the tissue interacting with the end effector 125 after the RF energy is delivered for a predetermined period T₁and measures the aperture A_jdefined by the clamp arm 145. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

The processor 502 compares Z_T1to Z_T2. If Z_T2is less than or equal to Z_T1after RF energy is delivered for a period of T₁, the processor 502 determines that there may be a short circuit or extremely low the tissue impedance present at the end effector 125 that is too low for RF energy to deliver any power to the tissue. Accordingly, the processor 502 proceeds along the YES branch and the generator 500 and compares the measured aperture A_jdefined by the clamp arm 145 to a predetermined threshold aperture A_jodefined by the clamp arm 145, where the predetermined threshold aperture A_jod corresponds to a thick vessel or a thick tissue bundle located between the clamp arm 145 and the ultrasonic blade 149. If the measured aperture A_jdefined by the clamp arm 145 is less than or equal to the predetermined threshold aperture A_jo, the processor 502 continues along the NO branch and controls the waveform generator 504 and amplifier 506 to continue delivering RF energy to the end effector 125 until the tissue impedance Z_T2is less than the initial tissue impedance Z_T1. If the measured aperture A_jdefined by the clamp arm 145 is greater than the predetermined threshold aperture A_jo, the processor 502 continues along the YES branch and controls the generator to stop 3110 delivering RF energy to the end effector 125 and start delivering 3112 ultrasonic energy (ENERGY1/RETURN) to the end effector 125 until Z_T2is greater than Z_T1. Once Z_T2is greater than Z_T1the processor 502 continues along the NO branch and controls the waveform generator 504 and amplifier 506 to continue 3114 delivering RF energy to the end effector 125 until the tissue is sealed 3116. Once the tissue is sealed, the processor 502 continues along the YES branch and controls the waveform generator 504 and amplifier 506 to stop delivering RF energy and start delivering 3920 ultrasonic energy to the end effector 125 to cut the tissue. If the tissue is not sealed, the processor 502 continues along the NO branch and controls the waveform generator 504 and amplifier 506 to continue delivering RF energy to the end effector 125 until the tissue seal is complete.

Techniques for Switching Between RF and Ultrasonic Energy Based on the State of Coagulation of Tissue

In one aspect, the present disclosure provides a technique for switching between RF and ultrasonic energy based on the state of coagulation of tissue by controlling the power delivered to an end effector from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). In accordance with the present technique, the power delivered to an end effector of a surgical instrument can be switched between RF and ultrasonic based on the state of coagulation of tissue interacting with the end effector. For conciseness and clarity of disclosure, the techniques for switching between RF and ultrasonic energy based on the state of coagulation of tissue will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

To address these issues, in some aspects, a generator 500 capable of handling both ultrasonic and RF electrosurgical systems may include a completely nested neural network to identify whether the generator 500 is presented with a true short circuit vs. a low impedance tissue. In addition, in some aspects, to assist in the detection of short circuits, the neural network may be configured to track and store at least the following factors: a. Measured resistance/impedance; b. Drive current (RMS); c. Drive Voltage (RMS); and d. Moving average of measured impedance. In some aspects, the neural network will be thought to in order to be capable of discerning between a true short and low impedance tissue.

Furthermore, in some aspects, methods for detecting a short circuit may utilize the ultrasonic functionality to cut low impedance tissue and to identify a true short circuit. For example, instead of faulting, the generator 500 may send in an exploratory pulse to the ultrasonic transducer 120. The tissue properties initially assessed by the ultrasonic blade 149 touching a metal short would result in a higher output drive voltage and resulting impedance. This level of impedance may be measured to determine whether the material was actually metal versus low impedance tissue. If the processor 502 determines that metal is not present in the end effector 125, the generator 500 continues to deliver ultrasonic energy to the end effector 125 and cut through the load. Thus, if the impedance is too low for the application of RF energy to seal the tissue in a timely manner, ultrasonic energy could be applied cut through non-metal low impedances without difficulty.

FIG. 61 is a logic flow diagram 4000 of one aspect of a technique for distinguishing a short circuit from low impedance tissue while utilizing RF energy by measuring voltage properties of an exploratory ultrasonic pulse. As described herein, the logic flow diagram 4000 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to FIG. 61, the logic flow diagram 4000 provides a method for distinguishing a short circuit from low impedance tissue. With reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. In accordance with the method, the processor 502 signals the waveform generator 504 and amplifier 506 to transition 4002 from delivering RF energy (ENERGY2/RETURN) to delivering ultrasonic energy (ENERGY1/RETURN). The processor 502 then controls the waveform generator 504 and amplifier 506 to transmit 4004 an exploratory pulse to the ultrasonic transducer 120 to apply ultrasonic energy to the short circuit area in question. The processor 502 then measures 4006 the output drive voltage and drive current and determines the impedance. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514. At this juncture, the processor 502 determines 4008 whether the impedance is consistent with low impedance tissue. When the impedance is consistent with low impedance tissue, the processor 502 proceeds along the YES branch and controls the waveform generator 504 and amplifier 506 to continue 4010 delivering ultrasonic energy to cut through tissue. When the impedance is not consistent with low impedance tissue, the processor 502 proceeds along the NO branch and controls the waveform generator 504 and amplifier 506 to stop 4012 the application of ultrasonic energy.

Additionally, in some aspects, if a short is detected while in RF mode and delivering RF energy to the end effector 125, the processor 502 signals the waveform generator 504 and amplifier 506 to transmit an ultrasonic pulse to the ultrasonic transducer 120. A microphone and ultrasonic application can be configured to detect the sound of characteristic ultrasonic vibrations against metal, since it would be very apparent and instantly or easily recognizable. Using knowledge in acoustics and waveform engineering, the processor 502 can account for what frequencies are heard due to the ultrasonic blade 149 acting on metal and on other non-tissue materials.

FIG. 62 is a logic flow diagram 4100 of a technique for distinguishing a short circuit from low impedance tissue while delivering RF energy and measuring acoustic properties of an exploratory ultrasonic pulse, according to some aspects. As described herein, the logic flow diagram 4100 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. With reference now to FIG. 62, the logic flow diagram 4100 provides a method for distinguishing a short circuit from low impedance tissue. The tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. In accordance with the method, the processor 502 signals the waveform generator 504 and amplifier 506 to transition 4102 from delivering RF energy (ENERGY2/RETURN) to delivering ultrasonic energy (ENERGY1/RETURN). The processor 502 then controls the waveform generator 504 and amplifier 506 to transmit 4104 an exploratory pulse to the ultrasonic transducer 120 to apply ultrasonic energy to the short circuit area in question. The processor 502 measures 4106 the acoustic properties of the area in question based on applied ultrasonic vibrations. At this juncture, the processor 502 determines 4108 whether the acoustic properties are consistent with the low impedance tissue. When the processor 502 determines acoustic properties are consistent with low impedance tissue, the processor 502 proceeds along the YES branch and controls the waveform generator 504 and amplifier 506 to continue 3210 delivering ultrasonic energy to cut through tissue. When the processor 502 determines that the acoustic properties are consistent with low impedance tissue, the processor 502 proceeds along the NO branch and controls the waveform generator 504 and amplifier 506 to stop 4112 delivering ultrasonic energy.

In some aspects, a neural network, such as neural network 5500 for controlling a generator shown in FIG. 82, may be programmed to identify these properties in metal, tissues, and other non-tissue materials. The neural network also may be configured to transmit the exploratory pulse to the ultrasonic transducer. In addition, new developments or additional programs, including receiving feedback from the attempts to detect short circuits, may be incorporated back into the neural network to increase its situational awareness and effectively better learn how to detect a true short circuit. Wth confirmation of a short circuit both by RF and ultrasonic functionality, this can allow for less time spent getting repeat errors on RF and faster transection on low impedance tissue.

Also disclosed herein are techniques for combining RF energy and ultrasonic energy to seal tissue without cutting. In some aspects, the surgical system including the generator of the present disclosures may be configured to implement a method for sealing tissue at a surgical site without cutting, by using a combination of ultrasonic energy and RF energy. In some aspects, the method includes superimposing the ultrasonic drive signal together with a fixed low RF signal (e.g., ultrasonic at 55.5 KHz and RF at 330 KHz). For example, during a sealing procedure, the ultrasonic drive signal may be configured to dynamically change in order to: (1) track the resonance of the ultrasonic drive signal, and (2) provide the desired strength or amplitude of vibrations in order to achieve the desired tissue effect. The fixed low RF signal will be provided in order to measure the tissue impedance and modify the ultrasonic drive to achieve the desired seal without cutting.

The RF signal may be superimposed in several non-exhaustive ways. In one way, the RF drive signal may be superimpose on top of the ultrasonic drive signal in a continuous fashion. In another way, the ultrasonic drive signal may be time sliced in such way that periodically or aperiodically, e.g., every 250 mSec, the ultrasonic drive signal will cease and a short burst of the RF drive signal of, e.g., 50 mSec, will be driving the output at a sub-therapeutic level which will still be sufficient to measure tissue impedance. After this burst, the processor 502 will control the waveform generator 504 and the amplifier 506 to switch the output of the generator 500 back to delivering the ultrasonic drive signal. The overall control loop may be configured to monitor the RF tissue impedance and adjust the ultrasonic drive signal output to achieve a tissue seal without cutting the tissue.

FIG. 63 is a logic flow diagram 4200 of a technique for conducting a tissue sealing technique without cutting by using a combination of ultrasonic energy and RF energy, according to some aspects. As described herein, the logic flow diagram 4200 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to FIG. 63, the logic flow diagram 4200 provides an example iterative technique for cyclically combining RF energy (ENERGY2/RETURN) and ultrasonic energy (ENERGY1/RETURN) to seal tissue without cutting, according to some aspects. Tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. In accordance with the method, the processor 502 signals the waveform generator 504 to deliver 4202 an ultrasonic drive signal during a first interval of time to seal tissue at a surgical site. The processor 502 then controls the waveform generator 504 and the amplifier 506 to cease 4204 the ultrasonic drive signal after the first interval. The processor 502 then controls the waveform generator 504 and the amplifier 506 to deliver an RF drive signal at a sub-therapeutic amplitude during a second interval of time to measure tissue impedance. The processor 502 then controls the waveform generator 504 and the amplifier 506 to cease 4208 the RF drive signal after the second interval of time. The processor 502 then adjusts 4210 an ultrasonic drive signal based on the measured impedance from the RF drive signal. The processor 502 repeats 4212 the procedure until the surgical site is sealed.

The input to this control system to reduce/modify the ultrasonic drive signal and at eventually completely terminate the ultrasonic drive signal can utilize the following non-exhaustive methods: follow a power reduction and termination technique based on regular logic, fuzzy logic, vector machine, or neural network utilizing the following example: initial tissue impedance, initial jaws-aperture, current tissue impedance, rate of change of tissue impedance, energy driven into tissue, and transection time.

In some aspects, the surgical system may be configured to measure these terms through one or more sensors. Example methods for monitoring these terms and the ultrasonic functionality of the combination RF and ultrasonic surgical system may be based on methods described in U.S. Pat. No. 9,017,326, titled “Impedance Monitoring Apparatus, System, And Method For Ultrasonic Surgical Instruments,” which is hereby incorporated by reference in its entirety.

FIG. 64 is a logic flow diagram 4300 of a technique for conducting a tissue sealing technique without cutting by using a combination of ultrasonic energy and RF energy, according to some aspects. As described herein, the logic flow diagram 4300 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to FIG. 64, the logic flow diagram 4300 provides an example iterative technique for cyclically combining RF energy (ENERGY2/RETURN) and ultrasonic energy (ENERGY1/RETURN) to seal tissue without cutting, according to some aspects. Tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. In accordance with the method, the processor 502 signals the waveform generator 504 to deliver 4302 an ultrasonic drive signal to the tissue during a first interval of time T₁. The processor 502 then controls the waveform generator 504 and the amplifier 506 to cease 4304 the ultrasonic drive signal after the first interval T₁. The processor 502 then controls the waveform generator 504 and the amplifier 506 to deliver 4306 an RF drive signal at a sub-therapeutic amplitude during a second interval T₁of time to measure the tissue impedance. The processor 502 then controls the waveform generator 504 and the amplifier 506 to cease 4308 the RF drive signal after the second time interval T₂. The processor 502 then controls the waveform generator 504 and the amplifier 506 to iteratively adjust 4310 the ultrasonic drive signal based on the measured tissue impedance until the processor 502 determines that the tissue is sealed. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

Techniques for Improving Short Circuit Detection in a Combination Ultrasonic/RF Surgical Instrument

In one aspect, the present disclosure provides a technique for detecting extremely low impedances or actual short circuits in the end effector by controlling the power delivered to an end effector from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). In accordance with the present technique, the power delivered to an end effector of a surgical instrument can be varied based on whether a very low impedance or actual short circuit condition is present at the end effector. For conciseness and clarity of disclosure, the techniques for detecting extremely low impedances or actual short circuits in the end effector will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

Disclosed herein are techniques for detecting short circuits, including implementing detection methods in a neural network. In some aspects, the ultrasonic generator 500 of the present disclosures includes components configured to accurately and reliably detect short circuits. Particularly when performing surgeries on body tissue typical with use of the end effectors described herein, detecting a short circuit can be difficult for a number of reasons. For example, many times tissue presents itself as a short circuit, thereby fooling the detection software and at low signal magnitudes, which are inherent when driving signals with a short circuit, the measurement(s) error(s) is/are substantial and can result in making the wrong decision whether the generator is presented with a true short circuit. In addition, in some aspects of the generator described herein, low impedance tissue or metal shorts cause the generator to fault while in RF mode. In general, it may be difficult for the generator to distinguish between low impedance tissue and metal, where one may result in a true short circuit while the other is merely based on low impedance tissue.

FIG. 65 is logic flow diagram 4400 of a technique for detecting low impedance tissue or metal shorts that may cause false short circuits in RF mode. As described herein, the logic flow diagram 4400 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. With reference now to FIG. 65, the logic flow diagram 4400 provides an example technique for detecting low impedance tissue or metal shorts that may cause false short circuits in RF mode. Tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. In accordance with the method, if the processor 502 cannot distinguish low impedance tissue from metal located between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125, the processor 502 signals the waveform generator 504 to deliver ultrasonic energy (ENERGY1/RETURN) to cut low impedance tissue and to identify a true short circuit, such as metal to metal contact between the clamp arm 145 and the ultrasonic blade 149. In accordance with the method, the processor 502 signals the waveform generator 504 to deliver 4402 RF energy (ENERGY2/RETURN) with the end effector 125 to the target surgical site. The processor 502 then controls the waveform generator 504 and the amplifier 506 to transition 4404 from delivering RF energy to delivering ultrasonic energy to the end effector 125. The processor 502 signals the waveform generator 504 to transmit 4406 an exploratory ultrasonic pulse to the end effector 125 and then measures 4408 an ultrasonic property of the ultrasonic pulse upon transmission to the end effector 125.

Techniques for Delivering Pulsed RF and Ultrasonic Energy in a Combination Ultrasonic/RF Surgical Instrument

In one aspect, the present disclosure provides a technique for delivering RF and ultrasonic energy to an end effector of a surgical instrument by controlling the power delivered to an end effector from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). In accordance with the present technique, the power delivered to an end effector of a surgical instrument can be varied based on properties or parameters of tissue interacting with the end effector. For conciseness and clarity of disclosure, the techniques for delivering RF and ultrasonic energy to the end effector will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

FIGS. 66-75 illustrate aspects of timing diagrams of energy pulses for delivering different energy modalities to tissue. In one aspect the first energy modality is RF energy and the second energy modality is ultrasonic energy. There are many benefits to a surgical device that is capable of delivering both RF and ultrasonic energy. A surgical instrument capable of delivering both modalities provides stronger seals and can cut tissue without the need of a separate knife. The following disclosure provides multiple pulsing techniques than can be utilized for vessel sealing. These techniques employ tissue impedance measurements, current measurements, can seal only, and can seal and cut tissue. These techniques may be implemented using multiple generators, one generator configured to deliver RF energy and another generator configured to deliver ultrasonic energy. Alternatively, these techniques may be implemented with a single generator configured to deliver both RF and ultrasonic energy. In other aspects, these techniques may be implemented with a single generator that is configured to deliver RF and ultrasonic energy simultaneously through a single output port.

These techniques comprise pulsing between RF and ultrasonic energy modalities to create strong seals. Multiple configurations of pulsing are disclosed. The pulse sequence timing diagrams illustrated in FIGS. 57-63 and the logic flow diagrams shown in FIGS. 64-66 will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8. Tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108 and then the generator 500 delivers the pulse sequences discussed below.

FIG. 66 is a timing diagram of a seal only pulse sequence 4500 illustrating a basic configuration of pulsing RF and ultrasonic energy for “Seal Only” mode. The horizontal axis is time (t) in seconds that the energy is delivered or “pulsed.” The vertical axis is the current pulse amplitude in milliamps (mA) that the pulse is capable of sourcing. The ultrasonic energy pulses 4502 are shown in dashed line and the RF pulses 4504 are shown in solid line. As shown in FIG. 66, the generator 500 switches between the ultrasonic energy pulses 4502 and RF energy pulses 4504 at fixed time intervals. During a first half cycle, the pulse sequence starts with the RF energy pulse 4504 ON for about 1 mS at a current pulse of about 750 mA amplitude while the ultrasonic energy pulse 4502 is OFF for about 1 mS at 0 mA current amplitude. During the next half cycle, the RF energy pulse 4504 is OFF for about 1 mS at 0 mA current amplitude while ultrasonic energy pulse 4502 is ON for about 1 ms at a current pulse of about 350 mA amplitude. The cycle is repeated until a strong tissue seal is developed. It will be appreciated that the application of the sequence of ultrasonic energy pulses 4502 and RF energy pulses 4504 shown in the pulse sequence 4500 is suitable for effecting a tissue seal only. This configuration of pulse sequence can start either with an RF energy pulse 4504 or an ultrasonic energy pulse 4502. Ultimately energy delivery for a “Seal Only” mode would be stopped based on the tissue impedance measured on the RF pulses 4504.

In order to reduce the risk of cutting tissue with the ultrasonic energy pulses 4502, the number of ultrasonic energy pulses 4502 should be minimized. This configuration is shown in FIG. 67, which is a timing diagram of a seal only pulse sequence 4510 illustrating a basic configuration of pulsing RF and ultrasonic energy for “Seal Only” mode. As shown, the pulse sequence 4500 starts with an active RF energy pulse 4504. After two ultrasonic energy pulses 4502, or other predetermined limited number of ultrasonic energy pulses 4502, no more ultrasonic energy pulses 4502 are delivered after the last ultrasonic energy pulse 4502′ and the RF energy pulse 4504′ is delivered for an extended period to effect a seal only. To avoid cutting the tissue with the ultrasonic energy pulse 4504 the last RF energy pulse 4504′ remains ON at high amplitude while the ultrasonic energy pulse 4502 remains OFF.

It can be appreciated that the seal on the clamp arm 145 side may be wider and more complete than a seal on the ultrasonic blade 149 side. This may be caused by insufficient heating on the ultrasonic blade 149 side due to the higher thermal mass of the ultrasonic blade 149. In order to address this issue, the ultrasonic energy pulse 4502 could be left ON longer at the beginning to get the ultrasonic blade 149 up to the sealing temperature. FIG. 68 is a timing diagram of a seal only pulse sequence 4520 illustrating a basic configuration of pulsing RF and ultrasonic energy to preheat the ultrasonic blade 149. FIG. 68 is a timing diagram of a seal only pulse sequence 4520. As shown in FIG. 68, the first energy pulse delivered is an ultrasonic energy pulse 4502, which is left ON for an extended period sufficient to preheat the ultrasonic blade 149 prior to applying the RF energy pulses 4504. To avoid cutting the tissue with the ultrasonic energy pulse 4504 the last RF energy pulse 4504′ remains ON at high amplitude while the ultrasonic energy pulse 4502 remains OFF.

FIG. 69 is a timing diagram of a seal only pulse sequence 4530. One of the main benefits to having more than one pulse of ultrasonic energy 4502 is to maintain the ultrasonic blade 149 temperature. In order to maintain ultrasonic blade 149 temperature and reduce the risk of cutting tissue with the ultrasonic blade 149, the pulse sequence 4530 shown in FIG. 69 provides the first ultrasonic energy pulse 4502 at a high amplitude and then the subsequent ultrasonic energy pulses 4502′, 4502″ at lower amplitudes. To avoid cutting the tissue with the ultrasonic energy pulse 4504 the last RF energy pulse 4504′ remains ON at high amplitude while the ultrasonic energy pulse 4502 remains OFF.

The conditions for switching between the RF energy pulse 4504 and the ultrasonic energy pulse 4502 could be based on a fixed time or it could be based on tissue impedance. For example, when a “Seal Only” mode is desired, as shown in FIGS. 57-60, if a certain Impedance threshold is reached, the technique would not switch over to ultrasonic energy to minimize the risk of cutting through the tissue. The frequency slope could also be used as a trigger to switch from ultrasonic energy pulse 4502 delivery to RF energy pulse 4504 delivery.

If a “Seal and Cut” energy modality is desired, an ultrasonic energy pulse 4502 step could be added to the end of any of the techniques described in connection with FIGS. 57-60. This could occur once a certain impedance threshold is met. FIGS. 61 and 62 illustrate timing diagrams for seal and cut pulse sequences 4540, 4550 for issue seal and cut modes.

FIG. 70 is a timing diagram of a seal and cut pulse sequence 4540, which begins and ends with ultrasonic energy pulses 4502 delivered at the same amplitude during the sealing a cutting cycles. A first ultrasonic energy pulse 4502 is delivered at a predetermined amplitude and subsequent ultrasonic energy pulses 4502 are delivered at the same predetermined amplitude. The RF energy pulses 4504 are delivered until the tissue is sealed or until the tissue impedance is equal to or greater than a predetermined threshold. After the last delivered RF energy pulse 4504′ is turned OFF, the last ultrasonic energy pulse 4502′ is turned ON to cut tissue.

FIG. 71 is a timing diagram of a seal and cut pulse sequence 4550, which begins and ends with ultrasonic energy pulses 4502 delivered at variable amplitude during the sealing a cutting cycles. A first ultrasonic energy pulse 4502 is delivered at a predetermined amplitude and subsequent ultrasonic energy pulses 4502 are delivered at different amplitudes, and in one example as a stepped down amplitude. As shown, for example, a second ultrasonic energy pulse 4502′ is delivered at an amplitude lower than the first amplitude and a third ultrasonic energy pulse 4502″ is delivered at an amplitude that is lower the second predetermined amplitude. The RF energy pulses 4504 are delivered until the tissue is sealed or until the tissue impedance is equal to or greater than a predetermined threshold. After the last delivered RF energy pulse 4504′ is turned OFF, the last ultrasonic energy pulse 4502′″ is turned ON to cut tissue. The last ultrasonic energy pulse 4502′″ may be delivered at an amplitude that either the same as the first amplitude, may be different than previous amplitudes, or may be equal to one of the intermittent amplitudes.

For the seal and cut pulse sequences 4540, 4550, on thick tissue applications, the ultrasonic modality take approximately 250 ms to seek, meaning that low pulse widths result in a short amount of therapeutic time. In some aspects, pulse widths longer than 500 ms, for example, may provide certain benefits.

FIG. 72 is a timing diagram of a seal only pulse sequence 4560 where the ultrasonic energy pulse 4502 current is be set based on the impedance measured with the preceding RF energy pulse 4504. The right vertical axis is tissue impedance in Ohms. The ultrasonic energy pulse 4502 current could be set based on the impedance measured with the preceding RF energy pulse 4504. It would be preferred to have the ultrasonic energy pulse 4502 current high when the preceding RF impedance was low. As the RF impedance increases the ultrasonic energy pulse 4502 current of the next pulse would decrease. This would allow the technique to compensate for the amount of tissue positioned within the jaws of the end effector 125, where thick tissue/bundle applications would stay at lower impedance for a longer period of time and would require more energy/heat to seal. As shown in FIG. 72, based on the first two low tissue impedance 4506 measurements the ultrasonic energy pulse 4502 current amplitude remains the same. After the third tissue impedance 4506′ measurement, the amplitude of the ultrasonic energy pulse 4502′ current is reduced until the tissue impedance exceeds a predetermined threshold and the RF energy pulse 4504′ current remains ON while the ultrasonic energy pulse 4502 current amplitude remains at 0 mA.

In one aspect the first energy modality is RF energy and the second energy modality is ultrasonic energy. In one aspect, the process depicted by the logic flow diagram 4600 may be repeated until the tissue is sealed. As discussed in connection with FIGS. 57-60, in a seal only method, the ultrasonic energy modality may be turned off after a few predetermined number of cycles or based on tissue impedance measurements to avoid cutting the tissue while the RF energy modality is delivered to make a tissue seal. The ultrasonic and/or the RF energy modalities may be delivered at the same amplitude or at variable amplitudes. For example, the RF energy modality may be delivered at the same amplitude whereas the amplitude of the ultrasonic energy modality is stepped down. As discussed in connection with FIGS. 61 and 62, during a seal and cut cycle, the ultrasonic energy modality is delivered last to effect a tissue after the tissue is sealed. As previously discussed, during the sealing cycle, the amplitude of the ultrasonic energy modality may be the same or may be stepped down. A discussed in connection with FIG. 72, in a seal only method, the amplitude of the ultrasonic energy modality is adjusted base don the previous tissue impedance measurement utilizing the RF energy modality. In any of the seal or seal and cut methods discussed above, the ultrasonic energy may be delivered first to preheat the ultrasonic blade 149 because of the higher thermal mass of the ultrasonic blade 149 with respect to the thermal mass of the clamp arm 145.

FIG. 73 is a logic flow diagram 4600 of a technique for delivering pulses of different energy modalities to tissue. As described herein, the logic flow diagram 4600 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 4600 of FIG. 73, initially, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108 and then the processor 502 signals the waveform generator 504 to deliver the pulse sequences discussed below. In accordance with the method, the processor 502 activates 4602 a first energy modality of the surgical instrument 108. After a first period, the processor 502 deactivates 4604 the first energy modality and activates 4606 a second energy modality for a second period. The second energy modality is activated 4606 independent of the first energy modality. After the second period expires, the processor 502 deactivates 4608 the second energy modality.

FIG. 74 is a logic flow diagram 4700 of a technique for delivering pulses of different energy modalities to tissue. As described herein, the logic flow diagram 4700 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 4700 of FIG. 74, initially, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108 and then the processor 502 signals the waveform generator 504 to deliver the pulse sequences discussed herein. In accordance with the method, the processor 502 activates 4702 an RF energy modality of the surgical instrument 108 to drive RF energy through electrodes located in the clamp arm 145 of the end effector 125. The processor 502 deactivates 4704 the RF energy modality upon detecting a first predetermined tissue impedance Z_T1measured at the end effector 125 of the surgical instrument 108. The generator 500 then activates 4706 an ultrasonic energy modality of the surgical instrument 108 to drive the ultrasonic blade 149. The processor 502 deactivates 4708 the ultrasonic energy modality upon detecting a second predetermined tissue impedance Z_T2at the end effector 125 of the surgical instrument 108. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

FIG. 75 is a logic flow diagram 4000 of a technique for delivering pulses of different energy modalities to tissue. As described herein, the logic flow diagram 4800 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. With reference now to the logic flow diagram 4800 of FIG. 75, initially, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108 and then the processor 502 signals the waveform generator 504 to deliver the pulse sequences discussed herein. In accordance with the method, the processor 502 activates 4802 an RF energy modality of the surgical instrument 108 to drive RF energy through electrodes located in the clamp arm 145 of the end effector 125. The processor 502 deactivates 4804 the RF energy modality upon the expiration of a first predetermined period T₁. The processor 502 activates 4806 an ultrasonic energy modality of the surgical instrument 108 to drive the ultrasonic blade 149. The processor 502 deactivates 4808 the ultrasonic energy modality upon the expiration of a second predetermined period T₂.

Techniques for Simultaneously Delivering Blasts of Ultrasonic and RF Energy in a Combination Ultrasonic/RF Surgical Instrument

In one aspect, the present disclosure provides a technique for delivering a combination simultaneous blast of RF and ultrasonic energy to an end effector of a surgical instrument by controlling the power delivered to an end effector from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or a surgical instrument, such as the surgical instrument 108 (FIGS. 1-3). In accordance with the present technique, a combination simultaneous blast of RF and ultrasonic energy can be delivered to an end effector of a surgical instrument can be varied based on properties or parameters of tissue interacting with the end effector. For conciseness and clarity of disclosure, the techniques for delivering a combination simultaneous blast of RF and ultrasonic energy to the end effector will be described with reference to the multifunction surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

FIGS. 76-80 illustrate aspects of delivering multiple energy modalities to tissue. In one aspect the first energy modality is RF energy and the second energy modality is ultrasonic energy. There are many benefits to a surgical device that is capable of delivering both RF and ultrasonic energy. A surgical instrument capable of delivering both modalities provides stronger seals and can cut tissue without the need of a separate knife. The following disclosure provides multiple pulsing techniques than can be utilized for vessel sealing. These techniques employ tissue impedance measurements, current measurements, can seal only, and can seal and cut tissue.

The various aspects described below provides simultaneous activation of multiple energy modalities such as RF and ultrasonic energy modalities. Initially both RF and ultrasonic modalities are delivered to tissue. The RF energy modality is utilized for the first portion of the seal. After a set amount of time T₁, based off the RF impedance Z_Tdetected, the ultrasonic modality is terminated. A short blast of ultrasonic energy at the beginning of the seal cycle provides benefits to sealing, as it aids in heating the ultrasonic blade and subsequently the tissue surface in contact with the blade while the electrode is simultaneously heating the tissue surface in contact with the RF electrodes.

These techniques may be implemented using multiple generators, one generator configured to deliver RF energy and another generator configured to deliver ultrasonic energy. Alternatively, these techniques may be implemented with a single generator configured to deliver both RF and ultrasonic energy. In other aspects, these techniques may be implemented with a single generator that is configured to deliver RF and ultrasonic energy simultaneously through a single output port. These techniques comprise simultaneous pulsing of RF and ultrasonic energy modalities to create strong seals. Multiple configurations of pulsing are disclosed. Multiple configurations of the simultaneous techniques are disclosed.

FIG. 76 is a logic flow diagram 4900 of one aspect of a process of applying simultaneous activation of different energy modalities to tissue. As described herein, the logic flow diagram 4900 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 4900 of FIG. 76, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108 and then the generator 500 delivers the simultaneous energy modalities. The total seal time 4902 is shown along a vertical axis.

Once tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108, the processor 502 signals the waveform generator 504 to deliver the pulse sequences discussed herein. In accordance with the logic flow diagram 4900 of FIG. 76, the RF energy modality application process 4904 is shown on the left and ultrasonic energy modality application process 4916 is shown on the right. The processor 502 activates 4996 the RF energy modality at the same time that the ultrasonic energy modality is activated 4918. Once the RF energy modality is activated 4906, the processor 502 signals the waveform generator 504 to deliver 4908 RF energy in accordance with a variety of RF sealing techniques, including RF sealing techniques described herein in connection with the logic diagram 5400 shown FIG. 81. Turning back to FIG. 76, the processor 502 activates 4920 the ultrasonic energy modality at a constant power level. During the simultaneous application of the RF and ultrasonic energy modalities, the processor 502 measures the RF tissue impedance Z_tissueand when the RF tissue impedance Z_tissuemeets ore exceeds an ultrasonic termination impedance Z_US-term(see FIG. 77) it is provided 4910 as feedback to the processor 502 to signal 4922 the waveform generator 504 and amplifier 506 to terminate 4924 delivery of ultrasonic energy to the end effector 125. Meantime, the RF energy modality is continuously delivered until an RF termination impedance Z_RF-termis reached 4912 at which point the processor 502 signals the waveform generator 504 to terminate 4914 delivery of RF energy. The short blast of the ultrasonic energy at the beginning of the seal cycle provides benefits to sealing, as it aids in heating the ultrasonic blade 149 and subsequently the tissue surface in contact with the blade 149 while the electrode in the clamp arm 145 is simultaneously heating the tissue surface in contact with the electrode. As previously discussed, the tissue impedance is determined by the processor 502 by dividing the voltage applied to the end effector 125 by the current delivered to the end effector 125. For example, the processor 502 can determine the tissue impedance by dividing the voltage sensed by the second voltage sensing circuit 524 by the current sensed by the current sensing circuit 514.

FIG. 77 is a graphical representation of RF Impedance versus Time in connection with the logic flow diagram 4900 of FIG. 76 to illustrate the ultrasonic termination impedance. The horizontal axis is time (ms) and the vertical axis is RF impedance (Ohms). The tissue impedance Z_tissuecurve 5002 is monitored during the sealing period utilizing the RF energy. When the tissue impedance Z_tissuereaches the ultrasonic termination impedance Z_US-term5004 the ultrasonic power is terminated and when the tissue impedance Z_tissuereaches the RF termination impedance Z_RF-term5006 the RF energy is terminated.

FIG. 78 illustrates an example of the quality of a seal 5102 made in a vessel 5100 using the simultaneous activation of RF and ultrasonic energy modalities as described in connection with FIGS. 67 and 68. The main advantage of simultaneous activation of RF and ultrasonic energy modalities is that the ultrasonic energy heats up the ultrasonic blade 149 and helps to create a reduction in the difference in thermal mass between the ultrasonic blade 149 and the electrode in the clamp arm 145. During a non-simultaneous activation seal cycle utilizing both RF and ultrasonic modalities, a challenge is posed to create a strong seal with varying thermal masses on either side of the end effector 125 jaw.

FIG. 79 is a graphical representation 5200 of seal burst pressure of carotid bundles versus an RF only seal and a simultaneous RF/ultrasonic seal as described in connection with FIGS. 67-69. The horizontal axis is an RF seal only boxplot 5202 and a simultaneous RF/ultrasonic boxplot 5204. The boxplots 5202, 5204 demonstrate the tissue effect advantages described ion connection with the simultaneous RF/ultrasonic energy modality activation process 4100 shown in connection with FIG. 76 where simultaneously heating the ultrasonic blade and electrode provides a high quality 5102 in a vessel as shown in FIG. 78.

FIG. 80 is a logic flow diagram 5300 of a process of simultaneous activation of RF and ultrasonic energy modalities. As described herein, the logic flow diagram 5300 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 5300 of FIG. 80, initially, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108 and then the processor 502 signals the waveform generator 504 to deliver the pulse sequences discussed herein. In accordance with the logic flow diagram 5300, the processor 502 simultaneously activates 5302 an RF energy modality and an ultrasonic energy modality of the surgical instrument 108. The processor 502 monitors 5304 the tissue impedance using RF energy modality. When the tissue impedance is equal to or greater than a first termination impedance, the generator 500 deactivates 5306 the ultrasonic energy modality of the surgical instrument 108. The RF energy modality is delivered until the tissue impedance is equal to or greater than a second termination impedance, at which time the processor 502 deactivates 5308 the RF energy modality of the surgical instrument 108 and the tissue seal is complete.

In some aspects utilizing a pulsed drive signal, a generator, such as, for example, one of generators 102, 200, 300, 400, 500 described in connection with FIGS. 1-3 and 5-8, may apply one or more composite load curves to the drive signal, and ultimately to the tissue. Composite load curves may define a level of power to be delivered to the tissue as a function of a measured tissue property or properties (e.g., impedance). Composite load curves may, additionally, define pulse characteristics, such as pulse width, in terms of the measured tissue properties.

FIG. 81 illustrates one aspect of a logic diagram 5400 for the selection and application of composite load curves by any one of generators 102, 200, 300, 400, 500. It will be appreciated that the logic diagram 5400 may be implemented with any suitable type of generator or surgical device. According to various aspects, the logic diagram 5400 may be implemented utilizing an electrosurgical instrument, such as the electrosurgical instrument 106 described above with respect to FIG. 1, an ultrasonic surgical instrument 104 described above with respect to FIG. 1, or a combination surgical instrument 108 described above with respect to FIGS. 1-3.

Referring back to FIG. 81, a control process 5402 may be executed, for example by a digital device of the generator 102 to select and apply composite load curves 5406, 5408, 5410, 5412. The control process 5402 may receive a time input from a clock 5404 and may also receive loop input 5424 from sensors 5418. The loop input 5424 may represent properties or characteristics of the tissue that may be utilized in the control process 5402 to select and/or apply a composite load curve. Examples of such characteristics may comprise, for example, current, voltage, temperature, reflectivity, force delivered to the tissue, resonant frequency, rate of change of resonant frequency, etc. The sensors 5418 may be dedicated sensors (e.g., thermometers, pressure sensors, etc.) or may be software implemented sensors for deriving tissue characteristics based on other system values (e.g., for observing and/or calculating voltage, current, tissue temperature, etc., based on the drive signal). The control process 5402 may select one of the composite load curves 5406, 5408, 5410, 5412 to apply, for example based on the loop input 5424 and/or the time input from the clock 5404. Although four composite load curves are shown, it will be appreciated that any suitable number of composite load curves may be used.

The control process 5402 may apply a selected composite load curve in any suitable manner. For example, the control process 5402 may use the selected composite load curve to calculate a power level and one or more pulse characteristics based on tissue impedance (e.g., currently measured tissue impedance may be a part of, or may be derived from, the loop input) or resonant frequency characteristics of a ultrasonic surgical instrument 104. Examples of pulse characteristics that may be determined based on tissue impedance according to a composite load curve may include pulse width, ramp time, and off time.

At set point 5414, the derived power and pulse characteristics may be delivered to the drive signal. In various aspects, a feedback loop 5422 may be implemented to allow for more accurate modulation of the drive signal. At the output of the set point 5414, the drive signal may be provided to an amplifier 5416, which may provide suitable amplification. The amplified drive signal may be provided to a load 5420 (e.g., via sensors 5418). The load 5420 may comprise the tissue, the surgical instrument 104, 106, 108, and/or any cable electrically coupling a generator with the surgical instrument 104, 106, 108 (e.g., cables 142, 144, 146).

In various aspects the state of coagulation may be determined using neural networks that are configured to take a plurality of factors into account. In some aspects, a generator may be configured to drive both ultrasonic and electrosurgical systems and include a nested neural network to identify whether the generator is presented with a true short circuit vs. a low impedance tissue. In addition, in some aspects, to assist in the detection of short circuits, the neural network may be configured to track and store at least the following factors: a. Measured resistance/impedance; b. Drive current (RMS); c. Drive Voltage (RMS); and d. Moving average of measured impedance. In some aspects, the neural network will be thought to in order to be capable of discerning between a true short and low impedance tissue. In other aspects, a neural network may be programmed to identify properties in metal, tissues, and other non-tissue elements. The neural network also may be configured to transmit the exploratory pulse to the transducer. In addition, new developments or additional programs, including receiving feedback from the attempts to detect short circuits, may be incorporated back into the neural network to increase its situational awareness and effectively better learn how to detect a true short circuit. Wth confirmation of a short circuit both by RF and ultrasonic functionality, this can allow for less time spent getting repeat errors on RF and faster transection on low impedance tissue. An example of a neural network is described in connection with FIG. 82.

FIG. 82 illustrates one aspect of a neural network 5500 for controlling a generator. FIG. 73 illustrates one aspect of an artificial neural network 5500 for generating an estimated temperature T_estresulting from an application of ultrasonic energy using an ultrasonic surgical instrument, such as the ultrasonic surgical instruments 104, 106, 108 (FIGS. 1-3). In certain aspects, the neural network 5500 may be implemented in the processor and/or the programmable logic device of the generator 102 (FIG. 1). The neural network 5500 may comprise an input layer 5502, one or more nodes 5504 defining a hidden layer 5506, and one or more nodes 5508 defining an output layer 5510. For the sake of clarity, only one hidden layer 5506 is shown. In certain aspects, the neural network 5500 may comprise one or more additional hidden layers in a cascaded arrangement, with each additional hidden layer having a number of nodes 5504 that may be equal to or different from the number of nodes 5504 in the hidden layer 5506.

Each node 5504, 5508 in the layers 5502, 5510 may include one or more weight values w 5512, a bias value b 5514, and a transform function f 5516. In FIG. 82, the use of different subscripts for these values and functions is intended to illustrate that each of these values and functions may be different from the other values and functions. The input layer 5502 comprises one or more input variables p 5518, with each node 5504 of the hidden layer 5506 receiving as input at least one of the input variables p 5518. As shown in FIG. 82, for example, each node 5504 may receive all of the input variables p 5518. In other aspects, less than all of the input variables p 5518 may be received by a node 5504. Each input variable p 5518 received by a particular node 5504 is weighted by a corresponding weight value w 5512, then added to any other similarly weighted input variables p 5518, and to the bias value b 5512. The transform function f 5516 of the node 5504 is then applied to the resulting sum to generate the node's output. In FIG. 82, for example, the output of node 5504-1 may be given as f₁(n₁), where n₁=(w_1,1·p₁+w_1,2·p₂+ . . . +w_1,j·p_ij+b₁.

A particular node 5508 of the output layer 5510 may receive an output from one or more of the nodes 5504 of the hidden layer 5506 (e.g., each node 5508 receives outputs f₁(⋅), f₂(⋅), . . . , f_i(⋅) from respective nodes 5504-1, 5504-2, . . . , 5504-i in FIG. 82), with each received output being weighted by a corresponding weight value w 5512 and subsequently added to any other similarly weighted received outputs, and to a bias value b 5514. The transform function f 5516 of the node 5508 is then applied to the resulting sum to generate the node's output, which corresponds to an output of the neural network 5500 (e.g., the estimated temperature T_estin the aspect of FIG. 82). Although the aspect of the neural network 5500 in FIG. 82 comprises only one node 5508 in the output layer 5510, in other aspects the neural network 5500 may comprise more than one output, in which case the output layer 5510 may comprise multiple nodes 5508.

In certain aspects, the transform function f 5516 of a node 5504, 5508 may be a nonlinear transfer function. In one aspect, for example, one or more of the transform functions f 5516 may be a sigmoid function. In other aspects, the transform functions f 5516 may include a tangent sigmoid, a hyperbolic tangent sigmoid, a logarithmic sigmoid, a linear transfer function, a saturated linear transfer function, a radial basis transfer function, or some other type of transfer function. The transform function f 5516 of a particular node 5504, 5508 may be the same as, or different from, a transform function f 5516 in another node 5504, 5508.

In certain aspects, the input variables p 5518 received by the nodes 5504 of the hidden layer 5506 may represent, for example, signals and/or other quantities or conditions known or believed to have an effect on the temperature or heating resulting from an application of ultrasonic energy. Such variables may comprise, for example, one or more of: drive voltage output by the generator 102, drive current output by the generator 102, drive frequency of the generator output 102, drive power output by the generator 102, drive energy output by the generator 102, impedance of the ultrasonic transducer 120, and time duration over which ultrasonic energy is delivered. Additionally, one or more of the input variables p 5518 may be unrelated to outputs of the generator 102 and may comprise, for example, characteristics of the end effector 122, 125 (e.g., blade tip size, geometry, and/or material) and a particular type of tissue targeted by the ultrasonic energy.

The neural network 5500 may be trained (e.g., by changing or varying the weight values w 5512, the bias values b 5514, and the transform functions f 5516) such that its output (e.g., estimated temperature T_estin the aspect of FIG. 82) suitably approximates a measured dependency of the output for known values of the input variables p 5518. Training may be performed, for example, by supplying known sets of input variables p 5518, comparing output of the neural network 5500 to measured outputs corresponding to the known sets of input variables p 5518, and modifying the weight values w 5512, the bias values b 5514, and/or the transform functions f 5516 until the error between the outputs of the neural network 5500 and the corresponding measured outputs is below a predetermined error level. For example, the neural network 5500 may be trained until the mean square error is below a predetermined error threshold. In certain aspects, aspects of the training process may be implemented by the neural network 5500 (e.g., by propagating errors back through the network 5500 to adaptively adjust the weight values w 5512 and/or the bias values b 5514).

FIG. 83 illustrates an example graph of a curve 5600 of impedance (|Z|) versus time (t) showing the termination impedance at which a proper tissue seal is achieved using RF energy. The curve 5600 provides time in seconds along the horizontal axis and impedance in Ohms along the vertical axis. The impedance versus time curve 5600 is described in three sections 5602, 5604, and 5606. Section one 5602 represents the initial impedance of the tissue from a time 5608 just after energy is applied to the tissue to a time 5610 when the tissue impedance drops to a minimum value as shown in section two 5604. Section one 5602 of the curve 5600 decreases for an initial impedance |Z| value until it stabilizes to a minimum impedance in the second section 5604 of the curve 5600. After energy is delivered to the end effector and applied to the tissue for a certain period (e.g., 4.5 seconds as shown) the moisture content of the tissue evaporates causing the tissue to dry out and the impedance of the tissue to rise in section three 5606 of the curve until the termination impedance |Z_T| is reached, at which point in time, T_o, the energy to the end effector is shut off. The portion of the curve 5600 in section three 5606 (shown in dashed line) represents the increase in tissue impedance |Z| that would result if the energy were be applied continuously instead of being shut off at the termination impedance |Z_T| point.

Once the termination impedance |Z_T| has been reached, the generator may switch from delivering RF energy to ultrasonic energy. The termination impedance |Z_T| can be a fixed value based on the instrument's electrode and compression properties or it can be a variable that depends on factors measured during the grasping and coagulation cycle such as: amount of tissue grasped, initial impedance and minimum impedance. It also can be a variable dependent on various slopes of impedance, energy delivery at various points in the coagulation cycle such as minimum impedance, and/or inflection points, and combinations thereof.

Tissue impedance as a function of time is a continuous differentiable function of time. It can be shown, through system identification techniques and system parameter optimization that a model exists which can model the relationship of the power input to tissue. The form of the model is:

$\begin{matrix} \ddot{Z} = {\begin{matrix} kZ + b_{1} \dot{Z} + c_{1} (W - c_{2}) if \dot{Z} < 0 \\ kZ + b_{2} \dot{Z} + c_{1} (W - c_{2}) if \dot{Z} \geq 0 \end{matrix} & Equation 3 \end{matrix}$

In Equation 3, Z is the impedance measured (estimated from known current and voltage) across the tissue, Ż and {umlaut over (Z)} are the first and second derivatives of the tissue impedance. k, b₁, b₂c₁, and c₂are the parameters to be estimated. W is the work applied to the tissue in Joules. Using a combination of downhill simplex and global based optimization techniques, such as, for example evolutionary processes, particle swarm optimization, and simulated annealing. The parameters can be estimated in quasi-real time, which are below user noticeable time periods.

FIG. 84 displays curves 5702, 5704 of tissue impedance versus time of tissue impedance with 40 W of RF power delivered to tissue using a downhill simplex technique for a model of tissue 5702 and experimental data 5704. As shown in FIG. 84, the curves 5702, 5704 are similar to the curve 2500 shown in FIG. 83.

As demonstrated by the curves of FIG. 84, constant power may be applied to tissue while in the time period 0 seconds to approximately 8.8 seconds, the curves 5702, 5704 have a distinct shape that may be referred to as a “bathtub,” due to the characteristic bathtub shape of the tissue impedance as a function of time while power is applied to the tissue during the sealing process. Once system identification has occurred during the tissue “bathtub” period to estimate k, b₁, b₂, c₁, and c₂of Equation 1 above, a post “bathtub” impedance control technique can be configured for tissue interacting with the end effector 125 of the surgical instrument 108.

One post “bathtub” impedance control technique utilizes parameter estimation to determine tissue characteristics. In one aspect, the parameters estimated during the “bathtub” phase may relate to certain tissue properties, such as, for example tissue type, tissue amount, and tissue state. A predetermined controller can be selected from a range of controllers that best match the parameters estimated based on a lookup table

Another post “bathtub” impedance control technique utilizes a linear quadratic controller (LQR) with precompensation. A linear quadratic controller is a well-known and used controller which can be designed in real time and will result in optimal control of tissue impedance and the rate of change of impedance. In one aspect, an LQR controller can be implemented in the following form:

$\begin{matrix} W = Nb * r - K [\begin{matrix} Z \\ \dot{Z} \end{matrix}] + c_{2} & Equation 4 \end{matrix}$

It is assumed that K is the control gain and r is a desired reference set point and Nb is a precompensation gain to prevent steady state error. From this system, rate rise can be controlled explicitly. The second order differential equation shown in Equation 4 is to be reduced to two first order equations for each value of b₁and b₂. However, if it is assumed that the goal of post “bathtub” energy application will result in Ż>0 ∀ t>0 (that is, Ż>0 for all time values after the start of energy application when t=0) then it can be assumed that the controller must be designed for b=b₂. The reduction to first order is shown in Equation 5:

Let Z=U₁and Ż=U₂

then through substitution:

$\begin{matrix} [\begin{matrix} {\dot{U}}_{1} \\ {\dot{U}}_{2} \end{matrix}] = [\begin{matrix} 0 & 1 \\ k & b \end{matrix}] [\begin{matrix} U_{1} \\ U_{2} \end{matrix}] + [\begin{matrix} 0 \\ 1 \end{matrix}] (W - c_{2}) & Equation 5 \end{matrix}$

For such a system, the optimal control input K can be found by reducing a cost function of a particular form and solving the Ricatti algebraic equation. The control cost function to be reduced has the form given in Equation 4 and is common to all LQR controllers.

$\begin{matrix} J = \int_{0}^{\infty} ([U_{1} U_{2}] Q [\begin{matrix} U_{1} \\ U_{2} \end{matrix}] + [0 W] R [\begin{matrix} 0 \\ W \end{matrix}] + 2 [U_{1} U_{2}] N [\begin{matrix} 0 \\ W \end{matrix}]) dt & Equation 6 \end{matrix}$

R, N, and Q are predetermined constant matrices related to the cost function being reduced and controller performance. They are selected by the design engineer to regulate the controller's performance. When this process is completed, K is given by:

K=R⁻¹(B^TP(t)+N^T Equation 7

In Equation 5, P is the solution to the algebraic Riccati equation in Equation 8:

A^TP+PA−(PB+N)R⁻¹(B^TP+N^T)+Q=0 Equation 8

According to one aspect, upon fitting a model to experimental data points, such as that show in FIG. 84 for curves 5702 and 5704 respectively, Equation 5 may be used to create an optimal controller that holds impedance at a steady state value, r=250 Ohm. FIG. 85 displays curves 5802 and 5804 that represent the modeled data and the experimental data, respectively. As shown in FIG. 85, the controller performed as expected on a fitted tissue model where the desired impedance 5806, Z, is held at 250 Ohm. For the controller shown in FIG. 85, K=[1.9237 4.3321] and Nb=[26.9532]. A range of appropriate gains exist and can be determined. Similarly, a range of feasible gains for the model development can also be determined.

Additionally, a controller also may be configured to operate as a tracking controller to manipulate Ż by updating the reference r appropriately in time. An example of such a controller is illustrated in FIG. 86, where curves 5902 and 5904 that represent the modeled data and the experimental data, respectively, and line 5906 is the desired impedance for one aspect of a tracking controller. As shown in FIG. 86, a desired tissue impedance, where the desired impedance is based on a rate of change of the tissue impedance, may be achieved. Steady state performance with a tracking controller can be improved by incorporating an integrator to the system of equations shown by Equation 7.

FIG. 87 is a logic flow diagram 6000 of a method for identifying a tissue type and developing a control process to control the application of an energy modality to the tissue according to tissue impedance. As described herein, the logic flow diagram 6000 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 6000 shown in FIG. 87, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. In accordance with the method, the generator 500 may not be able to determine a tissue type located between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125. In accordance with the method, the processor 502 signals the waveform generator 504 to deliver 6002 an energy modality to the end effector 125 of the surgical instrument 108. The processor 502 measures 6004 tissue impedance. Application of the energy modality ceases 6006 upon the processor 502 determining that the tissue impedance matches a predetermined threshold tissue impedance. The processor 502 estimates 6008 at least one tissue parameter based at least partially on the measured tissue impedance. According to various aspects, the at least one tissue parameter comprises a tissue type, a tissue amount, a tissue state, or a combination thereof. The processor 502 develops 6010 a parameterized tissue model based on the at least one estimated tissue parameter and generates 6012 a control technique for application of the energy modality based on the parameterized tissue model. Accordingly, the energy modality may be applied to another tissue portion according to the control process.

In another aspect, generating the control process may comprise correlating specific tissue characteristics with the application of the energy modality to the tissue. Furthermore, the control process may be generated in real time such that it readily available for use on further applications to tissue. In addition, the control process may be configured to apply the energy modality so the tissue impedance matches a predetermined threshold value or a predetermined rate of change.

Ultrasonic Output Controlled by RF Impedance Trajectory

In one aspect, the present disclosure provides ultrasonic output controlled by RF impedance trajectory to control the power output from a generator, such as any one of the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), or the surgical instrument 108 (FIGS. 1-3). The power delivered to an end effector of a surgical instrument can vary based on the tissue RF impedance trajectory. For conciseness and clarity of disclosure, the techniques for ultrasonic output controlled by RF impedance trajectory to control the power output from a generator will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

According to one aspect, a surgical instrument may uses an RF energy modality to sense tissue characteristics, such as impedance, and the changes of the tissue characteristics to modulate the output power of an ultrasonic tissue treating system. Specifically, the output power of a surgical instrument may be modulated as a function of a desired impedance trajectory where the impedance trajectory results in a desired tissue effect or outcome. The RF output may be therapeutic, e.g. tissue treating, or sub-therapeutic, e.g. sensing only. Further, the RF output may be applied to the tissue and the voltage and current, or representations of the voltage and current, are measured or estimated. In addition, the impedance may be calculated by determining the ratio of the voltage to the current.

FIG. 88 is a logic flow diagram 6100 of a method for treating tissue. As described herein, the logic flow diagram 6100 may be implemented in the generator 500, the multifunction surgical instrument 108, or a combination thereof. With reference now to the logic flow diagram 6100 shown in FIG. 88, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108. In accordance with the method, the processor 502 signals the waveform generator 504 to deliver 6102 an energy modality to the end effector 125 of the surgical instrument 108. According to various aspects, the energy modality may be an RF energy modality or an ultrasonic energy modality, or a blended combination thereof, and the amplitude may be a therapeutic amplitude, a sub-therapeutic amplitude, or a combination thereof. The processor 502 measures 6104 tissue impedance and signals the waveform generator 504 to modulate 6106 the delivery of the selected energy modality based on the measured tissue impedance. Ultimately, the processor 502 signals the waveform generator 504 to cease 6108 the application of the energy modality upon meeting or exceeding a termination impedance threshold that corresponds to a tissue parameter, such as, for example, that the seal is complete. The application of the energy modality may cease upon the tissue impedance matching a predetermined threshold value of tissue impedance or a predetermined threshold rate of change of tissue impedance. The impedance may be determined by the processor 502 by dividing the output of the second voltage sensing circuit 524 is coupled across the terminals labeled ENERGY2/RETURN by the output of the current sensing circuit 514 is disposed in series with the RETURN leg of the secondary side of the power transformer 508 as shown in FIG. 8.

In accordance with the logic flow diagram 6100, the surgical instrument 108 may further determine that the tissue is sealed based on measuring at least one of an initial tissue impedance, an initial jaws-aperture of an end effector, a current tissue impedance, a rate of change of tissue impedance, an amount of energy driven into the tissue, a transaction time for the energy modality and/or determining a state of the tissue based on the measured tissue impedance of the tissue. The state of the tissue may comprise one of coagulated, sealed, or cut, for example.

Modulating application of the energy modality based on the measured tissue impedance may comprise applying the energy modality to cause the tissue impedance to change according to a predetermined course. In various aspects, the predetermined course comprises a predetermined threshold value of tissue impedance of the tissue or a predetermined threshold rate of change of tissue impedance of the tissue. In another aspect, modulating application of the energy modality based on the measured tissue impedance comprises modifying an output power of a generator, modifying an output waveform of the generator, selecting another energy modality to apply to the tissue, modifying the termination parameter. Additionally, the energy modality may be a first energy modality and the method further comprises applying a second energy modality to tissue at a second amplitude. The first energy modality may be an RF energy modality and the second energy modality may be an ultrasonic energy modality

In another aspect, the generator 500 may comprise an ultrasonic output (ENERGY1/RETURN) configured to deliver a drive signal to an ultrasonic transducer 120 coupled to an ultrasonic blade 149 of the surgical instrument 108. The generator 500 also may comprise an RF output (ENERGY2/RETURN) configured to deliver an electrosurgical RF drive signal to at least one electrode located in the arm 145 of the surgical instrument 108. The generator 500 also may comprise sensing circuitry such as a second voltage sensing circuit 524 and a current sensing circuit 514 configured to measure tissue impedance, and a processor 502 configured to determine whether a tissue reaction has occurred based on a measured tissue impedance of the tissue and a predetermined change in the measured tissue impedance. The waveform generator 504 and amplifier 506 are controlled by the processor 502 to provide the necessary ultrasonic energy or RF energy modalities at the respective outputs of the generator 500 labelled (ENERGY1/RETURN) and (ENERGY2/RETURN).

The tissue treating portion of the ultrasonic blade 149 is configured to apply ultrasonic energy to tissue to affect treatment of the tissue and the ultrasonic amplitude of the tissue treating portion is controlled by the processor 502. The at least one electrode is configured to receive RF energy from the generator 500 output and to apply the RF energy to the tissue via the electrode. The amplitude of the electrosurgical RF energy is controlled by the processor 502. In one aspect, the tissue reaction determination corresponds to a boiling point of fluid in the tissue. Moreover, the processor 502 may be configured to generate a target impedance trajectory as a function of the measured tissue impedance and a predetermined desired rate of change of tissue impedance, and the tissue reaction determination. The target impedance trajectory includes a plurality of target impedance values for each of a plurality of points of time. Furthermore, the processor 502 may be configured to drive tissue impedance along the target impedance trajectory by adjusting the ultrasonic amplitude of the tissue treating portion of the ultrasonic blade 149 to substantially match the tissue impedance to a predetermined tissue impedance value for a predetermined time period.

Also disclosed herein are control processes for dynamically changing the energy delivered from a generator based on tissue impedance of tissue engaged with an end effector, such as an end effector of a surgical instrument 108. According to one aspect, a process for controlling the power output from a generator, such as the generator 500 of FIG. 8, that is delivered to the end effector 125 of the surgical instrument 108 can include an input that represents tissue impedance of tissue engaged with the end effector 125 of the surgical instrument 108. During the tissue treatment process, the energy profile from the generator 500 can be dynamically changed between RF energy and ultrasonic energy based on the tissue impedance. This allows the generator 500 to switch from RF energy to ultrasonic energy based on the tissue impedance of the tissue under treatment. The tissue impedance is related to the creation of a proper coagulation seal, for example, when RF energy is delivered from the generator 500 to the end effector 125 of the surgical instrument 108, such that RF energy should be used when there is sufficient tissue impedance. Thus, in one aspect, when a particular tissue impedance is not found and there is not a sufficient tissue impedance to activate a RF energy modality on the tissue for proper coagulation or seal, ultrasonic energy may be delivered to the end effector 125 to raise the tissue impedance to a level where the RF energy modality can be delivered to complete the seal.

Energy parameters are configured to be loaded into the generator 500, and can include a plurality of different parameters, including but not limited to voltage, current, power, and one or more processes for use in treating tissue. These parameters can be related to the RF energy and ultrasonic energy that can be delivered from the generator 500 and accordingly, may be based on tissue impedance of tissue engaged with a surgical device. The energy parameters can include information such as maximum and/or minimum values to be used to control the energy delivered from the generator 500. The energy parameters can be stored in a variety of locations, including an EEPROM on the surgical instrument 108 or some other non-volatile memory. In addition, there can be multiple sets of energy parameters. For example, there can be a first set of energy parameters that are used to optimize tissue transection, and a second set of energy parameters that are used to optimize tissue spot coagulation. It will be understood that there can be any number of set of energy parameters that correspond to various types of tissue treatments to allow the generator to switch between the various sets of energy parameters based on the necessary tissue treatments.

It will be understood that various combinations of information can be used to determine which set of energy parameters are to be used during tissue treatment. For example, the aperture of the end effector and calculated tissue impedance can be used to determine which set of energy parameters are needed to control the energy being delivered from the generator.

In another aspect, a process for controlling the power output from a generator, such as the generator of FIG. 8, that is delivered to the end effector of the surgical instrument can include an input that includes inputs related to the size of the tissue being treated by the end effector of the surgical instrument. The energy being delivered from the generator can be dynamically changed during the procedure between RF and ultrasonic energy to achieve dissection and coagulation of a large tissue based on a determination of the effectiveness of the RF energy in coagulating the large tissue. A determination of the effectiveness of the RF energy in coagulating a tissue includes a calculation of tissue impedance, as explained above, of the large tissue interacting with the end effector, which is used to determine the type of energy being delivered by the generator to the end effector.

Technique for Switching Between RF and Ultrasonic Energy Based on Tissue Impedance

In one aspect, the present disclosure provides techniques for switching between RF and ultrasonic energy based on tissue impedance. The power output from a generator, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), is delivered to an end effector of a surgical instrument can be controlled based on the tissue impedance. The energy profile of the power output of the generator is dynamically switched between RF and ultrasonic energy modalities based on the tissue impedance to treat the tissue clamped between a clamp jaw and an ultrasonic blade of the end effector of the surgical instrument. For conciseness and clarity of disclosure, the techniques for switching between RF and ultrasonic energy based on tissue impedance will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

The following description provides techniques for measuring tissue impedance and dynamically switching the energy profile of the generator between RF and ultrasonic energy modalities based on the tissue impedance during the procedure. To provide a better seal, it may be desirable to operate a “combination” RF/ultrasonic instrument 108 such that the instrument transition from a tissue coagulation mode to a tissue cut mode during an application of the instrument 108 on tissue. Disclosed is a way to automatically transition from the RF (coagulation or seal) mode to the ultrasonic (cut or transection) mode. In various RF sealing techniques, the RF energy is applied with the goal of driving the tissue impedance to a particular level, called the “termination” impedance. It has been demonstrated that an adequate seal is achieved if an RF sealing technique is able to drive the tissue impedance to this termination impedance.

In order to determine the tissue impedance being treated by the end effector 125 of the surgical instrument 108, the tissue impedance must be calculated. The calculated tissue impedance is compared to a threshold value, as will be discussed in more detail below. The calculated tissue impedance is used by a technique to control the energy being delivered from the generator 500 to the surgical instrument 108 to allow the energy to switch between RF and ultrasonic energy when the tissue impedance reaches the threshold level. In one form, the tissue impedance is described by dividing the voltage measurement by the current measurement. More generally, impedance is the ratio of the voltage vector and the current vector and results in a complex number with the real component R and the imaginary component X dependent on both tissue properties and the frequency and spectra of the applied stimulus. This number also can be expressed in the form of a magnitude, |Z| and phase ϕ. Most calculations of tissue impedance ignore the small contribution of the phase difference between the voltage and current and presume that the magnitude of the impedance vector |Z| is essentially equivalent to the real component of the impedance, R. For purposes of description, the term R and Z indicating tissue impedance will be used interchangeably though it should be noted that sensing of tissue impedance implies that the impedance vector is the general form and any combination of magnitude, phase, real and imaginary components of this vector for determining tissue properties, control of energy delivery and the like is implied by this disclosure.

For example, when utilizing the surgical instrument 108 that can automatically transition between RF and ultrasonic energy, RF energy can be applied to the tissue utilizing the end effector 108 to drive the tissue impedance of the tissue to a particular level, such as a termination impedance. The termination impedance is the tissue impedance level of the tissue that substantially ensure that the RF energy has achieved adequate coagulation of the tissue.

FIG. 89 is a graphical depiction of a tissue impedance function 6200 represented as tissue impedance |Z| (Ohms) as a function of time (Sec) and showing a termination impedance at which a proper tissue seal is achieved utilizing RF energy. The tissue impedance function 6200 shows the termination impedance Z_T6216 at which a proper tissue seal is achieved utilizing RF energy. Time in seconds is shown along the horizontal axis and impedance in Ohms is shown along the vertical axis. The tissue impedance function 6200 can be described in three sections. In section one 6202, the tissue impedance function 6200 represents the initial impedance 6208 of the tissue from a time just after RF energy is applied to the tissue to a time when the tissue impedance drops to a minimum value as shown in the section two 6204. In section one 6202 of the tissue impedance function 6200, the tissue impedance drops from an initial value 6208 and decreases, e.g., has a negative slope, until it reaches a first inflection point 6210 and stabilizes to a minimum impedance 6212 in the second section 6204 of the tissue impedance function 6200 where the tissue impedance function flattens 6200 flattens out. After energy is applied to the tissue for a certain period (e.g., 4.5 seconds as shown) the moisture content of the tissue evaporates causing the tissue to dry out and causes the tissue impedance to begin rising, e.g., positive slope, at a second inflection point 6214 in section three 6206 of the tissue impedance function 6200 until the tissue impedance reaches a predetermined termination impedance 6216, at which point in time the RF energy to the end effector is shut off. The last portion 6218 of the tissue impedance function 6200 in section three 6206 (shown in dashed line) represents the increase in tissue impedance Z that would result if the RF energy were to be applied continuously instead of being shut off at the termination impedance 6216 point. The tissue impedance function 6200 may be referred to as the “bathtub” zone in a tissue sealing process due to its characteristic shape.

Once the termination impedance 6216 is reached, the generator 500 can switch from delivering RF energy to delivering ultrasonic energy to the end effector 125. The termination impedance 6216 can be a fixed value based on the electrode and compression properties or it can be a variable that depends on factors measured during the grasping and coagulation cycle such as amount of tissue grasped, initial impedance, and minimum impedance. It also can be a variable dependent on various slopes of impedance, energy delivery at various points in the coagulation cycle such as minimum impedance, and/or inflection points, and combinations thereof.

FIG. 90 is a logic flow diagram 6300 to control the generator 500 to switch between RF and ultrasonic energy upon reaching a predetermined termination impedance. As described herein, the logic flow diagram 6300 may be implemented in the generator 500, the surgical instrument 108, or a combination thereof. With reference now to the logic flow diagram shown in FIG. 90, the processor 502 determines the tissue impedance as described herein. For example, the processor 502 may determine the tissue impedance by dividing the output of the second voltage sensing circuit 524 coupled across the terminals labeled ENERGY2/RETURN by the output of the current sensing circuit 514 disposed in series with the RETURN leg of the secondary side of the power transformer 508 as shown in FIG. 8. Initially, the end effector 125 of the surgical instrument 108 is closed 6302 on the tissue and the end effector 125 is activated with RF energy from the generator 500. A technique for controlling the RF energy being delivered from the generator 500 to the tissue is applied 6304 to effect a tissue seal using the RF energy. This technique may comprise selecting and applying composite load curves (CLC) tables by the processor 502 of the generator 500, as described in connection with FIG. 64 hereinbelow. The processor 502 compares 6306 the tissue impedance to a threshold value to determine if the tissue impedance has reached the termination impedance at which time the generator 500 can switch from RF energy for coagulating or sealing tissue to ultrasonic energy for cutting tissue. Until the termination impedance is reached, the processor 502 proceeds along the NO branch to and signals the waveform generator 540 or amplifier 506 to continue delivering 6304 RF energy to the end effector 125. When the termination impedance is reached, the processor 502 proceeds along the YES branch and signals the waveform generator 504 or amplifier 506 to stop delivering RF energy (ENERGY2/RETURN) and the switch 6308 to delivering ultrasonic energy (ENERGY1/RETURN). Upon completing the tissue cut utilizing ultrasonic energy, the tissue is released 6310 from the end effector 125.

FIGS. 91A and 91B illustrate example graphs of the energy, both RF and ultrasonic, that is delivered to an end effector 125 of a surgical instrument 108 from a generator 500. The technique as described herein can be used to control the RF and ultrasonic energy to automatically switch from RF to ultrasonic energy to perform tissue cutting. A combined RF and ultrasonic surgical instrument 108 would then use a technique graphically depicted in FIGS. 91A and 91B to deliver and control RF energy to the electrodes in the end effector 125. At the end of the termination pulses 6406 (FIG. 91A), the generator 500 can automatically switch over to the ultrasonic mode to perform the tissue cutting.

In particular, FIG. 91A is a graphical depiction 6400 of a generator RF power 6402 function and RF tissue impedance function 6404 represented as functions of time. The RF power function 6402 is delivered from a generator 500 to an end effector 125 of a surgical instrument 108. Power (Joules) is shown along the left vertical axis, tissue impedance (Ohms) is shown along the right vertical axis, and time (Seconds) is shown along the horizontal axis. FIG. 91B is a graphical depiction 6450 of a RF voltage function 6452 and a RF current function 6454 represented as functions of time. The RF voltage and current functions 6452, 6454 coincide with the RF power and impedance functions 6402, 6404 delivered from the generator 500 to the electrodes in the end effector 125 of the surgical instrument 108. RF voltage (V) is shown along the left vertical axis, RF current (mA) is shown along the right vertical axis, and time (Seconds) is shown along the horizontal axis. Although the graphical depictions 6400, 6450 of the RF power function 6402 and the RF tissue impedance function 6404 and the RF voltage and RF current functions 6452, 6454 are shown in two separate graphs, it will be appreciated that all four functions 6402, 6404, 6452, 6454 occur simultaneously in response to the tissue impedance and techniques executed by the control circuits of the generator 500.

The graphical depiction 6400 of the RF power function 6402, the RF tissue impedance function 6404, the RF voltage function 6452, and the RF current function 6454 are divided into three separate modes. In Mode 1, the generator 500 delivers the RF power function 6402 to the electrodes in contact with the tissue clamped between the clamp jaw 145 and the ultrasonic blade 149 of the end effector 125. In Mode 1, the tissue impedance is low and demands high RF current 6454 from the generator 500. Thus, as the RF current 6452 is pulsed the RF voltage 6454 drops below its nominal output level. While the RF power 6402 is delivered to the tissue, the generator 500 enters Mode 2 where the control circuit manages the RF power 6402 delivered to the tissue to effect a proper seal. In one aspect, during Mode 2, the process includes selecting and applying CLC tables by the processor 502 of the generator 500, as described in connection with FIG. 64 hereinbelow. As the RF power function 6402 is applied to the tissue in Modes 1 and 2, the tissue begins to seal and moisture is evaporated for the tissue due to the heat generated in the process causing the tissue impedance to increase. This is known as the “bathtub” zone, as previously described in connection with the tissue impedance function 6200 in FIG. 89. Back to FIG. 91B, the generator 500 enters Mode 3 when the tissue impedance reaches a termination impedance 6406 of the RF tissue impedance function 6404. In Mode 3, the processor 502 signals the waveform generator 504 to employ RF energy to measure the tissue impedance and to use ultrasonic energy to the ultrasonic blade 149 to cut the tissue. Non-therapeutic RF power function 6402 may be applied to the tissue to measure the tissue impedance during the ultrasonic cutting phase in Mode 3.

FIG. 91C is a graphical depiction 6475 of the power function 6402, impedance function 6404, voltage function 6452, and current function 6453 as a function of time delivered from a generator to an end effector of a surgical instrument as shown in FIGS. 91A and 91B.

Simultaneous Control Techniques for Combination Ultrasonic/RF Surgical Instrument

In one aspect, the present disclosure provides a technique for controlling the power output from a generator, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8). The power delivered to an end effector of a surgical instrument can include simultaneous activation of RF and ultrasonic energy modalities to treat the tissue clamped between a clamp jaw and an ultrasonic blade of the end effector of the surgical instrument. For conciseness and clarity of disclosure, the techniques for simultaneously activating RF and ultrasonic energy modalities will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

The following description provides techniques for simultaneous activation of RF and ultrasonic energy modalities to treat the tissue clamped between a clamp jaw and an ultrasonic blade of the end effector of the surgical instrument. For conciseness and clarity of disclosure, the simultaneous application of different energy modalities will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

There are many benefits to a surgical instrument 108 that is capable of delivering both RF and ultrasonic energy. By having both modalities in one instrument 108, the instrument 108 is able to create stronger seals and also cut without the need for a separate knife. The following disclosure provides multiple simultaneous energy delivery techniques that could be used for sealing various vessels.

In general, the present disclosure provides a surgical instrument 108 and generator 500 capable of simultaneous activation of both RF and ultrasonic energy modalities. The simultaneous activation of both RF and ultrasonic energy modalities may be implemented utilizing a single generator capable of delivering both energy modalities from two or more ports, two separate generators, or a single port generator 500 capable of delivering both RF and ultrasonic energy modalities via a single port. Multiple configurations of the simultaneous techniques are disclosed. In one aspect, a technique utilizes CLC tables to implement an RF sealing technique while the ultrasonic energy is activated at a constant power level. Accordingly, the RF CLC tables are activated at the same time that ultrasonic energy is delivered. In one aspect, the technique selects and applies the CLC tables process according to FIG. 81.

During a seal only mode, the activation of power for both RF and ultrasonic energies are terminated at the point at which the RF termination impedance is reached, therefore, preventing the risk of inadvertently cutting through the tissue. One advantage of simultaneous activation of RF and ultrasonic energy modalities is that the ultrasonic energy heats up the ultrasonic blade 149 and helps to create a reduction in the difference in thermal mass between the ultrasonic blade 149 and the electrode.

In particular, FIG. 92 is a logic flow diagram 6500 of one aspect of a process of applying simultaneous activation of different energy modalities to tissue. As described herein, the logic flow diagram 6500 may be implemented in the generator 500, the surgical instrument 108, or a combination thereof. Wth reference now to the logic flow diagram 6500, tissue is clamped between the clamp arm 145 and the ultrasonic blade 149 of the end effector 125 of the surgical instrument 108 and then the generator 500 applies the simultaneous energy modalities. The RF energy delivery process 6502 is shown on the left side of the logic flow diagram 6500 and the ultrasonic energy delivery process 6512 is shown on the right. Once the tissue is clamped between the clamp jaw 145 and the ultrasonic blade 149, the processor 502 signals the waveform generator 504 to activate 6504 the RF energy and to activate 6514 the ultrasonic energy at a constant power level. Once the RF energy is activated 6504 the processor 502 signals the waveform generator 504 to deliver 6506 RF sealing techniques and to maintain 6516 the ultrasonic energy at a constant power level activation. In one aspect, the RF sealing techniques applied by the generator 500 involve selecting and applying the CLC tables according to the process described in FIG. 81. Referring back to FIG. 92, during the application 6506 of the RF sealing techniques, the processor 502 monitors the tissue impedance and determines when the termination impedance is reached. When the termination impedance is reached 6508, feedback is signaled 6518 to the processor 502 to terminate the ultrasonic power delivery. Subsequently, the processor 502 signals the waveform generator 504 to terminate 6510 the RF power and to terminate 6520 the ultrasonic power. As previously discussed, the processor 502 measures the RF tissue impedance by dividing the output of the second voltage sensing circuit 524 by the output of the current sensing circuit 514.

FIG. 93 is a graphical depiction 6600 of an RF tissue impedance function 6602 represented as RF tissue impedance (Ohms) as a function of time (Sec) in connection with the logic flow diagram 6500 of FIG. 92 to illustrate first and second termination impedances. As previously described, one advantage of simultaneous activation of RF and ultrasonic energy modalities is that the ultrasonic energy heats up the blade and helps to create a reduction in the difference in thermal mass between the blade and the electrode. In the graphical depiction 6600 of FIG. 93, the horizontal axis is time (ms) and the vertical axis is RF tissue impedance (Ohms). The first portion 6604 of the RF tissue impedance function 6602 coincides with the application of the RF energy sealing process described in connection with FIG. 64 and the constant ultrasonic power. The tissue impedance is monitored during the tissue sealing process utilizing the RF energy. When the tissue impedance reaches a first termination impedance 6606, the ultrasonic power is terminated and when the tissue impedance reaches a second termination impedance 6608 the RF power is terminated to avoid cutting through the sealed tissue.

FIG. 94 illustrates an example of the quality of a seal 6702 made in a vessel 6700 utilizing simultaneous activation of RF and ultrasonic energy modalities as described in connection with FIGS. 92 and 93. The main advantage of simultaneous activation of RF and ultrasonic energy modalities is that the ultrasonic energy heats up the ultrasonic blade 149 and helps to create a reduction in the difference in thermal mass between the ultrasonic blade 149 and the electrode in the clamp arm 145. During a non-simultaneous activation seal cycle utilizing both RF and ultrasonic modalities, a challenge is posed to create a strong seal with varying thermal masses on either side of the end effector 125 jaw. The boxplots shown in FIGS. 95 and 96 below demonstrate the tissue effect advantages mentioned above (simultaneously heating the ultrasonic blade 149 and electrode) of activating a simultaneous energy modality technique.

FIG. 95 is a boxplot graphic 6800 comparison of the burst pressure of a carotid artery seal made utilizing: (1) simultaneous application of RF and ultrasonic energy and (2) application of RF energy only as described in connection with FIGS. 92-94. Energy modality is shown along the horizontal axis and burst pressure (mmHg) of the two carotid artery seals represented by first and second boxplots 6802, 6804 is shown along the vertical axis. Along the horizontal axis, the first boxplot 6802 represents a carotid artery seal made utilizing simultaneous RF/ultrasonic energy and the second boxplot 6804 represents a carotid artery seal made utilizing RF energy only. The first and second boxplots 6802, 6804 demonstrate the tissue effect advantages provided by the simultaneous application of RF/ultrasonic energy modality as depicted by the logic flow diagram 6500 of FIG. 92 where simultaneously heating the ultrasonic blade 149 and electrode provides the high quality tissue seal 6702 shown in FIG. 94.

FIG. 96 is a boxplot graphic 6900 comparison of the burst pressure of a carotid artery bundle seal made utilizing: (1) simultaneous application of RF and ultrasonic energy and (2) application of RF energy only as described in connection with FIGS. 92-94. Energy modality is shown along the horizontal axis and burst pressure (mmHg) of the two carotid artery bundle seals represented by first and second boxplots 6902, 6904 is shown along the vertical axis. Along the horizontal axis, the first boxplot 6902 representing a carotid artery bundle seal made utilizing simultaneous RF/ultrasonic energy and the second boxplot 6904 represents a carotid artery bundle seal made utilizing RF energy only. The first and second boxplots 6902, 6904 demonstrate the tissue effect advantages provided by the simultaneous application of RF/ultrasonic energy modality as depicted by the logic flow diagram 6500 of FIG. 92 where simultaneously heating the ultrasonic blade 149 and electrode provides the high quality tissue seal 6702 shown in FIG. 94.

FIG. 97 is a boxplot graphic 7000 comparison of the burst pressure of a thyrocervical artery seal made utilizing: (1) simultaneous application of RF and ultrasonic energy and (2) application of RF energy only as described in connection with FIGS. 92-94. Energy modality is shown along the horizontal axis and burst pressure (mmHg) of the two thyrocervical artery seals represented by first and second boxplots 7002, 7004 is shown along the vertical axis. Along the horizontal axis, the first boxplot 7002 represents a thyrocervical artery seal made utilizing simultaneous RF/ultrasonic energy and the second boxplot 7004 represents a thyrocervical artery seal made utilizing RF energy only. The first and second boxplots 7002, 7004 demonstrate the tissue effect advantages provided by the simultaneous application of RF/ultrasonic energy modality as depicted by the logic flow diagram 6500 of FIG. 92 where simultaneously heating the ultrasonic blade 149 and electrode provides the high quality tissue seal 6702 shown in FIG. 94.

There are several factors that can drive the simultaneous RF/ultrasonic energy application technique. Ultrasonic power level is a factor if a “seal only” configuration is desired. For example, a lower ultrasonic power level may be selected as not to cut through the tissue. Data suggests that the higher the ultrasonic power level, the greater the seal results as shown and described below in connection with FIG. 98. In particular, FIG. 98 is a boxplot graphic 7100 comparison of the burst pressure of a carotid artery bundle seal made utilizing simultaneous application of: (1) RF and lower ultrasonic energy and (2) RF energy and higher ultrasonic energy as described in connection with FIGS. 92-94. Ultrasonic power level is shown along the horizontal axis and burst pressure (mmHg) of the two carotid artery bundle seals represented by first and second boxplots 7102, 7104 is shown along the vertical axis. Along the horizontal axis, the first boxplot 7102 represents a carotid artery bundle seal made utilizing simultaneous RF energy and lower ultrasonic energy and the second boxplot 7104 represents a carotid artery bundle seal made utilizing RF energy and lower ultrasonic energy relative to the first boxplot 7102. The first and second boxplots 7102, 7104 demonstrate that the higher the ultrasonic power level, the greater the seal.

If a “seal and cut” configuration is desired, a higher ultrasonic power level may be selected as an option to seal and cut tissue more efficiently with great tissue effects. Additionally, ultrasonic power level can also be altered during the seal/transection cycle based on the RF tissue impedance feedback. During a seal and cut cycle, the RF tissue impedance can be monitored and ultrasonic power delivered based on RF feedback impedance. There are different points during a seal in which impedance readings are useful including, for example, termination Impedance and power pulse impedance.

In regard to the termination impedance, one of which is the termination impedance which occurs as the impedance rises out of the sealing zone 6604 at a steady rate, as shown in FIG. 93. In particular, FIG. 99 is a boxplot graphic 7200 comparison of the burst pressure of a carotid artery bundle seal made utilizing simultaneous application of RF and ultrasonic energy at different termination impedances as described in connection with FIGS. 92-94. Termination impedance (Ohms) is shown along the horizontal axis and burst pressure (mmHg) of the two carotid artery bundle seals represented by first and second boxplots 7202, 7204 is shown along the vertical axis. Along the horizontal axis, the first boxplot 7202 represents a carotid artery bundle seal made utilizing simultaneous application of RF energy and ultrasonic energy terminated at a termination impedance of 1000 Ohms and the second boxplot 7204 represents a carotid artery bundle seal made utilizing simultaneous application of RF energy and ultrasonic energy terminated at a termination impedance of 2000 Ohms. The first and second boxplots 7202, 7204 demonstrate that the higher the termination impedance, the greater the seal. Thus, termination impedance is a statistical factor in the bundle tissue model for burst pressure as it yielded greater burst pressure results.

The power pulse impedance threshold is another point at which the sealing process could be optimized. This is the point at which the power pulse of the CLC tables delivers the most energy into the tissue. It monitors the point at which the impedance threshold is reached to know when the tissue has reached the state to begin the termination pulses. Changing the impedance value of the power pulse (lower value) can enable faster seal times with the same great burst pressure results.

Modulation Techniques for Ultrasonic Energy in Seal Only and Seal and Cut Modes

In one aspect, the present disclosure provides techniques for modulating ultrasonic energy in seal only mode and seal and cut mode. The power output from a generator, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), is controlled to modulate ultrasonic energy in seal only mode and seal and cut mode. The ultrasonic energy delivered to an end effector of a surgical instrument can be modulated to provide “seal only” mode or “seal and cut” mode to treat the tissue clamped between a clamp jaw and an ultrasonic blade of the end effector of the surgical instrument. For conciseness and clarity of disclosure, the techniques for modulating ultrasonic energy in seal only mode and seal and cut mode will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

The following description provides techniques for modulating ultrasonic energy in seal only and seal and cut modes to treat the tissue clamped between a clamp jaw and an ultrasonic blade of the end effector of the surgical instrument. For conciseness and clarity of disclosure, the simultaneous application of different energy modalities will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

In general, a surgical instrument 108 configured with a “seal only” mode and a “seal and cut” mode provide the surgeons the option of sealing or sealing and cutting tissue based on their intended surgical task. In one aspect, the surgical instrument 108 is configured to utilize both RF and ultrasonic technology in combination to achieve this task. In one aspect, in a “seal only” mode, the generator 500 is configured to determine when a cut is complete to eliminate a partial transection 7304 as shown in FIG. 100 below. An example of a vessel with a quality vessel seal made utilizing simultaneous application of RF and ultrasonic energy is shown FIG. 99. In particular, FIG. 100 is an example of a vessel 7360 with a partial seal 7302 made utilizing simultaneous application of RF and ultrasonic energy and a partial transection 7304 made utilizing ultrasonic energy.

Accordingly, it is desirable to provide “seal only” and “seal and cut” techniques utilizing RF and ultrasonic energy modalities to optimize the quality of seal and a seal and cut operation. In one aspect, a “seal only” technique may be applied as graphically depicted in FIG. 101. The seal only technique delivers simultaneous energy of ultrasonic and RF for the duration of the seal. The seal only technique can be optimized by modulating the ultrasonic energy delivered based on the RF tissue impedance.

In particular, FIG. 101 is a graphical depiction 7400 of an RF tissue impedance function 7402 represented as RF tissue impedance (Ohms) as a function of time (Sec) and an ultrasonic current function 7404 represented as ultrasonic current (mA) as a function of time (Sec) during a “seal only” modality. Time (Sec) is shown along the horizontal axis, impedance (Ohms) is shown along the left vertical axis, and ultrasonic current (mA) is shown along the right vertical axis. The “seal only” modality is achieved in three separate stages. During a first stage 7406, only RF energy is delivered to the electrodes and the ultrasonic current function 7404 is zero. During the first stage 7406, the impedance is slightly above zero such that power can be delivered to the tissue. At the end of the first stage 7406 and marking the beginning of the second stage 7408, the ultrasonic energy is delivered to the ultrasonic blade 149 in conjunction with the RF energy. During the second stage 7408, the ultrasonic current 7414 remains constant at −200 mA and the impedance begins to slowly increase as the tissue dries during the sealing process. Once the inflection point 7412 of the impedance function 7402 is reached, at the end of the second stage 7408 marking the beginning of the third stage 7410, the impedance starts to rapidly increase. The impedance is fed back to the generator 500 and when the impedance is equal to or greater than the inflection point 7412 impedance, the generator 500 decrements the ultrasonic current to reduce the amount of ultrasonic energy applied to the tissue to avoid cutting the tissue and achieve the seal only modality. During the third stage 7410, the ultrasonic current is decremented by equal steps 7416, as shown in FIG. 101, until the seal is complete, but without cutting the tissue. In other aspects, the ultrasonic current may be decremented by variable and non-equal steps 7416. In one aspect the decrement value is −50 mA, and thus the first decremented current value is −150 mA. When the impedance reaches a termination impedance, both the RF and ultrasonic power are turned off.

FIG. 102 is logic flow diagram 7500 of one aspect of a technique for simultaneous activation of RF and ultrasonic energy and modulating the ultrasonic energy to achieve a seal only process. As described herein, the logic flow diagram 7500 may be implemented in the generator 500, the surgical instrument 108, or a combination thereof. Wth reference to the graphical depiction 7400 of FIG. 101 and in accordance with the logic flow diagram 7500 of FIG. 102, the processor 502 signals the waveform generator 504 to deliver 7502 RF energy to the end effector 125 (e.g., to the electrode) for a first period during the first stage 7406 of the seal only process. At the end of the first period, the processor 502 signals the waveform generator 504 to deliver 7504 ultrasonic energy to the end effector 125 (e.g., to the ultrasonic blade 149) for a second period during the second stage 7408 of the seal only process. The processor 502 monitors 7506 the RF tissue impedance and compares 7508 the RF tissue impedance to a predetermined impedance corresponding to the inflection point 7412 impedance of the impedance function 7402 as shown in FIG. 101. If the RF tissue impedance is less than the predetermined inflection point 7412 impedance (“inflection impedance”), near the end of the sealing stage where the impedance begins to rapidly rise, the processor 502 proceeds along the NO branch and continues to monitor 7506 the RF tissue impedance while RF energy and constant ultrasonic energy is delivered 7502, 7504 to the end effector 125 during the second stage 7408 of the seal only process. As previously discussed, the processor 502 measures the RF tissue impedance by dividing the output of the second voltage sensing circuit 524 by the output of the current sensing circuit 514.

When the RF tissue impedance is equal to or greater than the inflection impedance, the process proceeds along the YES branch and the processor 502 signals the waveform generator 504 to reduce 7510 the ultrasonic energy from a first power level to a second power level by a predetermined decrement (˜50 mA, or any suitable or desired value). The ultrasonic energy may be reduced by a discrete reduction of a numerical quantity or may be reduced by a continuous quantity. In one aspect, the ˜200 mA ultrasonic current delivered during the second stage 7408 is decreased by a ˜50 mA step to ˜150 mA, to minimize the risk of partially transecting or cutting the vessel and achieve the seal only modality. The processor 502 compares 7512 the RF tissue impedance to a predetermined termination impedance. If the RF tissue impedance is less than the termination impedance, the processor 502 proceeds along the NO branch and the ultrasonic current function 7404 is reduced 7510 by the predetermined step, which can be done in equal or variable steps. When the RF tissue impedance is equal to or greater than the termination impedance, the processor 502 proceeds along the YES branch and the generator 500 terminates 7514 both the RF and ultrasonic energy. The modulated ultrasonic current function 7404 shown in FIG. 101 enables the achievement of a “seal only” modality without the risk of a partial transection. The technique can be store as a logic function or series of computer executable instructions in a look-up table in memory, such as an EEPROM located on the surgical instrument 108 or the generator 500.

In particular, FIG. 103 is a graphical depiction 7600 of an RF tissue impedance function 7602 represented as RF tissue impedance (Ohms) as a function of time (Sec) and an ultrasonic current function 7404 represented as ultrasonic current (mA) as a function of time (Sec) during a “seal and cut” modality. Time (Sec) is shown along the horizontal axis, impedance (Ohms) is shown along the left vertical axis, and ultrasonic current (mA) is shown along the right vertical axis. The “seal and cut only” modality is achieved in three separate stages. During a first stage 7606, only RF energy is delivered to the electrodes and the ultrasonic current function 7604 is zero. During the first stage 7606, the impedance is slightly above zero such that power can be delivered to the tissue. At the end of the first stage 7606 and marking the beginning of the second stage 7608, the ultrasonic energy is delivered to the ultrasonic blade 149 in conjunction with the RF energy. During the second stage 7608, the ultrasonic current 7614 remains constant at ˜200 mA and the impedance begins to slowly increase as the tissue dries during the sealing process. Once the inflection point 7612 of the impedance function 7602 is reached, at the end of the second stage 7608 marking the beginning of the third stage 7610, the impedance starts to rapidly increase. The impedance is fed back to the generator 500 and when the impedance is equal to or greater than the inflection point 7612 impedance, the generator 500 increments the ultrasonic current to increase the amount of ultrasonic energy applied to the tissue to achieve the seal and cut modality. During the third stage 7610, the ultrasonic current is incremented in equal steps 7616, as shown in FIG. 103, until the seal and cut is achieved. In other aspects, the ultrasonic current may be incremented by variable and non-equal steps. In one aspect the increment step 7616 value is ˜50 mA, and thus the first incremented current value is ˜150 mA. When the impedance reaches a termination impedance indicating that the cut is complete, both the RF and ultrasonic power are turned off.

FIG. 104 is a logic flow diagram 7700 of one aspect of a technique for simultaneous activation of RF and ultrasonic energy and modulating the ultrasonic energy to achieve a seal and cut process. As described herein, the logic flow diagram 7700 may be implemented in the generator 500, the surgical instrument 108, or a combination thereof. Wth reference to the graphical depiction 7600 of FIG. 103 and in accordance with the logic flow diagram 7700 of FIG. 104, the processor 502 signals the waveform generator 504 to deliver 7702 RF energy to the end effector 125 (e.g., to the electrode) for a first period during the first stage 7606 of the seal and cut process. At the end of the first period, the processor 502 signals the waveform generator 504 to deliver 7704 ultrasonic energy to the end effector 125 (e.g., the ultrasonic blade 149) for a second period during the second stage 7608 of the seal and cut process. The processor 502 monitors 7706 the RF tissue impedance during a sealing portion of the seal and cut process. The processor 502 compares 7708 the RF tissue impedance to a predetermined impedance corresponding to the inflection point 7612 of the impedance function 7602. If the RF tissue impedance is less than the predetermined inflection point 7612 impedance (“inflection impedance”), near the end of the sealing stage where the impedance begins to rapidly rise, the processor 502 proceeds along the NO branch and continues to monitor 7706 the RF tissue impedance while RF energy and constant ultrasonic energy is delivered 7702, 7704 to the end effector 125 during the second stage 7408 of the seal and cut process. As previously discussed, the processor 502 measures the RF tissue impedance by dividing the output of the second voltage sensing circuit 524 by the output of the current sensing circuit 514.

When the RF tissue impedance is equal to or greater than the inflection impedance, the processor 502 proceeds along the YES branch and signals the waveform generator 504 to increase 7710 the ultrasonic energy from a first power level to a second power level by a predetermined decrement (˜75 mA, or any suitable or desired value). The ultrasonic energy may be increased by a discrete reduction of a numerical quantity or may be increased by a continuous quantity. In one aspect, the ˜200 mA ultrasonic current is increased to ˜275 mA by a ˜75 mA step to achieve the seal and cut modality. The processor 502 compares 7712 the RF tissue impedance to a predetermined termination impedance. If the RF tissue impedance is less than the termination impedance, the processor 502 proceeds along the NO branch and the ultrasonic current function 7604 is increased 7710 by the predetermined step, which can be done in equal or variable steps. When the RF tissue impedance is equal to or greater than the termination impedance, the process proceeds along the YES branch and the generator 500 terminates 7714 both the RF and ultrasonic energy once the seal and cut has been achieved. The modulated ultrasonic current function 7604 shown in FIG. 103 enables the achievement of a “seal and cut” modality. The technique can be store as a logic function or series of computer executable instructions in a look-up table in memory, such as an EEPROM located on the surgical instrument 108 or the generator 500.

Techniques for Reducing Displacement of Ultrasonic Blade as a Function of RF Tissue Impedance

In one aspect, the present disclosure provides techniques to reduce ultrasonic blade displacement as a function of RF tissue impedance for RF/Ultrasonic combination surgical instruments. The power output from a generator, such as the generators 102, 200, 300, 400, 500 (FIGS. 1-3 and 4-8), is delivered to an end effector of a surgical instrument and can be controlled to reduce the displacement of an ultrasonic blade as a function of RF tissue impedance to treat the tissue clamped between a clamp jaw and an ultrasonic blade of the end effector of the surgical instrument. For conciseness and clarity of disclosure, the techniques for reducing ultrasonic blade displacement as a function of RF tissue impedance will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

The following description provides techniques for reducing the displacement of an ultrasonic blade as a function of RF tissue impedance to treat the tissue clamped between a clamp jaw and an ultrasonic blade of the end effector of the surgical instrument. For conciseness and clarity of disclosure, the simultaneous application of different energy modalities will be described with reference to the surgical instrument 108 of FIG. 2 coupled to the generator 500 of FIG. 8, although it will be appreciated that other configurations of instruments, generators, and end effectors described herein may be readily substituted without departing from the scope of the present disclosure.

In general, it is desirable to reduce the displacement of the ultrasonic blade 149 as a function of RF tissue impedance. Reduction of the ultrasonic blade 149 displacement can prevent prematurely cutting the tissue clamped between the clamp jaw 145 and the ultrasonic blade 149 of the end effector 125 if cutting tissue is not desired. In order to decay the displacement of the ultrasonic blade 149, a rise in RF tissue impedance can be used as feedback to the generator 500 as is well known that RF tissue impedance indicates the state of the tissue. For example, tissue with low impedance (i.e., in the first phase of the tissue sealing process) at current operating pressures indicates that the tissue has not yet been cut because the low impedances indicate the presence of tissue between the clamp jaw 145 and the ultrasonic blade 149 of the end effector 125. In general, there has been a reluctance to use high ultrasonic energy while the tissue is in the first phase of sealing for fear of cutting the tissue prematurely. Nevertheless, high ultrasonic energy is desirable in this phase to facilitate energy delivery to tissue when the RF tissue impedance is too low to drive electrical power into large bites of tissue.

A simple mathematical relationship between RF tissue impedance (Z) and ultrasonic blade displacement controlled by the current I_hflowing through the ultrasonic transducer can be employed to decay the displacement of the ultrasonic blade to zero or similar low value to prevent cutting tissue. A number of mathematical mappings exist to appropriately reduce I_has a function of Z such as neural networks, fuzzy logic, polynomials, radial basis functions, Fourier series, and the like, because many functions and series have been proven to map any relationship when a sufficiently high enough order is used. However, only a few functions exist that have a small number of adjustable gains that are intuitive to enable optimization. An intuitive functional mapping is represented in Equation 9 below:

$\begin{matrix} I_{h} = {\begin{matrix} I_{\max} \\ \frac{I_{\max} (Z^{- n} - Z_{\max}^{- n})}{(Z_{\min}^{- n} - Z_{\max}^{- n})} \\ 0 \end{matrix} \begin{matrix} \forall \\ \forall \\ \forall \end{matrix} \begin{matrix} Z < Z_{\min} \\ Z_{\min} < Z < Z_{\max} \\ Z > Z_{\max} \end{matrix} & Equation 9 \end{matrix}$

Where I_maxis the maximum current the ultrasonic blade can tolerate, Z_minis the threshold impedance that dictates when the tissue has exited the “first phase,” Z_maxis the impedance at which it is desired to have I_h=0 Amps, and the exponent n dictates the rate of decay of the tissue. Both the max and min impedance values can be dynamically updated as a function of the initial Z of the tissue during energy onset. A plot of Equation 1 with Z_max=500 Ohm, Z_min=50 Ohm, and I_max=200 mA for various n values is presented in FIG. 105.

In particular, FIG. 105A is a graphical depiction 7800 of an ultrasonic current functions represented as ultrasonic current I_h(Amperes) delivered to the ultrasonic transducer as a function of RF tissue impedance Z (Ohms) for various n values. The horizontal axis is RF tissue impedance Z (Ohms) and the vertical axis is ultrasonic current I_h(Amperes). The first ultrasonic current function 7802 has n=2. The second ultrasonic current function 7804 has n=1. The third ultrasonic current function 7806 has n=−0.25. The fourth ultrasonic current function 7808 has n=−1. The fifth ultrasonic current function 7810 has n=−3. The sixth ultrasonic current function 7812 has n=−10.

Additionally, FIG. 105B is a graphical depiction 7800′ of another set of ultrasonic current functions represented as ultrasonic current I_h(Amperes) delivered to the ultrasonic transducer as a function of RF tissue impedance Z (Ohms) for various n values. The horizontal axis is RF tissue impedance Z (Ohms) and the vertical axis is ultrasonic current In (Amperes). The first ultrasonic current function 7802′ has n=0.03. The second ultrasonic current function 7804′ has n=0.04. The third ultrasonic current function 7806′ has n=0.06. The fourth ultrasonic current function 7808′ has n=0.1.

FIG. 106 is a graphical depiction 7900 of multiple ultrasonic functions represented as functions of time. In particular, FIG. 106 is a graphical depiction 7900 of voltage 7902 (V) as a function of time (Sec), current 7904 (A) as a function of time (Sec), power 7906 (W) as a function of time (Sec), and frequency (kHz) as a function of time (Sec), where voltage (V) and current (A) are shown along the left vertical axis, power (W) and impedance (Ohm) are shown along the right vertical axis, and time (Sec) is shown along the horizontal axis.

FIG. 107 is a graphical depiction 8000 of constant RF power that was inputted into Equation 1 with RF energy terminated at 500 Ohm terminal impedance. In particular, FIG. 107 is a graphical depiction 8000 of voltage 8002 (V) as a function of time (Sec), current 8004 (A) as a function of time (Sec), power 8006 (W) as a function of time (Sec), and impedance (Ohms) as a function of time (Sec), where voltage (V) and current (A) are shown along the left vertical axis, power (W) and impedance (Ohm) are shown along the right vertical axis, and time (Sec) is shown along the horizontal axis.

Although the surgical system 100 is independent of the RF technique being applied, for clarity of illustration, a constant RF power was delivered to tissue and the ultrasonic current into the ultrasonic transducer was reduced accordingly as shown in FIGS. 106 and 107. This technique achieves a tissue seal without cutting the tissue. In FIG. 107, the RF termination impedance was set to 500 Ohms and n=−1. The RF power delivered (with low risk of cutting tissue) does not need to terminate at the same time that the ultrasonic power is terminated. Post phase one, the RF power heating of tissue improves sealing and can continue once ultrasonic power has been shut off. For a given jaw pressure and geometry, a surface response design of experiment can be performed to optimize the parameter values.

While various details have been set forth in the foregoing description, it will be appreciated that the various aspects of the surgical system with user adaptable techniques based on tissue type may be practiced without these specific details. For example, for conciseness and clarity selected aspects have been shown in block diagram form rather than in detail. Some portions of the detailed descriptions provided herein may be presented in terms of instructions that operate on data that is stored in a computer memory. Such descriptions and representations are used by those skilled in the art to describe and convey the substance of their work to others skilled in the art. In general, a technique refers to a self-consistent sequence of steps leading to a desired result, where a “step” refers to a manipulation of physical quantities which may, though need not necessarily, take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It is common usage to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. These and similar terms may be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities.

Unless specifically stated otherwise as apparent from the foregoing discussion, it is appreciated that, throughout the foregoing description, discussions using terms such as “processing” or “computing” or “calculating” or “determining” or “displaying” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.

It is worthy to note that any reference to “one aspect,” “an aspect,” “one form,” or “an form” means that a particular feature, structure, or characteristic described in connection with the aspect is included in at least one aspect. Thus, appearances of the phrases “in one aspect,” “in an aspect,” “in one form,” or “in an form” in various places throughout the specification are not necessarily all referring to the same aspect. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner in one or more aspects.

Some aspects may be described using the expression “coupled” and “connected” along with their derivatives. It should be understood that these terms are not intended as synonyms for each other. For example, some aspects may be described using the term “connected” to indicate that two or more elements are in direct physical or electrical contact with each other. In another example, some aspects may be described using the term “coupled” to indicate that two or more elements are in direct physical or electrical contact. The term “coupled,” however, also may mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other.

Although various forms have been described herein, many modifications, variations, substitutions, changes, and equivalents to those forms may be implemented and will occur to those skilled in the art. Also, where materials are disclosed for certain components, other materials may be used. It is therefore to be understood that the foregoing description and the appended claims are intended to cover all such modifications and variations as falling within the scope of the disclosed forms. The following claims are intended to cover all such modification and variations.

In a general sense, those skilled in the art will recognize that the various aspects described herein which can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or any combination thereof can be viewed as being composed of various types of “electrical circuitry.” Consequently, as used herein “electrical circuitry” includes, but is not limited to, electrical circuitry having at least one discrete electrical circuit, electrical circuitry having at least one integrated circuit, electrical circuitry having at least one application specific integrated circuit, electrical circuitry forming a general purpose computing device configured by a computer program (e.g., a general purpose computer configured by a computer program which at least partially carries out processes and/or devices described herein, or a microprocessor configured by a computer program which at least partially carries out processes and/or devices described herein), electrical circuitry forming a memory device (e.g., forms of random access memory), and/or electrical circuitry forming a communications device (e.g., a modem, communications switch, or optical-electrical equipment). Those having skill in the art will recognize that the subject matter described herein may be implemented in an analog or digital fashion or some combination thereof.

The foregoing detailed description has set forth various forms of the devices and/or processes via the use of block diagrams, flowcharts, and/or examples. Insofar as such block diagrams, flowcharts, and/or examples contain one or more functions and/or operations, it will be understood by those within the art that each function and/or operation within such block diagrams, flowcharts, or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. In one form, several portions of the subject matter described herein may be implemented via Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), digital signal processors (DSPs), or other integrated formats. However, those skilled in the art will recognize that some aspects of the forms disclosed herein, in whole or in part, can be equivalently implemented in integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more processors (e.g., as one or more programs running on one or more microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and/or writing the code for the software and or firmware would be well within the skill of one of skill in the art in light of this disclosure. In addition, those skilled in the art will appreciate that the mechanisms of the subject matter described herein are capable of being distributed as a program product in a variety of forms, and that an illustrative form of the subject matter described herein applies regardless of the particular type of signal bearing medium used to actually carry out the distribution. Examples of a signal bearing medium include, but are not limited to, the following: a recordable type medium such as a floppy disk, a hard disk drive, a Compact Disc (CD), a Digital Video Disk (DVD), a digital tape, a computer memory, etc.; and a transmission type medium such as a digital and/or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link (e.g., transmitter, receiver, transmission logic, reception logic, etc.), etc.).

All of the above-mentioned U.S. patents, U.S. patent application publications, U.S. patent applications, foreign patents, foreign patent applications, non-patent publications referred to in this specification and/or listed in any Application Data Sheet, or any other disclosure material are incorporated herein by reference, to the extent not inconsistent herewith. As such, and to the extent necessary, the disclosure as explicitly set forth herein supersedes any conflicting material incorporated herein by reference. Any material, or portion thereof, that is said to be incorporated by reference herein, but which conflicts with existing definitions, statements, or other disclosure material set forth herein will only be incorporated to the extent that no conflict arises between that incorporated material and the existing disclosure material.

One skilled in the art will recognize that the herein described components (e.g., operations), devices, objects, and the discussion accompanying them are used as examples for the sake of conceptual clarity and that various configuration modifications are contemplated. Consequently, as used herein, the specific exemplars set forth and the accompanying discussion are intended to be representative of their more general classes. In general, use of any specific exemplar is intended to be representative of its class, and the non-inclusion of specific components (e.g., operations), devices, and objects should not be taken limiting.

Wth respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations are not expressly set forth herein for sake of clarity.

The herein described subject matter sometimes illustrates different components contained within, or connected with, different other components. It is to be understood that such depicted architectures are merely example, and that in fact many other architectures may be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively “associated” such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality can be seen as “associated with” each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated also can be viewed as being “operably connected,” or “operably coupled,” to each other to achieve the desired functionality, and any two components capable of being so associated also can be viewed as being “operably couplable,” to each other to achieve the desired functionality. Specific examples of operably couplable include but are not limited to physically mateable and/or physically interacting components, and/or wirelessly interactable, and/or wirelessly interacting components, and/or logically interacting, and/or logically interactable components.

In some instances, one or more components may be referred to herein as “configured to,” “configurable to,” “operable/operative to,” “adapted/adaptable,” “able to,” “conformable/conformed to,” etc. Those skilled in the art will recognize that “configured to” can generally encompass active-state components and/or inactive-state components and/or standby-state components, unless context requires otherwise.

While particular aspects of the present subject matter described herein have been shown and described, it will be apparent to those skilled in the art that, based upon the teachings herein, changes and modifications may be made without departing from the subject matter described herein and its broader aspects and, therefore, the appended claims are to encompass within their scope all such changes and modifications as are within the true spirit and scope of the subject matter described herein. It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as “open” terms (e.g., the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases “at least one” and “one or more” to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim recitation to claims containing only one such recitation, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an” (e.g., “a” and/or “an” should typically be interpreted to mean “at least one” or “one or more”); the same holds true for the use of definite articles used to introduce claim recitations.

In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should typically be interpreted to mean at least the recited number (e.g., the bare recitation of “two recitations,” without other modifiers, typically means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to “at least one of A, B, or C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that typically a disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms unless context dictates otherwise. For example, the phrase “A or B” will be typically understood to include the possibilities of “A” or “B” or “A and B.”

Wth respect to the appended claims, those skilled in the art will appreciate that recited operations therein may generally be performed in any order. Also, although various operational flows are presented in a sequence(s), it should be understood that the various operations may be performed in other orders than those which are illustrated, or may be performed concurrently. Examples of such alternate orderings may include overlapping, interleaved, interrupted, reordered, incremental, preparatory, supplemental, simultaneous, reverse, or other variant orderings, unless context dictates otherwise. Furthermore, terms like “responsive to,” “related to,” or other past-tense adjectives are generally not intended to exclude such variants, unless context dictates otherwise.

In summary, numerous benefits have been described which result from employing the concepts described herein. The foregoing description of the one or more forms has been presented for purposes of illustration and description. It is not intended to be exhaustive or limiting to the precise form disclosed. Modifications or variations are possible in light of the above teachings. The one or more forms were chosen and described in order to illustrate principles and practical application to thereby enable one of ordinary skill in the art to utilize the various forms and with various modifications as are suited to the particular use contemplated. It is intended that the claims submitted herewith define the overall scope.

Claims

1. A method comprising: applying a force to tissue using an end effector of a surgical instrument;measuring, by a processor, the force applied to the tissue;comparing, by the processor, the measured force to a threshold minimum force value;determining, by the processor, that the measured force satisfies the threshold minimum force value;measuring, by the processor, a value of power by the end effector when the end effector applies the force to the tissue;computing, by the processor, a coefficient of determination value using the value of power and the measured force;determining, by the processor, a coefficient of friction of the tissue using the coefficient of determination value;determining, by the processor, a type of tissue by comparing the determined coefficient of friction to a database relating stored coefficients of friction to predetermined types of tissue; andselecting, by the processor, a power delivery profile for delivering energy from a generator to the end effector that is suitable for performing a surgical operation on the determined type of tissue; anddelivering the energy having the selected power delivery profile from the generator to perform the surgical operation on the determined type of tissue.
2. The method of claim 1, wherein determining the coefficient of friction of the tissue comprises: wherein applying a force to the tissue comprises applying and measuring a plurality of forces to the tissue, each at different values, using the end effector;measuring, by the processor, for each of the plurality of forces, a respective value of power; andcomputing, by the processor, for each pair of the plurality of forces and respective values of power, a slope value using said pair.
3. The method of claim 2, wherein determining the coefficient of friction of the tissue further comprises: determining, by the processor, a respective coefficient of determination for each of the slope values.
4. The method of claim 3, wherein determining the coefficient of friction of the tissue further comprises: determining, by the processor, a best fit slope value among each of the slope values that corresponds to the highest coefficient of determination among the respective coefficients of determination.
5. The method of claim 4, wherein determining the coefficient of friction of the tissue further comprises: determining that the highest coefficient of determination satisfies a predetermined threshold; andbased on the determination that the predetermined threshold is satisfied, computing the coefficient of friction using the best fit slope value.
6. The method of claim 1, further comprising dynamically changing the power delivery profile based on determining a change in the tissue coefficient of friction of the tissue.
7. The method of claim 1, further comprising entering a learning mode to improve accuracy of determining the coefficient of friction.
8. A method comprising: applying a force to tissue using an end effector of a surgical instrument;measuring, by a processor, the force applied to the tissue;comparing, by the processor, the measured force to a threshold minimum force value;determining, by the processor, that the measured force satisfies the threshold minimum force value;measuring, by the processor, a value of power by the end effector when the end effector applies the force to the tissue;computing, by the processor, a coefficient of determination value using the value of power and the measured force;determining, by the processor, a coefficient of friction of the tissue using the coefficient of determination value;determining, by the processor, a type of tissue by comparing the determined coefficient of friction to a database relating stored coefficients of friction to predetermined types of tissue, the predetermined types of tissue including porcine carotid with a coefficient of friction of 0.30, porcine carotid with a coefficient of friction of 0.35, porcine bowel with a coefficient of friction of 0.19, and dry chamois with a coefficient of friction of 0.75; andselecting, by the processor, a power delivery profile for delivering energy from a generator to the end effector that is suitable for performing a surgical operation on the determined type of tissue; anddelivering the energy having the selected power delivery profile from the generator to perform the surgical operation on the determined type of tissue.
9. The method of claim 8, wherein determining the coefficient of friction of the tissue comprises: wherein applying a force to the tissues comprises applying and measuring a plurality of forces to the tissue, each at different values, using the end effector;measuring, by the processor, for each of the plurality of forces, a respective value of power; andcomputing, by the processor, for each pair of the plurality of forces and respective values of power, a slope value using said pair.
10. The method of claim 9, wherein determining the coefficient of friction of the tissue further comprises: determining, by the processor, a respective coefficient of determination for each of the slope values.
11. The method of claim 10, wherein determining the coefficient of friction of the tissue further comprises: determining, by the processor, a best fit slope value among each of the slope values that corresponds to a highest coefficient of determination among the respective coefficients of determination.
12. The method of claim 11, wherein determining the coefficient of friction of the tissue further comprises: determining that the highest coefficient of determination satisfies a predetermined threshold; andbased on the determination that the predetermined threshold is satisfied, computing the coefficient of friction using the best fit slope value.
13. The method of claim 8, further comprising dynamically changing the power delivery profile based on determining a change in the coefficient of friction of the tissue.
14. The method of claim 8, further comprising entering a learning mode to improve accuracy of determining the coefficient of friction.
15. A method comprising: applying a force to tissue using an end effector of a surgical instrument;measuring, by a processor, the force applied to the tissue;comparing, by the processor, the measured force to a threshold minimum force value;measuring, by the processor, a value of power by the end effector when the end effector applies the force to the tissue;computing, by the processor, a coefficient of determination value using the value of power and the measured force;determining, by the processor, a coefficient of friction of the tissue using the coefficient of determination value;determining, by the processor, a type of tissue by comparing the determined coefficient of friction to a database relating stored coefficients of friction to predetermined types of tissue; andselecting, by the processor, a power delivery profile for delivering energy from a generator to the end effector that is suitable for performing a surgical operation on the determined type of tissue; anddelivering the energy having the selected power delivery profile from the generator to perform the surgical operation on the determined type of tissue.
16. The method of claim 15, wherein determining the coefficient of friction of the tissue comprises: wherein applying a force to the tissue comprises applying and measuring a plurality of forces to the tissue, each at different values, using the end effector;measuring, by the processor, for each of the plurality of forces, a respective value of power; andcomputing, by the processor, for each pair of the plurality of forces and respective values of power, a slope value using said pair.
17. The method of claim 16, wherein determining the coefficient of friction of the tissue further comprises: determining, by the processor, a respective coefficient of determination for each of the slope values.
18. The method of claim 17, wherein determining the coefficient of friction of the tissue further comprises: determining, by the processor, a best fit slope value among each of the slope values that corresponds to the highest coefficient of determination among the respective coefficients of determination.
19. The method of claim 18, wherein determining the coefficient of friction of the tissue further comprises: determining that the highest coefficient of determination satisfies a predetermined threshold; andbased on the determination that the predetermined threshold is satisfied, computing the coefficient of friction using the best fit slope value.
20. The method of claim 15, further comprising entering a learning mode to improve accuracy of determining the coefficient of friction.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application claiming priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 15/177,430, now U.S. Pat. No. 11,141,213, entitled STEPPED STAPLE CARTRIDGE WITH ASYMMETRICAL STAPLES, filed Jun. 9, 2016, which application claims the benefit of U.S. Provisional Application Ser. No. 62/186,984 filed Jun. 30, 2015, U.S. Provisional Application Ser. No. 62/235,260, filed Sep. 30, 2015, U.S. Provisional Application Ser. No. 62/235,368, filed Sep. 30, 2015, U.S. Provisional Application Ser. No. 62/235,466, filed Sep. 30, 2015, U.S. Provisional Application Ser. No. 62/279,635, filed Jan. 15, 2016, and U.S. Provisional Application Ser. No. 62/330,669, filed May 2, 2016, the contents of which are incorporated herein by reference in their entirety.

US Referenced Citations (2722)

Number	Name	Date	Kind
969528	Disbrow	Sep 1910	A
1570025	Young	Jan 1926	A
1813902	Bovie	Jul 1931	A
2188497	Calva	Jan 1940	A
2366274	Luth et al.	Jan 1945	A
2425245	Johnson	Aug 1947	A
2442966	Wallace	Jun 1948	A
2458152	Eakins	Jan 1949	A
2510693	Green	Jun 1950	A
2597564	Bugg	May 1952	A
2704333	Calosi et al.	Mar 1955	A
2736960	Armstrong	Mar 1956	A
2748967	Roach	Jun 1956	A
2845072	Shafer	Jul 1958	A
2849788	Creek	Sep 1958	A
2867039	Zach	Jan 1959	A
2874470	Richards	Feb 1959	A
2990616	Balamuth et al.	Jul 1961	A
RE25033	Balamuth et al.	Aug 1961	E
3015961	Roney	Jan 1962	A
3033407	Alfons	May 1962	A
3053124	Balamuth et al.	Sep 1962	A
3082805	Royce	Mar 1963	A
3166971	Stoecker	Jan 1965	A
3322403	Murphy	May 1967	A
3432691	Shoh	Mar 1969	A
3433226	Boyd	Mar 1969	A
3489930	Shoh	Jan 1970	A
3513848	Winston et al.	May 1970	A
3514856	Camp et al.	Jun 1970	A
3525912	Wallin	Aug 1970	A
3526219	Balamuth	Sep 1970	A
3554198	Tatoian et al.	Jan 1971	A
3580841	Cadotte et al.	May 1971	A
3606682	Camp et al.	Sep 1971	A
3614484	Shoh	Oct 1971	A
3616375	Inoue	Oct 1971	A
3629726	Popescu	Dec 1971	A
3636943	Balamuth	Jan 1972	A
3668486	Silver	Jun 1972	A
3702948	Balamuth	Nov 1972	A
3703651	Blowers	Nov 1972	A
3776238	Peyman et al.	Dec 1973	A
3777760	Essner	Dec 1973	A
3805787	Banko	Apr 1974	A
3809977	Balamuth et al.	May 1974	A
3830098	Antonevich	Aug 1974	A
3854737	Gilliam, Sr.	Dec 1974	A
3862630	Balamuth	Jan 1975	A
3875945	Friedman	Apr 1975	A
3885438	Harris, Sr. et al.	May 1975	A
3900823	Sokal et al.	Aug 1975	A
3918442	Nikolaev et al.	Nov 1975	A
3924335	Balamuth et al.	Dec 1975	A
3946738	Newton et al.	Mar 1976	A
3955859	Stella et al.	May 1976	A
3956826	Perdreaux, Jr.	May 1976	A
3989952	Hohmann	Nov 1976	A
4005714	Hiltebrandt	Feb 1977	A
4012647	Balamuth et al.	Mar 1977	A
4034762	Cosens et al.	Jul 1977	A
4058126	Leveen	Nov 1977	A
4074719	Semm	Feb 1978	A
4156187	Murry et al.	May 1979	A
4167944	Banko	Sep 1979	A
4188927	Harris	Feb 1980	A
4200106	Douvas et al.	Apr 1980	A
4203430	Takahashi	May 1980	A
4203444	Bonnell et al.	May 1980	A
4220154	Semm	Sep 1980	A
4237441	van Konynenburg et al.	Dec 1980	A
4244371	Farin	Jan 1981	A
4281785	Brooks	Aug 1981	A
4300083	Heiges	Nov 1981	A
4302728	Nakamura	Nov 1981	A
4304987	van Konynenburg	Dec 1981	A
4306570	Matthews	Dec 1981	A
4314559	Allen	Feb 1982	A
4353371	Cosman	Oct 1982	A
4409981	Lundberg	Oct 1983	A
4445063	Smith	Apr 1984	A
4461304	Kuperstein	Jul 1984	A
4463759	Garito et al.	Aug 1984	A
4491132	Aikins	Jan 1985	A
4492231	Auth	Jan 1985	A
4494759	Kieffer	Jan 1985	A
4504264	Kelman	Mar 1985	A
4512344	Barber	Apr 1985	A
4526571	Wuchinich	Jul 1985	A
4535773	Yoon	Aug 1985	A
4541638	Ogawa et al.	Sep 1985	A
4545374	Jacobson	Oct 1985	A
4545926	Fouts, Jr. et al.	Oct 1985	A
4549147	Kondo	Oct 1985	A
4550870	Krumme et al.	Nov 1985	A
4553544	Nomoto et al.	Nov 1985	A
4562838	Walker	Jan 1986	A
4574615	Bower et al.	Mar 1986	A
4582236	Hirose	Apr 1986	A
4593691	Lindstrom et al.	Jun 1986	A
4608981	Rothfuss et al.	Sep 1986	A
4617927	Manes	Oct 1986	A
4633119	Thompson	Dec 1986	A
4633874	Chow et al.	Jan 1987	A
4634420	Spinosa et al.	Jan 1987	A
4640279	Beard	Feb 1987	A
4641053	Takeda	Feb 1987	A
4646738	Trott	Mar 1987	A
4646756	Watmough et al.	Mar 1987	A
4649919	Thimsen et al.	Mar 1987	A
4662068	Polonsky	May 1987	A
4674502	Imonti	Jun 1987	A
4694835	Strand	Sep 1987	A
4708127	Abdelghani	Nov 1987	A
4712722	Hood et al.	Dec 1987	A
4735603	Goodson et al.	Apr 1988	A
4761871	O'Connor et al.	Aug 1988	A
4808154	Freeman	Feb 1989	A
4819635	Shapiro	Apr 1989	A
4827911	Broadwin et al.	May 1989	A
4830462	Karny et al.	May 1989	A
4832683	Idemoto et al.	May 1989	A
4836186	Scholz	Jun 1989	A
4838853	Parisi	Jun 1989	A
4844064	Thimsen et al.	Jul 1989	A
4849133	Yoshida et al.	Jul 1989	A
4850354	McGurk-Burleson et al.	Jul 1989	A
4852578	Companion et al.	Aug 1989	A
4860745	Farin et al.	Aug 1989	A
4862890	Stasz et al.	Sep 1989	A
4865159	Jamison	Sep 1989	A
4867157	McGurk-Burleson et al.	Sep 1989	A
4878493	Pasternak et al.	Nov 1989	A
4880015	Nierman	Nov 1989	A
4881550	Kothe	Nov 1989	A
4896009	Pawlowski	Jan 1990	A
4903696	Stasz et al.	Feb 1990	A
4910389	Sherman et al.	Mar 1990	A
4915643	Samejima et al.	Apr 1990	A
4920978	Colvin	May 1990	A
4922902	Wuchinich et al.	May 1990	A
4926860	Stice et al.	May 1990	A
4936842	D'Amelio et al.	Jun 1990	A
4954960	Lo et al.	Sep 1990	A
4965532	Sakurai	Oct 1990	A
4979952	Kubota et al.	Dec 1990	A
4981756	Rhandhawa	Jan 1991	A
5001649	Lo et al.	Mar 1991	A
5009661	Michelson	Apr 1991	A
5013956	Kurozumi et al.	May 1991	A
5015227	Broadwin et al.	May 1991	A
5020514	Heckele	Jun 1991	A
5026370	Lottick	Jun 1991	A
5026387	Thomas	Jun 1991	A
5035695	Weber, Jr. et al.	Jul 1991	A
5042461	Inoue et al.	Aug 1991	A
5042707	Taheri	Aug 1991	A
5052145	Wang	Oct 1991	A
5061269	Muller	Oct 1991	A
5075839	Fisher et al.	Dec 1991	A
5084052	Jacobs	Jan 1992	A
5099840	Goble et al.	Mar 1992	A
5104025	Main et al.	Apr 1992	A
5105117	Yamaguchi	Apr 1992	A
5106538	Barma et al.	Apr 1992	A
5108383	White	Apr 1992	A
5109819	Custer et al.	May 1992	A
5112300	Ureche	May 1992	A
5113139	Furukawa	May 1992	A
5123903	Quaid et al.	Jun 1992	A
5126618	Takahashi et al.	Jun 1992	A
D327872	McMills et al.	Jul 1992	S
5152762	McElhenney	Oct 1992	A
5156633	Smith	Oct 1992	A
5160334	Billings et al.	Nov 1992	A
5162044	Gahn et al.	Nov 1992	A
5163421	Bernstein et al.	Nov 1992	A
5163537	Radev	Nov 1992	A
5163945	Ortiz et al.	Nov 1992	A
5167619	Wuchinich	Dec 1992	A
5167725	Clark et al.	Dec 1992	A
5172344	Ehrlich	Dec 1992	A
5174276	Crockard	Dec 1992	A
D332660	Rawson et al.	Jan 1993	S
5176677	Wuchinich	Jan 1993	A
5176695	Dulebohn	Jan 1993	A
5184605	Grzeszykowski	Feb 1993	A
5188102	Idemoto et al.	Feb 1993	A
D334173	Liu et al.	Mar 1993	S
5190517	Zieve et al.	Mar 1993	A
5190518	Takasu	Mar 1993	A
5190541	Abele et al.	Mar 1993	A
5196007	Ellman et al.	Mar 1993	A
5205459	Brinkerhoff et al.	Apr 1993	A
5205817	Idemoto et al.	Apr 1993	A
5209719	Baruch et al.	May 1993	A
5213569	Davis	May 1993	A
5214339	Naito	May 1993	A
5217460	Knoepfler	Jun 1993	A
5218529	Meyer et al.	Jun 1993	A
5221282	Wuchinich	Jun 1993	A
5222937	Kagawa	Jun 1993	A
5226909	Evans et al.	Jul 1993	A
5226910	Kajiyama et al.	Jul 1993	A
5231989	Middleman et al.	Aug 1993	A
5234428	Kaufman	Aug 1993	A
5241236	Sasaki et al.	Aug 1993	A
5241968	Slater	Sep 1993	A
5242339	Thornton	Sep 1993	A
5242460	Klein et al.	Sep 1993	A
5246003	DeLonzor	Sep 1993	A
5254129	Alexander	Oct 1993	A
5257988	L'Esperance, Jr.	Nov 1993	A
5258004	Bales et al.	Nov 1993	A
5258006	Rydell et al.	Nov 1993	A
5261922	Hood	Nov 1993	A
5263957	Davison	Nov 1993	A
5264925	Shipp et al.	Nov 1993	A
5269297	Weng et al.	Dec 1993	A
5275166	Vaitekunas et al.	Jan 1994	A
5275607	Lo et al.	Jan 1994	A
5275609	Pingleton et al.	Jan 1994	A
5282800	Foshee et al.	Feb 1994	A
5282817	Hoogeboom et al.	Feb 1994	A
5285795	Ryan et al.	Feb 1994	A
5285945	Brinkerhoff et al.	Feb 1994	A
5290286	Parins	Mar 1994	A
5293863	Zhu et al.	Mar 1994	A
5300068	Rosar et al.	Apr 1994	A
5304115	Pflueger et al.	Apr 1994	A
D347474	Olson	May 1994	S
5307976	Olson et al.	May 1994	A
5309927	Welch	May 1994	A
5312023	Green et al.	May 1994	A
5312425	Evans et al.	May 1994	A
5318525	West et al.	Jun 1994	A
5318563	Malis et al.	Jun 1994	A
5318564	Eggers	Jun 1994	A
5318570	Hood et al.	Jun 1994	A
5318589	Lichtman	Jun 1994	A
5322055	Davison et al.	Jun 1994	A
5324299	Davison et al.	Jun 1994	A
5326013	Green et al.	Jul 1994	A
5326342	Pflueger et al.	Jul 1994	A
5330471	Eggers	Jul 1994	A
5330502	Hassler et al.	Jul 1994	A
5334183	Wuchinich	Aug 1994	A
5339723	Huitema	Aug 1994	A
5342356	Ellman et al.	Aug 1994	A
5342359	Rydell	Aug 1994	A
5344420	Hilal et al.	Sep 1994	A
5345937	Middleman et al.	Sep 1994	A
5346502	Estabrook et al.	Sep 1994	A
5353474	Good et al.	Oct 1994	A
5357164	Imabayashi et al.	Oct 1994	A
5357423	Weaver et al.	Oct 1994	A
5359994	Krauter et al.	Nov 1994	A
5361583	Huitema	Nov 1994	A
5366466	Christian et al.	Nov 1994	A
5368557	Nita et al.	Nov 1994	A
5370645	Klicek et al.	Dec 1994	A
5371429	Manna	Dec 1994	A
5374813	Shipp	Dec 1994	A
D354564	Medema	Jan 1995	S
5381067	Greenstein et al.	Jan 1995	A
5383874	Jackson et al.	Jan 1995	A
5383917	Desai et al.	Jan 1995	A
5387207	Dyer et al.	Feb 1995	A
5387215	Fisher	Feb 1995	A
5389098	Tsuruta et al.	Feb 1995	A
5394187	Shipp	Feb 1995	A
5395033	Byrne et al.	Mar 1995	A
5395312	Desai	Mar 1995	A
5395363	Billings et al.	Mar 1995	A
5395364	Anderhub et al.	Mar 1995	A
5396266	Brimhall	Mar 1995	A
5396900	Slater et al.	Mar 1995	A
5400267	Denen et al.	Mar 1995	A
5403312	Yates et al.	Apr 1995	A
5403334	Evans et al.	Apr 1995	A
5406503	Williams, Jr. et al.	Apr 1995	A
5408268	Shipp	Apr 1995	A
D358887	Feinberg	May 1995	S
5411481	Allen et al.	May 1995	A
5417709	Slater	May 1995	A
5419761	Narayanan et al.	May 1995	A
5421829	Olichney et al.	Jun 1995	A
5423844	Miller	Jun 1995	A
5428504	Bhatla	Jun 1995	A
5429131	Scheinman et al.	Jul 1995	A
5438997	Sieben et al.	Aug 1995	A
5441499	Fritzsch	Aug 1995	A
5443463	Stern et al.	Aug 1995	A
5445638	Rydell et al.	Aug 1995	A
5445639	Kuslich et al.	Aug 1995	A
5447509	Mills et al.	Sep 1995	A
5449370	Vaitekunas	Sep 1995	A
5451053	Garrido	Sep 1995	A
5451161	Sharp	Sep 1995	A
5451220	Ciervo	Sep 1995	A
5451227	Michaelson	Sep 1995	A
5456684	Schmidt et al.	Oct 1995	A
5458598	Feinberg et al.	Oct 1995	A
5462604	Shibano et al.	Oct 1995	A
5465895	Knodel et al.	Nov 1995	A
5471988	Fujio et al.	Dec 1995	A
5472443	Cordis et al.	Dec 1995	A
5476479	Green et al.	Dec 1995	A
5478003	Green et al.	Dec 1995	A
5480409	Riza	Jan 1996	A
5483501	Park et al.	Jan 1996	A
5484436	Eggers et al.	Jan 1996	A
5486162	Brumbach	Jan 1996	A
5486189	Mudry et al.	Jan 1996	A
5490860	Middle et al.	Feb 1996	A
5496317	Goble et al.	Mar 1996	A
5499992	Meade et al.	Mar 1996	A
5500216	Julian et al.	Mar 1996	A
5501654	Failla et al.	Mar 1996	A
5504650	Katsui et al.	Apr 1996	A
5505693	Mackool	Apr 1996	A
5507297	Slater et al.	Apr 1996	A
5507738	Ciervo	Apr 1996	A
5509922	Aranyi et al.	Apr 1996	A
5511556	DeSantis	Apr 1996	A
5520704	Castro et al.	May 1996	A
5522832	Kugo et al.	Jun 1996	A
5522839	Pilling	Jun 1996	A
5527331	Kresch et al.	Jun 1996	A
5531744	Nardella et al.	Jul 1996	A
5540681	Strul et al.	Jul 1996	A
5540693	Fisher	Jul 1996	A
5542916	Hirsch et al.	Aug 1996	A
5548286	Craven	Aug 1996	A
5549637	Crainich	Aug 1996	A
5553675	Pitzen et al.	Sep 1996	A
5558671	Yates	Sep 1996	A
5562609	Brumbach	Oct 1996	A
5562610	Brumbach	Oct 1996	A
5562659	Morris	Oct 1996	A
5562703	Desai	Oct 1996	A
5563179	Stone et al.	Oct 1996	A
5569164	Lurz	Oct 1996	A
5571121	Heifetz	Nov 1996	A
5573424	Poppe	Nov 1996	A
5573533	Strul	Nov 1996	A
5573534	Stone	Nov 1996	A
5577654	Bishop	Nov 1996	A
5584830	Ladd et al.	Dec 1996	A
5591187	Dekel	Jan 1997	A
5593414	Shipp et al.	Jan 1997	A
5599350	Schulze et al.	Feb 1997	A
5600526	Russell et al.	Feb 1997	A
5601601	Tal et al.	Feb 1997	A
5603773	Campbell	Feb 1997	A
5607436	Pratt et al.	Mar 1997	A
5607450	Zvenyatsky et al.	Mar 1997	A
5609573	Sandock	Mar 1997	A
5611813	Lichtman	Mar 1997	A
5618304	Hart et al.	Apr 1997	A
5618307	Donlon et al.	Apr 1997	A
5618492	Auten et al.	Apr 1997	A
5620447	Smith et al.	Apr 1997	A
5624452	Yates	Apr 1997	A
5626587	Bishop et al.	May 1997	A
5626595	Sklar et al.	May 1997	A
5626608	Cuny et al.	May 1997	A
5628760	Knoepfler	May 1997	A
5630420	Vaitekunas	May 1997	A
5632432	Schulze et al.	May 1997	A
5632717	Yoon	May 1997	A
5640741	Yano	Jun 1997	A
D381077	Hunt	Jul 1997	S
5647871	Levine et al.	Jul 1997	A
5649937	Bito et al.	Jul 1997	A
5649955	Hashimoto et al.	Jul 1997	A
5651780	Jackson et al.	Jul 1997	A
5653713	Michelson	Aug 1997	A
5655100	Ebrahim et al.	Aug 1997	A
5658281	Heard	Aug 1997	A
5662662	Bishop et al.	Sep 1997	A
5662667	Knodel	Sep 1997	A
5665085	Nardella	Sep 1997	A
5665100	Yoon	Sep 1997	A
5669922	Hood	Sep 1997	A
5674219	Monson et al.	Oct 1997	A
5674220	Fox et al.	Oct 1997	A
5674235	Parisi	Oct 1997	A
5678568	Uchikubo et al.	Oct 1997	A
5688270	Yates et al.	Nov 1997	A
5690269	Bolanos et al.	Nov 1997	A
5693051	Schulze et al.	Dec 1997	A
5694936	Fujimoto et al.	Dec 1997	A
5695510	Hood	Dec 1997	A
5700261	Brinkerhoff	Dec 1997	A
5704534	Huitema et al.	Jan 1998	A
5704791	Gillio	Jan 1998	A
5707369	Vaitekunas et al.	Jan 1998	A
5709680	Yates et al.	Jan 1998	A
5711472	Bryan	Jan 1998	A
5713896	Nardella	Feb 1998	A
5715817	Stevens-Wright et al.	Feb 1998	A
5716366	Yates	Feb 1998	A
5717306	Shipp	Feb 1998	A
5720742	Zacharias	Feb 1998	A
5720744	Eggleston et al.	Feb 1998	A
5722980	Schulz et al.	Mar 1998	A
5723970	Bell	Mar 1998	A
5728130	Ishikawa et al.	Mar 1998	A
5730752	Alden et al.	Mar 1998	A
5733074	Stock et al.	Mar 1998	A
5735848	Yates et al.	Apr 1998	A
5741226	Strukel et al.	Apr 1998	A
5743906	Parins et al.	Apr 1998	A
5752973	Kieturakis	May 1998	A
5755717	Yates et al.	May 1998	A
5762255	Chrisman et al.	Jun 1998	A
5766164	Mueller et al.	Jun 1998	A
5772659	Becker et al.	Jun 1998	A
5776130	Buysse et al.	Jul 1998	A
5776155	Beaupre et al.	Jul 1998	A
5779130	Alesi et al.	Jul 1998	A
5779701	McBrayer et al.	Jul 1998	A
5782834	Lucey et al.	Jul 1998	A
5792135	Madhani et al.	Aug 1998	A
5792138	Shipp	Aug 1998	A
5792165	Klieman et al.	Aug 1998	A
5796188	Bays	Aug 1998	A
5797941	Schulze et al.	Aug 1998	A
5797958	Yoon	Aug 1998	A
5797959	Castro et al.	Aug 1998	A
5800432	Swanson	Sep 1998	A
5800448	Banko	Sep 1998	A
5800449	Wales	Sep 1998	A
5805140	Rosenberg et al.	Sep 1998	A
5807393	Williamson, IV et al.	Sep 1998	A
5808396	Boukhny	Sep 1998	A
5810811	Yates et al.	Sep 1998	A
5810828	Lightman et al.	Sep 1998	A
5810859	DiMatteo et al.	Sep 1998	A
5817033	DeSantis et al.	Oct 1998	A
5817084	Jensen	Oct 1998	A
5817093	Williamson, IV et al.	Oct 1998	A
5817119	Klieman et al.	Oct 1998	A
5823197	Edwards	Oct 1998	A
5827271	Buysse et al.	Oct 1998	A
5827323	Klieman et al.	Oct 1998	A
5828160	Sugishita	Oct 1998	A
5833696	Whitfield et al.	Nov 1998	A
5836897	Sakurai et al.	Nov 1998	A
5836909	Cosmescu	Nov 1998	A
5836943	Miller, III	Nov 1998	A
5836957	Schulz et al.	Nov 1998	A
5836990	Li	Nov 1998	A
5843109	Mehta et al.	Dec 1998	A
5851212	Zirps et al.	Dec 1998	A
5853412	Mayenberger	Dec 1998	A
5854590	Dalstein	Dec 1998	A
5858018	Shipp et al.	Jan 1999	A
5865361	Milliman et al.	Feb 1999	A
5873873	Smith et al.	Feb 1999	A
5873882	Straub et al.	Feb 1999	A
5876401	Schulze et al.	Mar 1999	A
5878193	Wang et al.	Mar 1999	A
5879364	Bromfield et al.	Mar 1999	A
5880668	Hall	Mar 1999	A
5883615	Fago et al.	Mar 1999	A
5891142	Eggers et al.	Apr 1999	A
5893835	Witt et al.	Apr 1999	A
5897523	Wright et al.	Apr 1999	A
5897569	Kellogg et al.	Apr 1999	A
5903607	Tailliet	May 1999	A
5904681	West, Jr.	May 1999	A
5906625	Bito et al.	May 1999	A
5906627	Spaulding	May 1999	A
5906628	Miyawaki et al.	May 1999	A
5910129	Koblish et al.	Jun 1999	A
5911699	Anis et al.	Jun 1999	A
5913823	Hedberg et al.	Jun 1999	A
5916229	Evans	Jun 1999	A
5921956	Grinberg et al.	Jul 1999	A
5929846	Rosenberg et al.	Jul 1999	A
5935143	Hood	Aug 1999	A
5935144	Estabrook	Aug 1999	A
5938633	Beaupre	Aug 1999	A
5944718	Austin et al.	Aug 1999	A
5944737	Tsonton et al.	Aug 1999	A
5947984	Whipple	Sep 1999	A
5954717	Behl et al.	Sep 1999	A
5954736	Bishop et al.	Sep 1999	A
5954746	Holthaus et al.	Sep 1999	A
5957882	Nita et al.	Sep 1999	A
5957943	Vaitekunas	Sep 1999	A
5968007	Simon et al.	Oct 1999	A
5968060	Kellogg	Oct 1999	A
5974342	Petrofsky	Oct 1999	A
D416089	Barton et al.	Nov 1999	S
5980510	Tsonton et al.	Nov 1999	A
5980546	Hood	Nov 1999	A
5984938	Yoon	Nov 1999	A
5987344	West	Nov 1999	A
5989274	Davison et al.	Nov 1999	A
5989275	Estabrook et al.	Nov 1999	A
5993465	Shipp et al.	Nov 1999	A
5993972	Reich et al.	Nov 1999	A
5994855	Lundell et al.	Nov 1999	A
6003517	Sheffield et al.	Dec 1999	A
6004335	Vaitekunas et al.	Dec 1999	A
6013052	Durman et al.	Jan 2000	A
6024741	Williamson, IV et al.	Feb 2000	A
6024744	Kese et al.	Feb 2000	A
6024750	Mastri et al.	Feb 2000	A
6027515	Cimino	Feb 2000	A
6031526	Shipp	Feb 2000	A
6033375	Brumbach	Mar 2000	A
6033399	Gines	Mar 2000	A
6036667	Manna et al.	Mar 2000	A
6036707	Spaulding	Mar 2000	A
6039734	Goble	Mar 2000	A
6048224	Kay	Apr 2000	A
6050943	Slayton et al.	Apr 2000	A
6050996	Schmaltz et al.	Apr 2000	A
6051010	DiMatteo et al.	Apr 2000	A
6056735	Okada et al.	May 2000	A
6063098	Houser et al.	May 2000	A
6066132	Chen et al.	May 2000	A
6066151	Miyawaki et al.	May 2000	A
6068627	Orszulak et al.	May 2000	A
6068629	Haissaguerre et al.	May 2000	A
6068647	Witt et al.	May 2000	A
6074389	Levine et al.	Jun 2000	A
6077285	Boukhny	Jun 2000	A
6080149	Huang et al.	Jun 2000	A
6083191	Rose	Jul 2000	A
6086584	Miller	Jul 2000	A
6090120	Wright et al.	Jul 2000	A
6091995	Ingle et al.	Jul 2000	A
6096033	Tu et al.	Aug 2000	A
6099483	Palmer et al.	Aug 2000	A
6099542	Cohn et al.	Aug 2000	A
6099550	Yoon	Aug 2000	A
6109500	Alli et al.	Aug 2000	A
6110127	Suzuki	Aug 2000	A
6113594	Savage	Sep 2000	A
6113598	Baker	Sep 2000	A
6117152	Huitema	Sep 2000	A
H1904	Yates et al.	Oct 2000	H
6126629	Perkins	Oct 2000	A
6126658	Baker	Oct 2000	A
6129735	Okada et al.	Oct 2000	A
6129740	Michelson	Oct 2000	A
6132368	Cooper	Oct 2000	A
6132427	Jones et al.	Oct 2000	A
6132429	Baker	Oct 2000	A
6132448	Perez et al.	Oct 2000	A
6139320	Hahn	Oct 2000	A
6139561	Shibata et al.	Oct 2000	A
6142615	Qiu et al.	Nov 2000	A
6142994	Swanson et al.	Nov 2000	A
6144402	Norsworthy et al.	Nov 2000	A
6147560	Erhage et al.	Nov 2000	A
6152902	Christian et al.	Nov 2000	A
6152923	Ryan	Nov 2000	A
6154198	Rosenberg	Nov 2000	A
6156029	Mueller	Dec 2000	A
6159160	Hsei et al.	Dec 2000	A
6159175	Strukel et al.	Dec 2000	A
6162194	Shipp	Dec 2000	A
6162208	Hipps	Dec 2000	A
6165150	Banko	Dec 2000	A
6174309	Wrublewski et al.	Jan 2001	B1
6174310	Kirwan, Jr.	Jan 2001	B1
6176857	Ashley	Jan 2001	B1
6179853	Sachse et al.	Jan 2001	B1
6183426	Akisada et al.	Feb 2001	B1
6187003	Buysse et al.	Feb 2001	B1
6190386	Rydell	Feb 2001	B1
6193709	Miyawaki et al.	Feb 2001	B1
6204592	Hur	Mar 2001	B1
6205383	Hermann	Mar 2001	B1
6205855	Pfeiffer	Mar 2001	B1
6206844	Reichel et al.	Mar 2001	B1
6206876	Levine et al.	Mar 2001	B1
6210337	Dunham et al.	Apr 2001	B1
6210402	Olsen et al.	Apr 2001	B1
6210403	Klicek	Apr 2001	B1
6214023	Whipple et al.	Apr 2001	B1
6228080	Gines	May 2001	B1
6231565	Tovey et al.	May 2001	B1
6232899	Craven	May 2001	B1
6233476	Strommer et al.	May 2001	B1
6238366	Savage et al.	May 2001	B1
6241724	Fleischman et al.	Jun 2001	B1
6245065	Panescu et al.	Jun 2001	B1
6251110	Wampler	Jun 2001	B1
6252110	Uemura et al.	Jun 2001	B1
D444365	Bass et al.	Jul 2001	S
D445092	Lee	Jul 2001	S
D445764	Lee	Jul 2001	S
6254623	Haibel, Jr. et al.	Jul 2001	B1
6257241	Wampler	Jul 2001	B1
6258034	Hanafy	Jul 2001	B1
6259230	Chou	Jul 2001	B1
6267761	Ryan	Jul 2001	B1
6270831	Kumar et al.	Aug 2001	B2
6273852	Lehe et al.	Aug 2001	B1
6274963	Estabrook et al.	Aug 2001	B1
6277115	Saadat	Aug 2001	B1
6277117	Tetzlaff et al.	Aug 2001	B1
6278218	Madan et al.	Aug 2001	B1
6280407	Manna et al.	Aug 2001	B1
6283981	Beaupre	Sep 2001	B1
6287344	Wampler et al.	Sep 2001	B1
6290575	Shipp	Sep 2001	B1
6292700	Morrison et al.	Sep 2001	B1
6299591	Banko	Oct 2001	B1
6306131	Hareyama et al.	Oct 2001	B1
6306157	Shchervinsky	Oct 2001	B1
6309400	Beaupre	Oct 2001	B2
6311783	Harpell	Nov 2001	B1
6319221	Savage et al.	Nov 2001	B1
6325795	Lindemann et al.	Dec 2001	B1
6325799	Goble	Dec 2001	B1
6325811	Messerly	Dec 2001	B1
6328751	Beaupre	Dec 2001	B1
6332891	Himes	Dec 2001	B1
6338657	Harper et al.	Jan 2002	B1
6340352	Okada et al.	Jan 2002	B1
6340878	Oglesbee	Jan 2002	B1
6350269	Shipp et al.	Feb 2002	B1
6352532	Kramer et al.	Mar 2002	B1
6356224	Wohlfarth	Mar 2002	B1
6358246	Behl et al.	Mar 2002	B1
6358264	Banko	Mar 2002	B2
6364888	Niemeyer et al.	Apr 2002	B1
6379320	Lafon et al.	Apr 2002	B1
D457958	Dycus et al.	May 2002	S
6383194	Pothula	May 2002	B1
6384690	Wilhelmsson et al.	May 2002	B1
6387094	Eitenmuller	May 2002	B1
6387109	Davison et al.	May 2002	B1
6388657	Natol	May 2002	B1
6390973	Ouchi	May 2002	B1
6391026	Hung et al.	May 2002	B1
6391042	Cimino	May 2002	B1
6398779	Buysse et al.	Jun 2002	B1
6402743	Orszulak et al.	Jun 2002	B1
6402748	Schoenman et al.	Jun 2002	B1
6405184	Bohme et al.	Jun 2002	B1
6405733	Fogarty et al.	Jun 2002	B1
6409722	Hoey et al.	Jun 2002	B1
H2037	Yates et al.	Jul 2002	H
6416469	Phung et al.	Jul 2002	B1
6416486	Wampler	Jul 2002	B1
6419675	Gallo, Sr.	Jul 2002	B1
6423073	Bowman	Jul 2002	B2
6423082	Houser et al.	Jul 2002	B1
6425906	Young et al.	Jul 2002	B1
6428538	Blewett et al.	Aug 2002	B1
6428539	Baxter et al.	Aug 2002	B1
6430446	Knowlton	Aug 2002	B1
6432118	Messerly	Aug 2002	B1
6436114	Novak et al.	Aug 2002	B1
6436115	Beaupre	Aug 2002	B1
6440062	Ouchi	Aug 2002	B1
6443968	Holthaus et al.	Sep 2002	B1
6443969	Novak et al.	Sep 2002	B1
6449006	Shipp	Sep 2002	B1
6454781	Witt et al.	Sep 2002	B1
6454782	Schwemberger	Sep 2002	B1
6458128	Schulze	Oct 2002	B1
6458130	Frazier et al.	Oct 2002	B1
6458142	Faller et al.	Oct 2002	B1
6459363	Walker et al.	Oct 2002	B1
6461363	Gadberry et al.	Oct 2002	B1
6464689	Qin et al.	Oct 2002	B1
6464702	Schulze et al.	Oct 2002	B2
6468270	Hovda et al.	Oct 2002	B1
6475211	Chess et al.	Nov 2002	B2
6475215	Tanrisever	Nov 2002	B1
6480796	Wiener	Nov 2002	B2
6485490	Wampler et al.	Nov 2002	B2
6491690	Goble et al.	Dec 2002	B1
6491701	Tierney et al.	Dec 2002	B2
6491708	Madan et al.	Dec 2002	B2
6497715	Satou	Dec 2002	B2
6500112	Khouri	Dec 2002	B1
6500176	Truckai et al.	Dec 2002	B1
6500188	Harper et al.	Dec 2002	B2
6500312	Wedekamp	Dec 2002	B2
6503248	Levine	Jan 2003	B1
6506208	Hunt et al.	Jan 2003	B2
6511478	Burnside et al.	Jan 2003	B1
6511480	Tetzlaff et al.	Jan 2003	B1
6511493	Moutafis et al.	Jan 2003	B1
6514252	Nezhat et al.	Feb 2003	B2
6514267	Jewett	Feb 2003	B2
6517565	Whitman et al.	Feb 2003	B1
6524251	Rabiner et al.	Feb 2003	B2
6524316	Nicholson et al.	Feb 2003	B1
6527736	Attinger et al.	Mar 2003	B1
6531846	Smith	Mar 2003	B1
6533784	Truckai et al.	Mar 2003	B2
6537272	Christopherson et al.	Mar 2003	B2
6537291	Friedman et al.	Mar 2003	B2
6543452	Lavigne	Apr 2003	B1
6543456	Freeman	Apr 2003	B1
6544260	Markel et al.	Apr 2003	B1
6551309	LePivert	Apr 2003	B1
6554829	Schulze et al.	Apr 2003	B2
6558376	Bishop	May 2003	B2
6561983	Cronin et al.	May 2003	B2
6562035	Levin	May 2003	B1
6562037	Paton et al.	May 2003	B2
6565558	Lindenmeier et al.	May 2003	B1
6572563	Ouchi	Jun 2003	B2
6572632	Zisterer et al.	Jun 2003	B2
6572639	Ingle et al.	Jun 2003	B1
6575969	Rittman, III et al.	Jun 2003	B1
6582427	Goble et al.	Jun 2003	B1
6582451	Marucci et al.	Jun 2003	B1
6584360	Francischelli et al.	Jun 2003	B2
D477408	Bromley	Jul 2003	S
6585735	Frazier et al.	Jul 2003	B1
6588277	Giordano et al.	Jul 2003	B2
6589200	Schwemberger et al.	Jul 2003	B1
6589239	Khandkar et al.	Jul 2003	B2
6590733	Wilson et al.	Jul 2003	B1
6599288	Maguire et al.	Jul 2003	B2
6602252	Mollenauer	Aug 2003	B2
6602262	Griego et al.	Aug 2003	B2
6607540	Shipp	Aug 2003	B1
6610059	West, Jr.	Aug 2003	B1
6610060	Mulier et al.	Aug 2003	B2
6611793	Burnside et al.	Aug 2003	B1
6616450	Mossle et al.	Sep 2003	B2
6619529	Green et al.	Sep 2003	B2
6620161	Schulze et al.	Sep 2003	B2
6622731	Daniel et al.	Sep 2003	B2
6623482	Pendekanti et al.	Sep 2003	B2
6623500	Cook et al.	Sep 2003	B1
6623501	Heller et al.	Sep 2003	B2
6626848	Neuenfeldt	Sep 2003	B2
6626926	Friedman et al.	Sep 2003	B2
6629974	Penny et al.	Oct 2003	B2
6632221	Edwards et al.	Oct 2003	B1
6633234	Wiener et al.	Oct 2003	B2
6635057	Harano et al.	Oct 2003	B2
6644532	Green et al.	Nov 2003	B2
6651669	Burnside	Nov 2003	B1
6652513	Panescu et al.	Nov 2003	B2
6652539	Shipp et al.	Nov 2003	B2
6652545	Shipp et al.	Nov 2003	B2
6656132	Ouchi	Dec 2003	B1
6656177	Truckai et al.	Dec 2003	B2
6656198	Tsonton et al.	Dec 2003	B2
6660017	Beaupre	Dec 2003	B2
6662127	Wiener et al.	Dec 2003	B2
6663941	Brown et al.	Dec 2003	B2
6666860	Takahashi	Dec 2003	B1
6666875	Sakurai et al.	Dec 2003	B1
6669690	Okada et al.	Dec 2003	B1
6669710	Moutafis et al.	Dec 2003	B2
6673248	Chowdhury	Jan 2004	B2
6676660	Wampler et al.	Jan 2004	B2
6678621	Wiener et al.	Jan 2004	B2
6679875	Honda et al.	Jan 2004	B2
6679882	Kornerup	Jan 2004	B1
6679899	Wiener et al.	Jan 2004	B2
6682501	Nelson	Jan 2004	B1
6682544	Mastri et al.	Jan 2004	B2
6685700	Behl et al.	Feb 2004	B2
6685701	Orszulak et al.	Feb 2004	B2
6685703	Pearson et al.	Feb 2004	B2
6689145	Lee et al.	Feb 2004	B2
6689146	Himes	Feb 2004	B1
6690960	Chen et al.	Feb 2004	B2
6695840	Schulze	Feb 2004	B2
6702821	Bonutti	Mar 2004	B2
6716215	David et al.	Apr 2004	B1
6719692	Kleffner et al.	Apr 2004	B2
6719765	Bonutti	Apr 2004	B2
6719776	Baxter et al.	Apr 2004	B2
6722552	Fenton, Jr.	Apr 2004	B2
6723091	Goble et al.	Apr 2004	B2
D490059	Conway et al.	May 2004	S
6730080	Harano et al.	May 2004	B2
6731047	Kauf et al.	May 2004	B2
6733498	Paton et al.	May 2004	B2
6733506	McDevitt et al.	May 2004	B1
6736813	Yamauchi et al.	May 2004	B2
6739872	Turri	May 2004	B1
6740079	Eggers et al.	May 2004	B1
D491666	Kimmell et al.	Jun 2004	S
6743245	Lobdell	Jun 2004	B2
6746284	Spink, Jr.	Jun 2004	B1
6746443	Morley et al.	Jun 2004	B1
6752815	Beaupre	Jun 2004	B2
6755825	Shoenman et al.	Jun 2004	B2
6761698	Shibata et al.	Jul 2004	B2
6762535	Take et al.	Jul 2004	B2
6766202	Underwood et al.	Jul 2004	B2
6770072	Truckai et al.	Aug 2004	B1
6773409	Truckai et al.	Aug 2004	B2
6773434	Ciarrocca	Aug 2004	B2
6773435	Schulze et al.	Aug 2004	B2
6773443	Truwit et al.	Aug 2004	B2
6773444	Messerly	Aug 2004	B2
6775575	Bommannan et al.	Aug 2004	B2
6778023	Christensen	Aug 2004	B2
6783524	Anderson et al.	Aug 2004	B2
6786382	Hoffman	Sep 2004	B1
6786383	Stegelmann	Sep 2004	B2
6789939	Schrodinger et al.	Sep 2004	B2
6790173	Saadat et al.	Sep 2004	B2
6790216	Ishikawa	Sep 2004	B1
6794027	Araki et al.	Sep 2004	B1
6796981	Wham et al.	Sep 2004	B2
D496997	Dycus et al.	Oct 2004	S
6800085	Selmon et al.	Oct 2004	B2
6802843	Truckai et al.	Oct 2004	B2
6808525	Latterell et al.	Oct 2004	B2
6809508	Donofrio	Oct 2004	B2
6810281	Brock et al.	Oct 2004	B2
6811842	Ehrnsperger et al.	Nov 2004	B1
6814731	Swanson	Nov 2004	B2
6819027	Saraf	Nov 2004	B2
6821273	Mollenauer	Nov 2004	B2
6827712	Tovey et al.	Dec 2004	B2
6828712	Battaglin et al.	Dec 2004	B2
6835082	Gonnering	Dec 2004	B2
6835199	McGuckin, Jr. et al.	Dec 2004	B2
6840938	Morley et al.	Jan 2005	B1
6843789	Goble	Jan 2005	B2
6849073	Hoey et al.	Feb 2005	B2
6860878	Brock	Mar 2005	B2
6860880	Treat et al.	Mar 2005	B2
6863676	Lee et al.	Mar 2005	B2
6866671	Tierney et al.	Mar 2005	B2
6869439	White et al.	Mar 2005	B2
6875220	Du et al.	Apr 2005	B2
6877647	Green et al.	Apr 2005	B2
6882439	Ishijima	Apr 2005	B2
6887209	Kadziauskas et al.	May 2005	B2
6887252	Okada et al.	May 2005	B1
6893435	Goble	May 2005	B2
6898536	Wiener et al.	May 2005	B2
6899685	Kermode et al.	May 2005	B2
6905497	Truckai et al.	Jun 2005	B2
6908463	Treat et al.	Jun 2005	B2
6908472	Wiener et al.	Jun 2005	B2
6913579	Truckai et al.	Jul 2005	B2
6915623	Dey et al.	Jul 2005	B2
6923804	Eggers et al.	Aug 2005	B2
6923806	Hooven et al.	Aug 2005	B2
6926712	Phan	Aug 2005	B2
6926716	Baker et al.	Aug 2005	B2
6926717	Garito et al.	Aug 2005	B1
6929602	Hirakui et al.	Aug 2005	B2
6929622	Chian	Aug 2005	B2
6929632	Nita et al.	Aug 2005	B2
6929644	Truckai et al.	Aug 2005	B2
6933656	Matsushita et al.	Aug 2005	B2
D509589	Wells	Sep 2005	S
6942660	Pantera et al.	Sep 2005	B2
6942677	Nita et al.	Sep 2005	B2
6945981	Donofrio et al.	Sep 2005	B2
6946779	Birge	Sep 2005	B2
6948503	Refior et al.	Sep 2005	B2
6953461	McClurken et al.	Oct 2005	B2
6958070	Witt et al.	Oct 2005	B2
D511145	Donofrio et al.	Nov 2005	S
6974450	Weber et al.	Dec 2005	B2
6976844	Hickok et al.	Dec 2005	B2
6976969	Messerly	Dec 2005	B2
6977495	Donofrio	Dec 2005	B2
6979332	Adams	Dec 2005	B2
6981628	Wales	Jan 2006	B2
6984220	Wuchinich	Jan 2006	B2
6984231	Goble et al.	Jan 2006	B2
6988295	Tillim	Jan 2006	B2
6994708	Manzo	Feb 2006	B2
6994709	Iida	Feb 2006	B2
7000818	Shelton, IV et al.	Feb 2006	B2
7001335	Adachi et al.	Feb 2006	B2
7001379	Behl et al.	Feb 2006	B2
7001382	Gallo, Sr.	Feb 2006	B2
7004951	Gibbens, III	Feb 2006	B2
7011657	Truckai et al.	Mar 2006	B2
7014638	Michelson	Mar 2006	B2
7018389	Camerlengo	Mar 2006	B2
7025732	Thompson et al.	Apr 2006	B2
7033356	Latterell et al.	Apr 2006	B2
7033357	Baxter et al.	Apr 2006	B2
7037306	Podany et al.	May 2006	B2
7041083	Chu et al.	May 2006	B2
7041088	Nawrocki et al.	May 2006	B2
7041102	Truckai et al.	May 2006	B2
7044949	Orszulak et al.	May 2006	B2
7052494	Goble et al.	May 2006	B2
7052496	Yamauchi	May 2006	B2
7055731	Shelton, IV et al.	Jun 2006	B2
7063699	Hess et al.	Jun 2006	B2
7066893	Hibner et al.	Jun 2006	B2
7066895	Podany	Jun 2006	B2
7066936	Ryan	Jun 2006	B2
7070597	Truckai et al.	Jul 2006	B2
7074218	Washington et al.	Jul 2006	B2
7074219	Levine et al.	Jul 2006	B2
7077039	Gass et al.	Jul 2006	B2
7077845	Hacker et al.	Jul 2006	B2
7077853	Kramer et al.	Jul 2006	B2
7083075	Swayze et al.	Aug 2006	B2
7083613	Treat	Aug 2006	B2
7083618	Couture et al.	Aug 2006	B2
7083619	Truckai et al.	Aug 2006	B2
7087054	Truckai et al.	Aug 2006	B2
7090637	Danitz et al.	Aug 2006	B2
7090672	Underwood et al.	Aug 2006	B2
7094235	Francischelli	Aug 2006	B2
7101371	Dycus et al.	Sep 2006	B2
7101372	Dycus et al.	Sep 2006	B2
7101373	Dycus et al.	Sep 2006	B2
7101378	Salameh et al.	Sep 2006	B2
7104834	Robinson et al.	Sep 2006	B2
7108695	Witt et al.	Sep 2006	B2
7111769	Wales et al.	Sep 2006	B2
7112201	Truckai et al.	Sep 2006	B2
7113831	Hooven	Sep 2006	B2
D531311	Guerra et al.	Oct 2006	S
7117034	Kronberg	Oct 2006	B2
7118564	Ritchie et al.	Oct 2006	B2
7118570	Tetzlaff et al.	Oct 2006	B2
7118587	Dycus et al.	Oct 2006	B2
7119516	Denning	Oct 2006	B2
7124932	Isaacson et al.	Oct 2006	B2
7125409	Truckai et al.	Oct 2006	B2
7128720	Podany	Oct 2006	B2
7131860	Sartor et al.	Nov 2006	B2
7131970	Moses et al.	Nov 2006	B2
7135018	Ryan et al.	Nov 2006	B2
7135030	Schwemberger et al.	Nov 2006	B2
7137980	Buysse et al.	Nov 2006	B2
7143925	Shelton, IV et al.	Dec 2006	B2
7144403	Booth	Dec 2006	B2
7147138	Shelton, IV	Dec 2006	B2
7153315	Miller	Dec 2006	B2
D536093	Nakajima et al.	Jan 2007	S
7156189	Bar-Cohen et al.	Jan 2007	B1
7156846	Dycus et al.	Jan 2007	B2
7156853	Muratsu	Jan 2007	B2
7157058	Marhasin et al.	Jan 2007	B2
7159750	Racenet et al.	Jan 2007	B2
7160259	Tardy et al.	Jan 2007	B2
7160296	Pearson et al.	Jan 2007	B2
7160298	Lawes et al.	Jan 2007	B2
7160299	Baily	Jan 2007	B2
7163548	Stulen et al.	Jan 2007	B2
7166103	Carmel et al.	Jan 2007	B2
7169144	Hoey et al.	Jan 2007	B2
7169146	Truckai et al.	Jan 2007	B2
7169156	Hart	Jan 2007	B2
7179254	Pendekanti et al.	Feb 2007	B2
7179271	Friedman et al.	Feb 2007	B2
7186253	Truckai et al.	Mar 2007	B2
7189233	Truckai et al.	Mar 2007	B2
7195631	Dumbauld	Mar 2007	B2
D541418	Schechter et al.	Apr 2007	S
7198635	Danek et al.	Apr 2007	B2
7204820	Akahoshi	Apr 2007	B2
7207471	Heinrich et al.	Apr 2007	B2
7207997	Shipp et al.	Apr 2007	B2
7208005	Frecker et al.	Apr 2007	B2
7210881	Greenberg	May 2007	B2
7211079	Treat	May 2007	B2
7217128	Atkin et al.	May 2007	B2
7217269	El-Galley et al.	May 2007	B2
7220951	Truckai et al.	May 2007	B2
7223229	Inman et al.	May 2007	B2
7225964	Mastri et al.	Jun 2007	B2
7226447	Uchida et al.	Jun 2007	B2
7226448	Bertolero et al.	Jun 2007	B2
7229455	Sakurai et al.	Jun 2007	B2
7232440	Dumbauld et al.	Jun 2007	B2
7235071	Gonnering	Jun 2007	B2
7235073	Levine et al.	Jun 2007	B2
7241294	Reschke	Jul 2007	B2
7244262	Wiener et al.	Jul 2007	B2
7251531	Mosher et al.	Jul 2007	B2
7252641	Thompson et al.	Aug 2007	B2
7252667	Moses et al.	Aug 2007	B2
7258688	Shah et al.	Aug 2007	B1
7264618	Murakami et al.	Sep 2007	B2
7267677	Johnson et al.	Sep 2007	B2
7267685	Butaric et al.	Sep 2007	B2
7269873	Brewer et al.	Sep 2007	B2
7273483	Wiener et al.	Sep 2007	B2
D552241	Bromley et al.	Oct 2007	S
7282048	Goble et al.	Oct 2007	B2
7285895	Beaupre	Oct 2007	B2
7287682	Ezzat et al.	Oct 2007	B1
7297149	Vitali et al.	Nov 2007	B2
7300431	Dubrovsky	Nov 2007	B2
7300435	Wham et al.	Nov 2007	B2
7300446	Beaupre	Nov 2007	B2
7300450	Vleugels et al.	Nov 2007	B2
7303531	Lee et al.	Dec 2007	B2
7303557	Wham et al.	Dec 2007	B2
7306597	Manzo	Dec 2007	B2
7307313	Ohyanagi et al.	Dec 2007	B2
7309849	Truckai et al.	Dec 2007	B2
7311706	Schoenman et al.	Dec 2007	B2
7311709	Truckai et al.	Dec 2007	B2
7317955	McGreevy	Jan 2008	B2
7318831	Alvarez et al.	Jan 2008	B2
7318832	Young et al.	Jan 2008	B2
7326236	Andreas et al.	Feb 2008	B2
7329257	Kanehira et al.	Feb 2008	B2
7331410	Yong et al.	Feb 2008	B2
7335165	Truwit et al.	Feb 2008	B2
7335997	Wiener	Feb 2008	B2
7337010	Howard et al.	Feb 2008	B2
7353068	Tanaka et al.	Apr 2008	B2
7354440	Truckal et al.	Apr 2008	B2
7357287	Shelton, IV et al.	Apr 2008	B2
7357802	Palanker et al.	Apr 2008	B2
7361172	Cimino	Apr 2008	B2
7364577	Wham et al.	Apr 2008	B2
7367976	Lawes et al.	May 2008	B2
7371227	Zeiner	May 2008	B2
RE40388	Gines	Jun 2008	E
7380695	Doll et al.	Jun 2008	B2
7380696	Shelton, IV et al.	Jun 2008	B2
7381209	Truckai et al.	Jun 2008	B2
7384420	Dycus et al.	Jun 2008	B2
7390317	Taylor et al.	Jun 2008	B2
7396356	Mollenauer	Jul 2008	B2
7403224	Fuller et al.	Jul 2008	B2
7404508	Smith et al.	Jul 2008	B2
7407077	Ortiz et al.	Aug 2008	B2
7408288	Hara	Aug 2008	B2
7412008	Lliev	Aug 2008	B2
7416101	Shelton, IV et al.	Aug 2008	B2
7416437	Sartor et al.	Aug 2008	B2
D576725	Shumer et al.	Sep 2008	S
7419490	Falkenstein et al.	Sep 2008	B2
7422139	Shelton, IV et al.	Sep 2008	B2
7422463	Kuo	Sep 2008	B2
7422582	Malackowski et al.	Sep 2008	B2
D578643	Shumer et al.	Oct 2008	S
D578644	Shumer et al.	Oct 2008	S
D578645	Shumer et al.	Oct 2008	S
7431694	Stefanchik et al.	Oct 2008	B2
7431704	Babaev	Oct 2008	B2
7431720	Pendekanti et al.	Oct 2008	B2
7435582	Zimmermann et al.	Oct 2008	B2
7441684	Shelton, IV et al.	Oct 2008	B2
7442193	Shields et al.	Oct 2008	B2
7445621	Dumbauld et al.	Nov 2008	B2
7449004	Yamada et al.	Nov 2008	B2
7451904	Shelton, IV	Nov 2008	B2
7455208	Wales et al.	Nov 2008	B2
7455641	Yamada et al.	Nov 2008	B2
7462181	Kraft et al.	Dec 2008	B2
7464846	Shelton, IV et al.	Dec 2008	B2
7464849	Shelton, IV et al.	Dec 2008	B2
7472815	Shelton, IV et al.	Jan 2009	B2
7473145	Ehr et al.	Jan 2009	B2
7473253	Dycus et al.	Jan 2009	B2
7473263	Johnston et al.	Jan 2009	B2
7479148	Beaupre	Jan 2009	B2
7479160	Branch et al.	Jan 2009	B2
7481775	Weikel, Jr. et al.	Jan 2009	B2
7488285	Honda et al.	Feb 2009	B2
7488319	Yates	Feb 2009	B2
7491201	Shields et al.	Feb 2009	B2
7491202	Odom et al.	Feb 2009	B2
7494468	Rabiner et al.	Feb 2009	B2
7494501	Ahlberg et al.	Feb 2009	B2
7498080	Tung et al.	Mar 2009	B2
7502234	Goliszek et al.	Mar 2009	B2
7503893	Kucklick	Mar 2009	B2
7503895	Rabiner et al.	Mar 2009	B2
7506790	Shelton, IV	Mar 2009	B2
7506791	Omaits et al.	Mar 2009	B2
7507239	Shadduck	Mar 2009	B2
7510107	Timm et al.	Mar 2009	B2
7510556	Nguyen et al.	Mar 2009	B2
7513025	Fischer	Apr 2009	B2
7517349	Truckai et al.	Apr 2009	B2
7520865	Radley Young et al.	Apr 2009	B2
7524320	Tierney et al.	Apr 2009	B2
7530986	Beaupre et al.	May 2009	B2
7534243	Chin et al.	May 2009	B1
7535233	Kojovic et al.	May 2009	B2
D594983	Price et al.	Jun 2009	S
7540871	Gonnering	Jun 2009	B2
7540872	Schechter et al.	Jun 2009	B2
7543730	Marczyk	Jun 2009	B1
7544200	Houser	Jun 2009	B2
7549564	Boudreaux	Jun 2009	B2
7550216	Ofer et al.	Jun 2009	B2
7553309	Buysse et al.	Jun 2009	B2
7554343	Bromfield	Jun 2009	B2
7559450	Wales et al.	Jul 2009	B2
7559452	Wales et al.	Jul 2009	B2
7563259	Takahashi	Jul 2009	B2
7566318	Haefner	Jul 2009	B2
7567012	Namikawa	Jul 2009	B2
7568603	Shelton, IV et al.	Aug 2009	B2
7569057	Liu et al.	Aug 2009	B2
7572266	Young et al.	Aug 2009	B2
7572268	Babaev	Aug 2009	B2
7578820	Moore et al.	Aug 2009	B2
7582084	Swanson et al.	Sep 2009	B2
7582086	Privitera et al.	Sep 2009	B2
7582087	Tetzlaff et al.	Sep 2009	B2
7582095	Shipp et al.	Sep 2009	B2
7585181	Olsen	Sep 2009	B2
7586289	Andruk et al.	Sep 2009	B2
7587536	McLeod	Sep 2009	B2
7588176	Timm et al.	Sep 2009	B2
7588177	Racenet	Sep 2009	B2
7594925	Danek et al.	Sep 2009	B2
7597693	Garrison	Oct 2009	B2
7601119	Shahinian	Oct 2009	B2
7601136	Akahoshi	Oct 2009	B2
7604150	Boudreaux	Oct 2009	B2
7607557	Shelton, IV et al.	Oct 2009	B2
7617961	Viola	Nov 2009	B2
7621930	Houser	Nov 2009	B2
7625370	Hart et al.	Dec 2009	B2
7628791	Garrison et al.	Dec 2009	B2
7628792	Guerra	Dec 2009	B2
7632267	Dahla	Dec 2009	B2
7632269	Truckai et al.	Dec 2009	B2
7637410	Marczyk	Dec 2009	B2
7641653	Dalla Betta et al.	Jan 2010	B2
7641671	Crainich	Jan 2010	B2
7644848	Swayze et al.	Jan 2010	B2
7645240	Thompson et al.	Jan 2010	B2
7645277	McClurken et al.	Jan 2010	B2
7645278	Ichihashi et al.	Jan 2010	B2
7648499	Orszulak et al.	Jan 2010	B2
7649410	Andersen et al.	Jan 2010	B2
7654431	Hueil et al.	Feb 2010	B2
7655003	Lorang et al.	Feb 2010	B2
7658311	Boudreaux	Feb 2010	B2
7659833	Warner et al.	Feb 2010	B2
7662151	Crompton, Jr. et al.	Feb 2010	B2
7665647	Shelton, IV et al.	Feb 2010	B2
7666206	Taniguchi et al.	Feb 2010	B2
7667592	Ohyama et al.	Feb 2010	B2
7670334	Hueil et al.	Mar 2010	B2
7670338	Albrecht et al.	Mar 2010	B2
7674263	Ryan	Mar 2010	B2
7678069	Baker et al.	Mar 2010	B1
7678105	McGreevy et al.	Mar 2010	B2
7678125	Shipp	Mar 2010	B2
7682366	Sakurai et al.	Mar 2010	B2
7686770	Cohen	Mar 2010	B2
7686826	Lee et al.	Mar 2010	B2
7688028	Phillips et al.	Mar 2010	B2
7691095	Bednarek et al.	Apr 2010	B2
7691098	Wallace et al.	Apr 2010	B2
7696441	Kataoka	Apr 2010	B2
7699846	Ryan	Apr 2010	B2
7703459	Saadat et al.	Apr 2010	B2
7703653	Shah et al.	Apr 2010	B2
7708735	Chapman et al.	May 2010	B2
7708751	Hughes et al.	May 2010	B2
7708758	Lee et al.	May 2010	B2
7708768	Danek et al.	May 2010	B2
7713202	Boukhny et al.	May 2010	B2
7713267	Pozzato	May 2010	B2
7714481	Sakai	May 2010	B2
7717312	Beetel	May 2010	B2
7717914	Kimura	May 2010	B2
7717915	Miyazawa	May 2010	B2
7721935	Racenet et al.	May 2010	B2
7722527	Bouchier et al.	May 2010	B2
7722607	Dumbauld et al.	May 2010	B2
D618797	Price et al.	Jun 2010	S
7726537	Olson et al.	Jun 2010	B2
7727177	Bayat	Jun 2010	B2
7731717	Odom et al.	Jun 2010	B2
7738969	Bleich	Jun 2010	B2
7740594	Hibner	Jun 2010	B2
7744615	Couture	Jun 2010	B2
7749240	Takahashi et al.	Jul 2010	B2
7751115	Song	Jul 2010	B2
7753245	Boudreaux et al.	Jul 2010	B2
7753904	Shelton, IV et al.	Jul 2010	B2
7753908	Swanson	Jul 2010	B2
7762445	Heinrich et al.	Jul 2010	B2
D621503	Otten et al.	Aug 2010	S
7766210	Shelton, IV et al.	Aug 2010	B2
7766693	Sartor et al.	Aug 2010	B2
7766910	Hixson et al.	Aug 2010	B2
7768510	Tsai et al.	Aug 2010	B2
7770774	Mastri et al.	Aug 2010	B2
7770775	Shelton, IV et al.	Aug 2010	B2
7771425	Dycus et al.	Aug 2010	B2
7771444	Patel et al.	Aug 2010	B2
7775972	Brock et al.	Aug 2010	B2
7776036	Schechter et al.	Aug 2010	B2
7776037	Odom	Aug 2010	B2
7778733	Nowlin et al.	Aug 2010	B2
7780054	Wales	Aug 2010	B2
7780593	Ueno et al.	Aug 2010	B2
7780651	Madhani et al.	Aug 2010	B2
7780659	Okada et al.	Aug 2010	B2
7780663	Yates et al.	Aug 2010	B2
7784662	Wales et al.	Aug 2010	B2
7784663	Shelton, IV	Aug 2010	B2
7789883	Takashino et al.	Sep 2010	B2
7793814	Racenet et al.	Sep 2010	B2
7794475	Hess et al.	Sep 2010	B2
7796969	Kelly et al.	Sep 2010	B2
7798386	Schall et al.	Sep 2010	B2
7799020	Shores et al.	Sep 2010	B2
7799027	Hafner	Sep 2010	B2
7799045	Masuda	Sep 2010	B2
7803152	Honda et al.	Sep 2010	B2
7803156	Eder et al.	Sep 2010	B2
7803168	Gifford et al.	Sep 2010	B2
7806891	Nowlin et al.	Oct 2010	B2
7810693	Broehl et al.	Oct 2010	B2
7811283	Moses et al.	Oct 2010	B2
7815238	Cao	Oct 2010	B2
7815641	Dodde et al.	Oct 2010	B2
7819298	Hall et al.	Oct 2010	B2
7819299	Shelton, IV et al.	Oct 2010	B2
7819819	Quick et al.	Oct 2010	B2
7819872	Johnson et al.	Oct 2010	B2
7821143	Wiener	Oct 2010	B2
D627066	Romero	Nov 2010	S
7824401	Manzo et al.	Nov 2010	B2
7832408	Shelton, IV et al.	Nov 2010	B2
7832611	Boyden et al.	Nov 2010	B2
7832612	Baxter, III et al.	Nov 2010	B2
7834484	Sartor	Nov 2010	B2
7837699	Yamada et al.	Nov 2010	B2
7845537	Shelton, IV et al.	Dec 2010	B2
7846155	Houser et al.	Dec 2010	B2
7846159	Morrison et al.	Dec 2010	B2
7846160	Payne et al.	Dec 2010	B2
7846161	Dumbauld et al.	Dec 2010	B2
7854735	Houser et al.	Dec 2010	B2
D631155	Peine et al.	Jan 2011	S
7861906	Doll et al.	Jan 2011	B2
7862560	Marion	Jan 2011	B2
7862561	Swanson et al.	Jan 2011	B2
7867228	Nobis et al.	Jan 2011	B2
7871392	Sartor	Jan 2011	B2
7871423	Livneh	Jan 2011	B2
7876030	Taki et al.	Jan 2011	B2
D631965	Price et al.	Feb 2011	S
7877852	Unger et al.	Feb 2011	B2
7878991	Babaev	Feb 2011	B2
7879029	Jimenez	Feb 2011	B2
7879033	Sartor et al.	Feb 2011	B2
7879035	Garrison et al.	Feb 2011	B2
7879070	Ortiz et al.	Feb 2011	B2
7883475	Dupont et al.	Feb 2011	B2
7892606	Thies et al.	Feb 2011	B2
7896875	Heim et al.	Mar 2011	B2
7897792	Iikura et al.	Mar 2011	B2
7901400	Wham et al.	Mar 2011	B2
7901423	Stulen et al.	Mar 2011	B2
7905881	Masuda et al.	Mar 2011	B2
7909220	Viola	Mar 2011	B2
7909820	Lipson et al.	Mar 2011	B2
7909824	Masuda et al.	Mar 2011	B2
7918848	Lau et al.	Apr 2011	B2
7919184	Mohapatra et al.	Apr 2011	B2
7922061	Shelton, IV et al.	Apr 2011	B2
7922651	Yamada et al.	Apr 2011	B2
7931611	Novak et al.	Apr 2011	B2
7931649	Couture et al.	Apr 2011	B2
D637288	Houghton	May 2011	S
D638540	Ijiri et al.	May 2011	S
7935114	Takashino et al.	May 2011	B2
7936203	Zimlich	May 2011	B2
7951095	Makin et al.	May 2011	B2
7951165	Golden et al.	May 2011	B2
7955331	Truckai et al.	Jun 2011	B2
7956620	Gilbert	Jun 2011	B2
7959050	Smith et al.	Jun 2011	B2
7959626	Hong et al.	Jun 2011	B2
7963963	Francischelli et al.	Jun 2011	B2
7967602	Lindquist	Jun 2011	B2
7972328	Wham et al.	Jul 2011	B2
7972329	Refior et al.	Jul 2011	B2
7975895	Milliman	Jul 2011	B2
7976544	McClurken et al.	Jul 2011	B2
7980443	Scheib et al.	Jul 2011	B2
7981050	Ritchart et al.	Jul 2011	B2
7981113	Truckai et al.	Jul 2011	B2
7997278	Utley et al.	Aug 2011	B2
7998157	Culp et al.	Aug 2011	B2
8002732	Visconti	Aug 2011	B2
8002770	Swanson et al.	Aug 2011	B2
8020743	Shelton, IV	Sep 2011	B2
8025672	Novak et al.	Sep 2011	B2
8028885	Smith et al.	Oct 2011	B2
8033173	Ehlert et al.	Oct 2011	B2
8034049	Odom et al.	Oct 2011	B2
8038693	Allen	Oct 2011	B2
8048070	O'Brien et al.	Nov 2011	B2
8052672	Laufer et al.	Nov 2011	B2
8055208	Lilla et al.	Nov 2011	B2
8056720	Hawkes	Nov 2011	B2
8056787	Boudreaux et al.	Nov 2011	B2
8057468	Konesky	Nov 2011	B2
8057498	Robertson	Nov 2011	B2
8058771	Giordano et al.	Nov 2011	B2
8061014	Smith et al.	Nov 2011	B2
8066167	Measamer et al.	Nov 2011	B2
8070036	Knodel	Dec 2011	B1
8070711	Bassinger et al.	Dec 2011	B2
8070762	Escudero et al.	Dec 2011	B2
8075555	Truckai et al.	Dec 2011	B2
8075558	Truckai et al.	Dec 2011	B2
8089197	Rinner et al.	Jan 2012	B2
8092475	Cotter et al.	Jan 2012	B2
8096459	Ortiz et al.	Jan 2012	B2
8097012	Kagarise	Jan 2012	B2
8100894	Mucko et al.	Jan 2012	B2
8105230	Honda et al.	Jan 2012	B2
8105323	Buysse et al.	Jan 2012	B2
8105324	Palanker et al.	Jan 2012	B2
8114104	Young et al.	Feb 2012	B2
8118276	Sanders et al.	Feb 2012	B2
8128624	Couture et al.	Mar 2012	B2
8133218	Daw et al.	Mar 2012	B2
8136712	Zingman	Mar 2012	B2
8141762	Bedi et al.	Mar 2012	B2
8142421	Cooper et al.	Mar 2012	B2
8142461	Houser et al.	Mar 2012	B2
8147485	Wham et al.	Apr 2012	B2
8147488	Masuda	Apr 2012	B2
8147508	Madan et al.	Apr 2012	B2
8152801	Goldberg et al.	Apr 2012	B2
8152825	Madan et al.	Apr 2012	B2
8157145	Shelton, IV et al.	Apr 2012	B2
8161977	Shelton, IV et al.	Apr 2012	B2
8162966	Connor et al.	Apr 2012	B2
8170717	Sutherland et al.	May 2012	B2
8172846	Brunnett et al.	May 2012	B2
8172870	Shipp	May 2012	B2
8177800	Spitz et al.	May 2012	B2
8182502	Stulen et al.	May 2012	B2
8186560	Hess et al.	May 2012	B2
8186877	Klimovitch et al.	May 2012	B2
8187267	Pappone et al.	May 2012	B2
D661801	Price et al.	Jun 2012	S
D661802	Price et al.	Jun 2012	S
D661803	Price et al.	Jun 2012	S
D661804	Price et al.	Jun 2012	S
8197472	Lau et al.	Jun 2012	B2
8197479	Olson et al.	Jun 2012	B2
8197502	Smith et al.	Jun 2012	B2
8207651	Gilbert	Jun 2012	B2
8210411	Yates et al.	Jul 2012	B2
8211100	Podhajsky et al.	Jul 2012	B2
8220688	Laurent et al.	Jul 2012	B2
8221306	Okada et al.	Jul 2012	B2
8221415	Francischelli	Jul 2012	B2
8221418	Prakash et al.	Jul 2012	B2
8226580	Govari et al.	Jul 2012	B2
8226665	Cohen	Jul 2012	B2
8226675	Houser et al.	Jul 2012	B2
8231607	Takuma	Jul 2012	B2
8235917	Joseph et al.	Aug 2012	B2
8236018	Yoshimine et al.	Aug 2012	B2
8236019	Houser	Aug 2012	B2
8236020	Smith et al.	Aug 2012	B2
8241235	Kahler et al.	Aug 2012	B2
8241271	Millman et al.	Aug 2012	B2
8241282	Unger et al.	Aug 2012	B2
8241283	Guerra et al.	Aug 2012	B2
8241284	Dycus et al.	Aug 2012	B2
8241312	Messerly	Aug 2012	B2
8246575	Viola	Aug 2012	B2
8246615	Behnke	Aug 2012	B2
8246616	Amoah et al.	Aug 2012	B2
8246618	Bucciaglia et al.	Aug 2012	B2
8246642	Houser et al.	Aug 2012	B2
8251994	McKenna et al.	Aug 2012	B2
8252012	Stulen	Aug 2012	B2
8253303	Giordano et al.	Aug 2012	B2
8257377	Wiener et al.	Sep 2012	B2
8257387	Cunningham	Sep 2012	B2
8262563	Bakos et al.	Sep 2012	B2
8267300	Boudreaux	Sep 2012	B2
8267935	Couture et al.	Sep 2012	B2
8273087	Kimura et al.	Sep 2012	B2
D669992	Schafer et al.	Oct 2012	S
D669993	Merchant et al.	Oct 2012	S
8277446	Heard	Oct 2012	B2
8277447	Garrison et al.	Oct 2012	B2
8277471	Wiener et al.	Oct 2012	B2
8282581	Zhao et al.	Oct 2012	B2
8282669	Gerber et al.	Oct 2012	B2
8286846	Smith et al.	Oct 2012	B2
8287485	Kimura et al.	Oct 2012	B2
8287528	Wham et al.	Oct 2012	B2
8287532	Carroll et al.	Oct 2012	B2
8292886	Kerr et al.	Oct 2012	B2
8292888	Whitman	Oct 2012	B2
8292905	Taylor et al.	Oct 2012	B2
8295902	Salahieh et al.	Oct 2012	B2
8298223	Wham et al.	Oct 2012	B2
8298225	Gilbert	Oct 2012	B2
8298232	Unger	Oct 2012	B2
8298233	Mueller	Oct 2012	B2
8303576	Brock	Nov 2012	B2
8303579	Shibata	Nov 2012	B2
8303580	Wham et al.	Nov 2012	B2
8303583	Hosier et al.	Nov 2012	B2
8303613	Crandall et al.	Nov 2012	B2
8306629	Mioduski et al.	Nov 2012	B2
8308040	Huang et al.	Nov 2012	B2
8319400	Houser et al.	Nov 2012	B2
8323302	Robertson et al.	Dec 2012	B2
8323310	Kingsley	Dec 2012	B2
8328061	Kasvikis	Dec 2012	B2
8328761	Widenhouse et al.	Dec 2012	B2
8328802	Deville et al.	Dec 2012	B2
8328833	Cuny	Dec 2012	B2
8328834	Isaacs et al.	Dec 2012	B2
8333764	Francischelli et al.	Dec 2012	B2
8333778	Smith et al.	Dec 2012	B2
8333779	Smith et al.	Dec 2012	B2
8334468	Palmer et al.	Dec 2012	B2
8334635	Voegele et al.	Dec 2012	B2
8337407	Quistgaard et al.	Dec 2012	B2
8338726	Palmer et al.	Dec 2012	B2
8343146	Godara et al.	Jan 2013	B2
8344596	Nield et al.	Jan 2013	B2
8348880	Messerly et al.	Jan 2013	B2
8348947	Takashino et al.	Jan 2013	B2
8348967	Stulen	Jan 2013	B2
8353297	Dacquay et al.	Jan 2013	B2
8357103	Mark et al.	Jan 2013	B2
8357144	Whitman et al.	Jan 2013	B2
8357149	Govari et al.	Jan 2013	B2
8357158	McKenna et al.	Jan 2013	B2
8361066	Long et al.	Jan 2013	B2
8361072	Dumbauld et al.	Jan 2013	B2
8361569	Saito et al.	Jan 2013	B2
8366727	Witt et al.	Feb 2013	B2
8372064	Douglass et al.	Feb 2013	B2
8372099	Deville et al.	Feb 2013	B2
8372101	Smith et al.	Feb 2013	B2
8372102	Stulen et al.	Feb 2013	B2
8374670	Selkee	Feb 2013	B2
8377044	Coe et al.	Feb 2013	B2
8377059	Deville et al.	Feb 2013	B2
8377085	Smith et al.	Feb 2013	B2
8382748	Geisel	Feb 2013	B2
8382775	Bender et al.	Feb 2013	B1
8382782	Robertson et al.	Feb 2013	B2
8382792	Chojin	Feb 2013	B2
8388646	Chojin	Mar 2013	B2
8388647	Nau, Jr. et al.	Mar 2013	B2
8393514	Shelton, IV et al.	Mar 2013	B2
8394115	Houser et al.	Mar 2013	B2
8397971	Yates et al.	Mar 2013	B2
8398394	Sauter et al.	Mar 2013	B2
8403926	Nobis et al.	Mar 2013	B2
8403945	Whitfield et al.	Mar 2013	B2
8403948	Deville et al.	Mar 2013	B2
8403949	Palmer et al.	Mar 2013	B2
8403950	Palmer et al.	Mar 2013	B2
8409234	Stahler et al.	Apr 2013	B2
8414577	Boudreaux et al.	Apr 2013	B2
8418073	Mohr et al.	Apr 2013	B2
8418349	Smith et al.	Apr 2013	B2
8419757	Smith et al.	Apr 2013	B2
8419758	Smith et al.	Apr 2013	B2
8419759	Dietz	Apr 2013	B2
8423182	Robinson et al.	Apr 2013	B2
8425410	Murray et al.	Apr 2013	B2
8425545	Smith et al.	Apr 2013	B2
8430811	Hess et al.	Apr 2013	B2
8430874	Newton et al.	Apr 2013	B2
8430876	Kappus et al.	Apr 2013	B2
8430897	Novak et al.	Apr 2013	B2
8430898	Wiener et al.	Apr 2013	B2
8435257	Smith et al.	May 2013	B2
8437832	Govari et al.	May 2013	B2
8439912	Cunningham et al.	May 2013	B2
8439939	Deville et al.	May 2013	B2
8444637	Podmore et al.	May 2013	B2
8444662	Palmer et al.	May 2013	B2
8444663	Houser et al.	May 2013	B2
8444664	Balanev et al.	May 2013	B2
8453906	Huang et al.	Jun 2013	B2
8454599	Inagaki et al.	Jun 2013	B2
8454639	Du et al.	Jun 2013	B2
8459525	Yates et al.	Jun 2013	B2
8460284	Aronow et al.	Jun 2013	B2
8460288	Tamai et al.	Jun 2013	B2
8460292	Truckai et al.	Jun 2013	B2
8461744	Wiener et al.	Jun 2013	B2
8469981	Robertson et al.	Jun 2013	B2
8471685	Shingai	Jun 2013	B2
8479969	Shelton, IV	Jul 2013	B2
8480703	Nicholas et al.	Jul 2013	B2
8484833	Cunningham et al.	Jul 2013	B2
8485413	Scheib et al.	Jul 2013	B2
8485970	Widenhouse et al.	Jul 2013	B2
8486057	Behnke, II	Jul 2013	B2
8486096	Robertson et al.	Jul 2013	B2
8491578	Manwaring et al.	Jul 2013	B2
8491625	Horner	Jul 2013	B2
8496682	Guerra et al.	Jul 2013	B2
D687549	Johnson et al.	Aug 2013	S
8506555	Ruiz Morales	Aug 2013	B2
8509318	Tailliet	Aug 2013	B2
8512336	Couture	Aug 2013	B2
8512337	Francischelli et al.	Aug 2013	B2
8512359	Whitman et al.	Aug 2013	B2
8512364	Kowalski et al.	Aug 2013	B2
8512365	Wiener et al.	Aug 2013	B2
8518067	Masuda et al.	Aug 2013	B2
8521331	Itkowitz	Aug 2013	B2
8523882	Huitema et al.	Sep 2013	B2
8523889	Stulen et al.	Sep 2013	B2
8528563	Gruber	Sep 2013	B2
8529437	Taylor et al.	Sep 2013	B2
8529565	Masuda et al.	Sep 2013	B2
8531064	Robertson et al.	Sep 2013	B2
8535308	Govari et al.	Sep 2013	B2
8535311	Schall	Sep 2013	B2
8535340	Allen	Sep 2013	B2
8535341	Allen	Sep 2013	B2
8540128	Shelton, IV et al.	Sep 2013	B2
8546996	Messerly et al.	Oct 2013	B2
8546999	Houser et al.	Oct 2013	B2
8551077	Main et al.	Oct 2013	B2
8551086	Kimura et al.	Oct 2013	B2
8556929	Harper et al.	Oct 2013	B2
8561870	Baxter, III et al.	Oct 2013	B2
8562592	Conlon et al.	Oct 2013	B2
8562598	Falkenstein et al.	Oct 2013	B2
8562600	Kirkpatrick et al.	Oct 2013	B2
8562604	Nishimura	Oct 2013	B2
8568390	Mueller	Oct 2013	B2
8568397	Horner et al.	Oct 2013	B2
8568400	Gilbert	Oct 2013	B2
8568412	Brandt et al.	Oct 2013	B2
8569997	Lee	Oct 2013	B2
8573461	Shelton, IV et al.	Nov 2013	B2
8573465	Shelton, IV	Nov 2013	B2
8574231	Boudreaux et al.	Nov 2013	B2
8574253	Gruber et al.	Nov 2013	B2
8579176	Smith et al.	Nov 2013	B2
8579897	Vakharia et al.	Nov 2013	B2
8579928	Robertson et al.	Nov 2013	B2
8579937	Gresham	Nov 2013	B2
8585727	Polo	Nov 2013	B2
8588371	Ogawa et al.	Nov 2013	B2
8591459	Clymer et al.	Nov 2013	B2
8591506	Wham et al.	Nov 2013	B2
8591536	Robertson	Nov 2013	B2
D695407	Price et al.	Dec 2013	S
D696631	Price et al.	Dec 2013	S
8596513	Olson et al.	Dec 2013	B2
8597193	Grunwald et al.	Dec 2013	B2
8597287	Benamou et al.	Dec 2013	B2
8602031	Reis et al.	Dec 2013	B2
8602288	Shelton, IV et al.	Dec 2013	B2
8603085	Jimenez	Dec 2013	B2
8603089	Viola	Dec 2013	B2
8608044	Hueil et al.	Dec 2013	B2
8608045	Smith et al.	Dec 2013	B2
8608745	Guzman et al.	Dec 2013	B2
8613383	Beckman et al.	Dec 2013	B2
8616431	Timm et al.	Dec 2013	B2
8617152	Werneth et al.	Dec 2013	B2
8617194	Beaupre	Dec 2013	B2
8622274	Yates et al.	Jan 2014	B2
8623011	Spivey	Jan 2014	B2
8623016	Fischer	Jan 2014	B2
8623027	Price et al.	Jan 2014	B2
8623044	Timm et al.	Jan 2014	B2
8628529	Aldridge et al.	Jan 2014	B2
8628534	Jones et al.	Jan 2014	B2
8632461	Glossop	Jan 2014	B2
8636736	Yates et al.	Jan 2014	B2
8638428	Brown	Jan 2014	B2
8640788	Dachs, II et al.	Feb 2014	B2
8641663	Kirschenman et al.	Feb 2014	B2
8647350	Mohan et al.	Feb 2014	B2
8650728	Wan et al.	Feb 2014	B2
8652120	Giordano et al.	Feb 2014	B2
8652132	Tsuchiya et al.	Feb 2014	B2
8652155	Houser et al.	Feb 2014	B2
8657489	Ladurner et al.	Feb 2014	B2
8659208	Rose et al.	Feb 2014	B1
8663214	Weinberg et al.	Mar 2014	B2
8663220	Wiener et al.	Mar 2014	B2
8663222	Anderson et al.	Mar 2014	B2
8663223	Masuda et al.	Mar 2014	B2
8663262	Smith et al.	Mar 2014	B2
8668691	Heard	Mar 2014	B2
8668710	Slipszenko et al.	Mar 2014	B2
8684253	Giordano et al.	Apr 2014	B2
8685016	Wham et al.	Apr 2014	B2
8685020	Weizman et al.	Apr 2014	B2
8690582	Rohrbach et al.	Apr 2014	B2
8695866	Leimbach et al.	Apr 2014	B2
8696366	Chen et al.	Apr 2014	B2
8696665	Hunt et al.	Apr 2014	B2
8696666	Sanai et al.	Apr 2014	B2
8696917	Petisce et al.	Apr 2014	B2
8702609	Hadjicostis	Apr 2014	B2
8702704	Shelton, IV et al.	Apr 2014	B2
8704425	Giordano et al.	Apr 2014	B2
8708213	Shelton, IV et al.	Apr 2014	B2
8709008	Willis et al.	Apr 2014	B2
8709031	Stulen	Apr 2014	B2
8709035	Johnson et al.	Apr 2014	B2
8715270	Weitzner et al.	May 2014	B2
8715277	Weizman	May 2014	B2
8721640	Taylor et al.	May 2014	B2
8721657	Kondoh et al.	May 2014	B2
8733613	Huitema et al.	May 2014	B2
8733614	Ross et al.	May 2014	B2
8734443	Hixson et al.	May 2014	B2
8738110	Tabada et al.	May 2014	B2
8747238	Shelton, IV et al.	Jun 2014	B2
8747351	Schultz	Jun 2014	B2
8747404	Boudreaux et al.	Jun 2014	B2
8749116	Messerly et al.	Jun 2014	B2
8752264	Ackley et al.	Jun 2014	B2
8752749	Moore et al.	Jun 2014	B2
8753338	Widenhouse et al.	Jun 2014	B2
8754570	Voegele et al.	Jun 2014	B2
8758342	Bales et al.	Jun 2014	B2
8758352	Cooper et al.	Jun 2014	B2
8758391	Swayze et al.	Jun 2014	B2
8764735	Coe et al.	Jul 2014	B2
8764747	Cummings et al.	Jul 2014	B2
8767970	Eppolito	Jul 2014	B2
8770459	Racenet et al.	Jul 2014	B2
8771269	Sherman et al.	Jul 2014	B2
8771270	Burbank	Jul 2014	B2
8771293	Surti et al.	Jul 2014	B2
8773001	Wiener et al.	Jul 2014	B2
8777944	Frankhouser et al.	Jul 2014	B2
8777945	Floume et al.	Jul 2014	B2
8779648	Giordano et al.	Jul 2014	B2
8783541	Shelton, IV et al.	Jul 2014	B2
8784415	Malackowski et al.	Jul 2014	B2
8784418	Romero	Jul 2014	B2
8790342	Stulen et al.	Jul 2014	B2
8795274	Hanna	Aug 2014	B2
8795275	Hafner	Aug 2014	B2
8795276	Dietz et al.	Aug 2014	B2
8795327	Dietz et al.	Aug 2014	B2
8800838	Shelton, IV	Aug 2014	B2
8801710	Ullrich et al.	Aug 2014	B2
8801752	Fortier et al.	Aug 2014	B2
8808204	Irisawa et al.	Aug 2014	B2
8808319	Houser et al.	Aug 2014	B2
8814856	Elmouelhi et al.	Aug 2014	B2
8814870	Paraschiv et al.	Aug 2014	B2
8820605	Shelton, IV	Sep 2014	B2
8821388	Naito et al.	Sep 2014	B2
8827992	Koss et al.	Sep 2014	B2
8827995	Schaller et al.	Sep 2014	B2
8834466	Cummings et al.	Sep 2014	B2
8834518	Faller et al.	Sep 2014	B2
8844789	Shelton, IV et al.	Sep 2014	B2
8845537	Tanaka et al.	Sep 2014	B2
8845630	Mehta et al.	Sep 2014	B2
8848808	Dress	Sep 2014	B2
8851354	Swensgard et al.	Oct 2014	B2
8852184	Kucklick	Oct 2014	B2
8858547	Brogna	Oct 2014	B2
8862955	Cesari	Oct 2014	B2
8864749	Okada	Oct 2014	B2
8864757	Klimovitch et al.	Oct 2014	B2
8864761	Johnson et al.	Oct 2014	B2
8870865	Frankhouser et al.	Oct 2014	B2
8874220	Draghici et al.	Oct 2014	B2
8876726	Amit et al.	Nov 2014	B2
8876858	Braun	Nov 2014	B2
8882766	Couture et al.	Nov 2014	B2
8882791	Stulen	Nov 2014	B2
8888776	Dietz et al.	Nov 2014	B2
8888783	Young	Nov 2014	B2
8888809	Davison et al.	Nov 2014	B2
8899462	Kostrzewski et al.	Dec 2014	B2
8900259	Houser et al.	Dec 2014	B2
8906016	Boudreaux et al.	Dec 2014	B2
8906017	Rioux et al.	Dec 2014	B2
8911438	Swoyer et al.	Dec 2014	B2
8911460	Neurohr et al.	Dec 2014	B2
8920412	Fritz et al.	Dec 2014	B2
8920414	Stone et al.	Dec 2014	B2
8920421	Rupp	Dec 2014	B2
8926607	Norvell et al.	Jan 2015	B2
8926608	Bacher et al.	Jan 2015	B2
8926620	Chasmawala et al.	Jan 2015	B2
8931682	Timm et al.	Jan 2015	B2
8932282	Gilbert	Jan 2015	B2
8932299	Bono et al.	Jan 2015	B2
8936614	Allen, IV	Jan 2015	B2
8939974	Boudreaux et al.	Jan 2015	B2
8945126	Garrison et al.	Feb 2015	B2
8951248	Messerly et al.	Feb 2015	B2
8951272	Robertson et al.	Feb 2015	B2
8956349	Aldridge et al.	Feb 2015	B2
8960520	McCuen	Feb 2015	B2
8961515	Twomey et al.	Feb 2015	B2
8961547	Dietz et al.	Feb 2015	B2
8967443	McCuen	Mar 2015	B2
8968283	Kharin	Mar 2015	B2
8968294	Maass et al.	Mar 2015	B2
8968296	McPherson	Mar 2015	B2
8968355	Malkowski et al.	Mar 2015	B2
8974447	Kimball et al.	Mar 2015	B2
8974477	Yamada	Mar 2015	B2
8974479	Ross et al.	Mar 2015	B2
8974932	McGahan et al.	Mar 2015	B2
8979843	Timm et al.	Mar 2015	B2
8979844	White et al.	Mar 2015	B2
8979890	Boudreaux	Mar 2015	B2
8986287	Park et al.	Mar 2015	B2
8986297	Daniel et al.	Mar 2015	B2
8986302	Aldridge et al.	Mar 2015	B2
8989855	Murphy et al.	Mar 2015	B2
8989903	Weir et al.	Mar 2015	B2
8991678	Wellman et al.	Mar 2015	B2
8992422	Spivey et al.	Mar 2015	B2
8992526	Brodbeck et al.	Mar 2015	B2
8998891	Garito et al.	Apr 2015	B2
9005199	Beckman et al.	Apr 2015	B2
9011437	Woodruff et al.	Apr 2015	B2
9011471	Timm et al.	Apr 2015	B2
9017326	DiNardo et al.	Apr 2015	B2
9017355	Smith et al.	Apr 2015	B2
9017372	Artale et al.	Apr 2015	B2
9023070	Levine et al.	May 2015	B2
9023071	Miller et al.	May 2015	B2
9028397	Naito	May 2015	B2
9028476	Bonn	May 2015	B2
9028478	Mueller	May 2015	B2
9028481	Behnke, II	May 2015	B2
9028494	Shelton, IV et al.	May 2015	B2
9028519	Yates et al.	May 2015	B2
9031667	Williams	May 2015	B2
9033973	Krapohl et al.	May 2015	B2
9035741	Hamel et al.	May 2015	B2
9037259	Mathur	May 2015	B2
9039690	Kersten et al.	May 2015	B2
9039695	Giordano et al.	May 2015	B2
9039696	Assmus et al.	May 2015	B2
9039705	Takashino	May 2015	B2
9039731	Joseph	May 2015	B2
9043018	Mohr	May 2015	B2
9044227	Shelton, IV et al.	Jun 2015	B2
9044238	Orszulak	Jun 2015	B2
9044243	Johnson et al.	Jun 2015	B2
9044245	Condie et al.	Jun 2015	B2
9044256	Cadeddu et al.	Jun 2015	B2
9044261	Houser	Jun 2015	B2
9050093	Aldridge et al.	Jun 2015	B2
9050098	Deville et al.	Jun 2015	B2
9050123	Krause et al.	Jun 2015	B2
9050124	Houser	Jun 2015	B2
9055961	Manzo et al.	Jun 2015	B2
9059547	McLawhorn	Jun 2015	B2
9060770	Shelton, IV et al.	Jun 2015	B2
9060775	Wiener et al.	Jun 2015	B2
9060776	Yates et al.	Jun 2015	B2
9060778	Condie et al.	Jun 2015	B2
9066720	Ballakur et al.	Jun 2015	B2
9066723	Beller et al.	Jun 2015	B2
9066747	Robertson	Jun 2015	B2
9072523	Houser et al.	Jul 2015	B2
9072535	Shelton, IV et al.	Jul 2015	B2
9072536	Shelton, IV et al.	Jul 2015	B2
9072538	Suzuki et al.	Jul 2015	B2
9072539	Messerly et al.	Jul 2015	B2
9084624	Larkin et al.	Jul 2015	B2
9089327	Worrell et al.	Jul 2015	B2
9089360	Messerly et al.	Jul 2015	B2
9095362	Dachs, II et al.	Aug 2015	B2
9095367	Olson et al.	Aug 2015	B2
9099863	Smith et al.	Aug 2015	B2
9101358	Kerr et al.	Aug 2015	B2
9101385	Shelton, IV et al.	Aug 2015	B2
9107684	Ma	Aug 2015	B2
9107689	Robertson et al.	Aug 2015	B2
9107690	Bales, Jr. et al.	Aug 2015	B2
9113900	Buysse et al.	Aug 2015	B2
9113907	Allen, IV et al.	Aug 2015	B2
9113940	Twomey	Aug 2015	B2
9119657	Shelton, IV et al.	Sep 2015	B2
9119957	Gantz et al.	Sep 2015	B2
9125662	Shelton, IV	Sep 2015	B2
9125667	Stone et al.	Sep 2015	B2
9144453	Rencher et al.	Sep 2015	B2
9147965	Lee	Sep 2015	B2
9149324	Huang et al.	Oct 2015	B2
9149325	Worrell et al.	Oct 2015	B2
9161803	Yates et al.	Oct 2015	B2
9165114	Jain et al.	Oct 2015	B2
9168054	Turner et al.	Oct 2015	B2
9168085	Juzkiw et al.	Oct 2015	B2
9168089	Buysse et al.	Oct 2015	B2
9173656	Schurr et al.	Nov 2015	B2
9179912	Yates et al.	Nov 2015	B2
9186199	Strauss et al.	Nov 2015	B2
9186204	Nishimura et al.	Nov 2015	B2
9186796	Ogawa	Nov 2015	B2
9192380	(Tarinelli) Racenet et al.	Nov 2015	B2
9192421	Garrison	Nov 2015	B2
9192428	Houser et al.	Nov 2015	B2
9192431	Woodruff et al.	Nov 2015	B2
9198714	Worrell et al.	Dec 2015	B2
9198715	Livneh	Dec 2015	B2
9198718	Marczyk et al.	Dec 2015	B2
9198776	Young	Dec 2015	B2
9204879	Shelton, IV	Dec 2015	B2
9204891	Weitzman	Dec 2015	B2
9204918	Germain et al.	Dec 2015	B2
9204923	Manzo et al.	Dec 2015	B2
9216050	Condie et al.	Dec 2015	B2
9216051	Fischer et al.	Dec 2015	B2
9216062	Duque et al.	Dec 2015	B2
9220483	Frankhouser et al.	Dec 2015	B2
9220527	Houser et al.	Dec 2015	B2
9220559	Worrell et al.	Dec 2015	B2
9226750	Weir et al.	Jan 2016	B2
9226751	Shelton, IV et al.	Jan 2016	B2
9226766	Aldridge et al.	Jan 2016	B2
9226767	Stulen et al.	Jan 2016	B2
9232979	Parihar et al.	Jan 2016	B2
9237891	Shelton, IV	Jan 2016	B2
9237921	Messerly et al.	Jan 2016	B2
9241060	Fujisaki	Jan 2016	B1
9241692	Gunday et al.	Jan 2016	B2
9241728	Price et al.	Jan 2016	B2
9241730	Babaev	Jan 2016	B2
9241731	Boudreaux et al.	Jan 2016	B2
9241768	Sandhu et al.	Jan 2016	B2
9247953	Palmer et al.	Feb 2016	B2
9254165	Aronow et al.	Feb 2016	B2
9259234	Robertson et al.	Feb 2016	B2
9259265	Harris et al.	Feb 2016	B2
9265567	Orban, III et al.	Feb 2016	B2
9265926	Strobl et al.	Feb 2016	B2
9265973	Akagane	Feb 2016	B2
9277962	Koss et al.	Mar 2016	B2
9282974	Shelton, IV	Mar 2016	B2
9283027	Monson et al.	Mar 2016	B2
9283045	Rhee et al.	Mar 2016	B2
9289256	Shelton, IV et al.	Mar 2016	B2
9295514	Shelton, IV et al.	Mar 2016	B2
9301759	Spivey et al.	Apr 2016	B2
9305497	Seo et al.	Apr 2016	B2
9307388	Liang et al.	Apr 2016	B2
9307986	Hall et al.	Apr 2016	B2
9308009	Madan et al.	Apr 2016	B2
9308014	Fischer	Apr 2016	B2
9314261	Bales, Jr. et al.	Apr 2016	B2
9314292	Trees et al.	Apr 2016	B2
9314301	Ben-Haim et al.	Apr 2016	B2
9326754	Polster	May 2016	B2
9326787	Sanai et al.	May 2016	B2
9326788	Batross et al.	May 2016	B2
9333025	Monson et al.	May 2016	B2
9333034	Hancock	May 2016	B2
9339289	Robertson	May 2016	B2
9339323	Eder et al.	May 2016	B2
9339326	McCullagh et al.	May 2016	B2
9345481	Hall et al.	May 2016	B2
9345534	Artale et al.	May 2016	B2
9345900	Wu et al.	May 2016	B2
9351642	Nadkarni et al.	May 2016	B2
9351726	Leimbach et al.	May 2016	B2
9351754	Vakharia et al.	May 2016	B2
9352173	Yamada et al.	May 2016	B2
9358065	Ladtkow et al.	Jun 2016	B2
9364171	Harris et al.	Jun 2016	B2
9364230	Shelton, IV et al.	Jun 2016	B2
9364279	Houser et al.	Jun 2016	B2
9370364	Smith et al.	Jun 2016	B2
9370400	Parihar	Jun 2016	B2
9370611	Ross et al.	Jun 2016	B2
9375230	Ross et al.	Jun 2016	B2
9375232	Hunt et al.	Jun 2016	B2
9375256	Cunningham et al.	Jun 2016	B2
9375264	Horner et al.	Jun 2016	B2
9375267	Kerr et al.	Jun 2016	B2
9385831	Marr et al.	Jul 2016	B2
9386983	Swensgard et al.	Jul 2016	B2
9393037	Olson et al.	Jul 2016	B2
9393070	Gelfand et al.	Jul 2016	B2
9398911	Auld	Jul 2016	B2
9402680	Ginnebaugh et al.	Aug 2016	B2
9402682	Worrell et al.	Aug 2016	B2
9408606	Shelton, IV	Aug 2016	B2
9408622	Stulen et al.	Aug 2016	B2
9408660	Strobl et al.	Aug 2016	B2
9414853	Stulen et al.	Aug 2016	B2
9414880	Monson et al.	Aug 2016	B2
9421060	Monson et al.	Aug 2016	B2
9427249	Robertson et al.	Aug 2016	B2
9427279	Muniz-Medina et al.	Aug 2016	B2
9439668	Timm et al.	Sep 2016	B2
9439669	Wiener et al.	Sep 2016	B2
9439671	Akagane	Sep 2016	B2
9442288	Tanimura	Sep 2016	B2
9445784	O'Keeffe	Sep 2016	B2
9445832	Wiener et al.	Sep 2016	B2
9451967	Jordan et al.	Sep 2016	B2
9456863	Moua	Oct 2016	B2
9456864	Witt et al.	Oct 2016	B2
9468498	Sigmon, Jr.	Oct 2016	B2
9474542	Slipszenko et al.	Oct 2016	B2
9474568	Akagane	Oct 2016	B2
9486236	Price et al.	Nov 2016	B2
9492146	Kostrzewski et al.	Nov 2016	B2
9492224	Boudreaux et al.	Nov 2016	B2
9498245	Voegele et al.	Nov 2016	B2
9498275	Wham et al.	Nov 2016	B2
9504483	Houser et al.	Nov 2016	B2
9504520	Worrell et al.	Nov 2016	B2
9504524	Behnke, II	Nov 2016	B2
9504855	Messerly et al.	Nov 2016	B2
9510850	Robertson et al.	Dec 2016	B2
9510906	Boudreaux et al.	Dec 2016	B2
9522029	Yates et al.	Dec 2016	B2
9522032	Behnke	Dec 2016	B2
9526564	Rusin	Dec 2016	B2
9526565	Strobl	Dec 2016	B2
9545253	Worrell et al.	Jan 2017	B2
9545497	Wenderow et al.	Jan 2017	B2
9554846	Boudreaux	Jan 2017	B2
9554854	Yates et al.	Jan 2017	B2
9560995	Addison et al.	Feb 2017	B2
9561038	Shelton, IV et al.	Feb 2017	B2
9572592	Price et al.	Feb 2017	B2
9574644	Parihar	Feb 2017	B2
9585714	Livneh	Mar 2017	B2
9592072	Akagane	Mar 2017	B2
9597143	Madan et al.	Mar 2017	B2
9603669	Govari et al.	Mar 2017	B2
9610091	Johnson et al.	Apr 2017	B2
9610114	Baxter, III et al.	Apr 2017	B2
9615877	Tyrrell et al.	Apr 2017	B2
9623237	Turner et al.	Apr 2017	B2
9636135	Stulen	May 2017	B2
9636165	Larson et al.	May 2017	B2
9636167	Gregg	May 2017	B2
9638770	Dietz et al.	May 2017	B2
9642644	Houser et al.	May 2017	B2
9642669	Takashino et al.	May 2017	B2
9643052	Tchao et al.	May 2017	B2
9649111	Shelton, IV et al.	May 2017	B2
9649126	Robertson et al.	May 2017	B2
9649173	Choi et al.	May 2017	B2
9655670	Larson et al.	May 2017	B2
9662131	Omori et al.	May 2017	B2
9668806	Unger et al.	Jun 2017	B2
9671860	Ogawa et al.	Jun 2017	B2
9674949	Liu et al.	Jun 2017	B1
9675374	Stulen et al.	Jun 2017	B2
9675375	Houser et al.	Jun 2017	B2
9681884	Clem et al.	Jun 2017	B2
9687290	Keller	Jun 2017	B2
9690362	Leimbach et al.	Jun 2017	B2
9693817	Mehta et al.	Jul 2017	B2
9700309	Jaworek et al.	Jul 2017	B2
9700339	Nield	Jul 2017	B2
9700343	Messerly et al.	Jul 2017	B2
9705456	Gilbert	Jul 2017	B2
9707004	Houser et al.	Jul 2017	B2
9707027	Ruddenklau et al.	Jul 2017	B2
9707030	Davison et al.	Jul 2017	B2
9713507	Stulen et al.	Jul 2017	B2
9717548	Couture	Aug 2017	B2
9717552	Cosman et al.	Aug 2017	B2
9724118	Schulte et al.	Aug 2017	B2
9724120	Faller et al.	Aug 2017	B2
9724152	Horlle et al.	Aug 2017	B2
9730695	Leimbach et al.	Aug 2017	B2
9737326	Worrell et al.	Aug 2017	B2
9737355	Yates et al.	Aug 2017	B2
9737358	Beckman et al.	Aug 2017	B2
9743929	Leimbach et al.	Aug 2017	B2
9743946	Faller et al.	Aug 2017	B2
9743947	Price et al.	Aug 2017	B2
9757142	Shimizu	Sep 2017	B2
9757150	Alexander et al.	Sep 2017	B2
9757186	Boudreaux et al.	Sep 2017	B2
9764164	Wiener et al.	Sep 2017	B2
9770285	Zoran et al.	Sep 2017	B2
9782214	Houser et al.	Oct 2017	B2
9788851	Dannaher et al.	Oct 2017	B2
9795405	Price et al.	Oct 2017	B2
9795436	Yates et al.	Oct 2017	B2
9795808	Messerly et al.	Oct 2017	B2
9801648	Houser et al.	Oct 2017	B2
9802033	Hibner et al.	Oct 2017	B2
9808246	Shelton, IV et al.	Nov 2017	B2
9808308	Faller et al.	Nov 2017	B2
9814514	Shelton, IV et al.	Nov 2017	B2
9820768	Gee et al.	Nov 2017	B2
9820771	Norton et al.	Nov 2017	B2
9820806	Lee et al.	Nov 2017	B2
9839443	Brockman et al.	Dec 2017	B2
9848901	Robertson et al.	Dec 2017	B2
9848902	Price et al.	Dec 2017	B2
9848937	Trees et al.	Dec 2017	B2
9861381	Johnson	Jan 2018	B2
9861428	Trees et al.	Jan 2018	B2
9867651	Wham	Jan 2018	B2
9867670	Brannan et al.	Jan 2018	B2
9872722	Lech	Jan 2018	B2
9872725	Worrell et al.	Jan 2018	B2
9872726	Morisaki	Jan 2018	B2
9877720	Worrell et al.	Jan 2018	B2
9877776	Boudreaux	Jan 2018	B2
9878184	Beaupre	Jan 2018	B2
9883884	Neurohr et al.	Feb 2018	B2
9888919	Leimbach et al.	Feb 2018	B2
9888958	Evans et al.	Feb 2018	B2
9901321	Harks et al.	Feb 2018	B2
9901383	Hassler, Jr.	Feb 2018	B2
9901754	Yamada	Feb 2018	B2
9907563	Germain et al.	Mar 2018	B2
9913656	Stulen	Mar 2018	B2
9913680	Voegele et al.	Mar 2018	B2
9918730	Trees et al.	Mar 2018	B2
9925003	Parihar et al.	Mar 2018	B2
9949785	Price et al.	Apr 2018	B2
9949788	Boudreaux	Apr 2018	B2
9962182	Dietz et al.	May 2018	B2
9974539	Yates et al.	May 2018	B2
9987033	Neurohr et al.	Jun 2018	B2
10004526	Dycus et al.	Jun 2018	B2
10004527	Gee et al.	Jun 2018	B2
10010339	Witt et al.	Jul 2018	B2
10010341	Houser et al.	Jul 2018	B2
10016207	Suzuki et al.	Jul 2018	B2
10022142	Aranyi et al.	Jul 2018	B2
10022567	Messerly et al.	Jul 2018	B2
10022568	Messerly et al.	Jul 2018	B2
10028761	Leimbach et al.	Jul 2018	B2
10028786	Mucilli et al.	Jul 2018	B2
10034684	Weisenburgh, II et al.	Jul 2018	B2
10034704	Asher et al.	Jul 2018	B2
10039588	Harper et al.	Aug 2018	B2
10045794	Witt et al.	Aug 2018	B2
10045810	Schall et al.	Aug 2018	B2
10045819	Jensen et al.	Aug 2018	B2
10070916	Artale	Sep 2018	B2
10080609	Hancock et al.	Sep 2018	B2
10085762	Timm et al.	Oct 2018	B2
10085792	Johnson et al.	Oct 2018	B2
10092310	Boudreaux et al.	Oct 2018	B2
10092344	Mohr et al.	Oct 2018	B2
10092348	Boudreaux	Oct 2018	B2
10092350	Rothweiler et al.	Oct 2018	B2
10105140	Malinouskas et al.	Oct 2018	B2
10111699	Boudreaux	Oct 2018	B2
10111703	Cosman, Jr. et al.	Oct 2018	B2
10117667	Robertson et al.	Nov 2018	B2
10117702	Danziger et al.	Nov 2018	B2
10123835	Keller et al.	Nov 2018	B2
10130367	Cappola et al.	Nov 2018	B2
10130410	Strobl et al.	Nov 2018	B2
10130412	Wham	Nov 2018	B2
10154848	Chernov et al.	Dec 2018	B2
10154852	Conlon et al.	Dec 2018	B2
10159524	Yates et al.	Dec 2018	B2
10166060	Johnson et al.	Jan 2019	B2
10172665	Heckel et al.	Jan 2019	B2
10172669	Felder et al.	Jan 2019	B2
10179022	Yates et al.	Jan 2019	B2
10188455	Hancock et al.	Jan 2019	B2
10194972	Yates et al.	Feb 2019	B2
10194973	Wiener et al.	Feb 2019	B2
10194976	Boudreaux	Feb 2019	B2
10194977	Yang	Feb 2019	B2
10194999	Bacher et al.	Feb 2019	B2
10201364	Leimbach et al.	Feb 2019	B2
10201365	Boudreaux et al.	Feb 2019	B2
10201382	Wiener et al.	Feb 2019	B2
10226273	Messerly et al.	Mar 2019	B2
10231747	Stulen et al.	Mar 2019	B2
10238385	Yates et al.	Mar 2019	B2
10238391	Leimbach et al.	Mar 2019	B2
10245095	Boudreaux	Apr 2019	B2
10245104	McKenna et al.	Apr 2019	B2
10251664	Shelton, IV et al.	Apr 2019	B2
10263171	Wiener et al.	Apr 2019	B2
10265117	Wiener et al.	Apr 2019	B2
10265118	Gerhardt	Apr 2019	B2
10271840	Sapre	Apr 2019	B2
10278721	Dietz et al.	May 2019	B2
10285724	Faller et al.	May 2019	B2
10285750	Coulson et al.	May 2019	B2
10299810	Robertson et al.	May 2019	B2
10299821	Shelton, IV et al.	May 2019	B2
10314579	Chowaniec et al.	Jun 2019	B2
10314638	Gee et al.	Jun 2019	B2
10321950	Yates et al.	Jun 2019	B2
10335182	Stulen et al.	Jul 2019	B2
10335183	Worrell et al.	Jul 2019	B2
10335614	Messerly et al.	Jul 2019	B2
10342602	Strobl et al.	Jul 2019	B2
10342606	Cosman et al.	Jul 2019	B2
10349999	Yates et al.	Jul 2019	B2
10357303	Conlon et al.	Jul 2019	B2
10363084	Friedrichs	Jul 2019	B2
10376305	Yates et al.	Aug 2019	B2
10398466	Stulen et al.	Sep 2019	B2
10398497	Batross et al.	Sep 2019	B2
10413352	Thomas et al.	Sep 2019	B2
10413353	Kerr et al.	Sep 2019	B2
10420579	Wiener et al.	Sep 2019	B2
10420607	Woloszko et al.	Sep 2019	B2
10426507	Wiener et al.	Oct 2019	B2
10426978	Akagane	Oct 2019	B2
10433865	Witt et al.	Oct 2019	B2
10433866	Witt et al.	Oct 2019	B2
10433900	Harris et al.	Oct 2019	B2
10441308	Robertson	Oct 2019	B2
10441310	Olson et al.	Oct 2019	B2
10441345	Aldridge et al.	Oct 2019	B2
10448986	Zikorus et al.	Oct 2019	B2
10456193	Yates et al.	Oct 2019	B2
10463421	Boudreaux et al.	Nov 2019	B2
10463887	Witt et al.	Nov 2019	B2
10485607	Strobl et al.	Nov 2019	B2
10492849	Juergens et al.	Dec 2019	B2
10507033	Dickerson et al.	Dec 2019	B2
10512795	Voegele et al.	Dec 2019	B2
10517627	Timm et al.	Dec 2019	B2
10524787	Shelton, IV et al.	Jan 2020	B2
10524854	Woodruff et al.	Jan 2020	B2
10524872	Stewart et al.	Jan 2020	B2
10537351	Shelton, IV et al.	Jan 2020	B2
10543008	Vakharia et al.	Jan 2020	B2
10548655	Scheib et al.	Feb 2020	B2
10555769	Worrell et al.	Feb 2020	B2
10561560	Boutoussov et al.	Feb 2020	B2
10575892	Danziger et al.	Mar 2020	B2
10595929	Boudreaux et al.	Mar 2020	B2
10595930	Scheib et al.	Mar 2020	B2
10610286	Wiener et al.	Apr 2020	B2
10617420	Shelton, IV et al.	Apr 2020	B2
10617464	Duppuis	Apr 2020	B2
10624691	Wiener et al.	Apr 2020	B2
RE47996	Turner et al.	May 2020	E
10639092	Corbett et al.	May 2020	B2
10639098	Cosman et al.	May 2020	B2
10646269	Worrell et al.	May 2020	B2
10677764	Ross et al.	Jun 2020	B2
10687884	Wiener et al.	Jun 2020	B2
10688321	Wiener et al.	Jun 2020	B2
10695119	Smith	Jun 2020	B2
10702329	Strobl et al.	Jul 2020	B2
10709469	Shelton, IV et al.	Jul 2020	B2
10709906	Nield	Jul 2020	B2
10716615	Shelton, IV et al.	Jul 2020	B2
10729458	Stoddard et al.	Aug 2020	B2
10729494	Parihar et al.	Aug 2020	B2
10736685	Wiener et al.	Aug 2020	B2
10751108	Yates et al.	Aug 2020	B2
10758294	Jones	Sep 2020	B2
10765470	Yates et al.	Sep 2020	B2
10779845	Timm et al.	Sep 2020	B2
10779849	Shelton, IV et al.	Sep 2020	B2
10779879	Yates et al.	Sep 2020	B2
10820938	Fischer et al.	Nov 2020	B2
10828058	Shelton, IV et al.	Nov 2020	B2
10835307	Shelton, IV et al.	Nov 2020	B2
10842523	Shelton, IV et al.	Nov 2020	B2
10842563	Gilbert et al.	Nov 2020	B2
10856896	Eichmann et al.	Dec 2020	B2
10856929	Yates et al.	Dec 2020	B2
10856934	Trees et al.	Dec 2020	B2
10874465	Weir et al.	Dec 2020	B2
10881449	Boudreaux et al.	Jan 2021	B2
10888347	Witt et al.	Jan 2021	B2
10898256	Yates et al.	Jan 2021	B2
10912580	Green et al.	Feb 2021	B2
10912603	Boudreaux et al.	Feb 2021	B2
10925659	Shelton, IV et al.	Feb 2021	B2
10932847	Yates et al.	Mar 2021	B2
10952788	Asher et al.	Mar 2021	B2
10966741	Illizaliturri-Sanchez et al.	Apr 2021	B2
10966747	Worrell et al.	Apr 2021	B2
10987123	Weir et al.	Apr 2021	B2
10987156	Trees et al.	Apr 2021	B2
10993763	Batross et al.	May 2021	B2
11020140	Gee et al.	Jun 2021	B2
11033322	Wiener et al.	Jun 2021	B2
11051840	Shelton, IV et al.	Jul 2021	B2
11051873	Wiener et al.	Jul 2021	B2
11058447	Houser	Jul 2021	B2
11058448	Shelton, IV et al.	Jul 2021	B2
11058475	Wiener et al.	Jul 2021	B2
11090104	Wiener et al.	Aug 2021	B2
11096752	Stulen et al.	Aug 2021	B2
11129669	Stulen et al.	Sep 2021	B2
11129670	Shelton, IV et al.	Sep 2021	B2
11134978	Shelton, IV et al.	Oct 2021	B2
11141213	Yates et al.	Oct 2021	B2
11202670	Worrell et al.	Dec 2021	B2
11229450	Shelton, IV et al.	Jan 2022	B2
11229471	Shelton, IV et al.	Jan 2022	B2
11229472	Shelton, IV et al.	Jan 2022	B2
20010025173	Ritchie et al.	Sep 2001	A1
20010025183	Shahidi	Sep 2001	A1
20010025184	Messerly	Sep 2001	A1
20010031950	Ryan	Oct 2001	A1
20010039419	Francischelli et al.	Nov 2001	A1
20020002377	Cimino	Jan 2002	A1
20020002380	Bishop	Jan 2002	A1
20020019649	Sikora et al.	Feb 2002	A1
20020022836	Goble et al.	Feb 2002	A1
20020029036	Goble et al.	Mar 2002	A1
20020029055	Bonutti	Mar 2002	A1
20020049551	Friedman et al.	Apr 2002	A1
20020052617	Anis et al.	May 2002	A1
20020077550	Rabiner et al.	Jun 2002	A1
20020107517	Witt et al.	Aug 2002	A1
20020156466	Sakurai et al.	Oct 2002	A1
20020156493	Houser et al.	Oct 2002	A1
20020165577	Witt et al.	Nov 2002	A1
20020177862	Aranyi et al.	Nov 2002	A1
20030014053	Nguyen et al.	Jan 2003	A1
20030014087	Fang et al.	Jan 2003	A1
20030036705	Hare et al.	Feb 2003	A1
20030040758	Wang et al.	Feb 2003	A1
20030050572	Brautigam et al.	Mar 2003	A1
20030055443	Spotnitz	Mar 2003	A1
20030109778	Rashidi	Jun 2003	A1
20030109875	Tetzlaff et al.	Jun 2003	A1
20030114851	Truckai et al.	Jun 2003	A1
20030130693	Levin et al.	Jul 2003	A1
20030139741	Goble et al.	Jul 2003	A1
20030144680	Kellogg et al.	Jul 2003	A1
20030158548	Phan et al.	Aug 2003	A1
20030171747	Kanehira et al.	Sep 2003	A1
20030181898	Bowers	Sep 2003	A1
20030199794	Sakurai et al.	Oct 2003	A1
20030204199	Novak et al.	Oct 2003	A1
20030208186	Moreyra	Nov 2003	A1
20030212332	Fenton et al.	Nov 2003	A1
20030212363	Shipp	Nov 2003	A1
20030212392	Fenton et al.	Nov 2003	A1
20030212422	Fenton et al.	Nov 2003	A1
20030225332	Okada et al.	Dec 2003	A1
20030229344	Dycus et al.	Dec 2003	A1
20040030254	Babaev	Feb 2004	A1
20040030330	Brassell et al.	Feb 2004	A1
20040047485	Sherrit et al.	Mar 2004	A1
20040054364	Aranyi et al.	Mar 2004	A1
20040064151	Mollenauer	Apr 2004	A1
20040087943	Dycus et al.	May 2004	A1
20040092921	Kadziauskas et al.	May 2004	A1
20040092992	Adams et al.	May 2004	A1
20040097911	Murakami et al.	May 2004	A1
20040097912	Gonnering	May 2004	A1
20040097919	Wellman et al.	May 2004	A1
20040097996	Rabiner et al.	May 2004	A1
20040116952	Sakurai et al.	Jun 2004	A1
20040122423	Dycus et al.	Jun 2004	A1
20040132383	Langford et al.	Jul 2004	A1
20040138621	Jahns et al.	Jul 2004	A1
20040142667	Lochhead et al.	Jul 2004	A1
20040147934	Kiester	Jul 2004	A1
20040147945	Fritzsch	Jul 2004	A1
20040158237	Abboud et al.	Aug 2004	A1
20040167508	Wham et al.	Aug 2004	A1
20040176686	Hare et al.	Sep 2004	A1
20040176751	Weitzner et al.	Sep 2004	A1
20040193150	Sharkey et al.	Sep 2004	A1
20040193153	Sartor et al.	Sep 2004	A1
20040199193	Hayashi et al.	Oct 2004	A1
20040215132	Yoon	Oct 2004	A1
20040243147	Lipow	Dec 2004	A1
20040249374	Tetzlaff et al.	Dec 2004	A1
20040260273	Wan	Dec 2004	A1
20040260300	Gorensek et al.	Dec 2004	A1
20040267311	Viola et al.	Dec 2004	A1
20050015125	Mioduski et al.	Jan 2005	A1
20050020967	Ono	Jan 2005	A1
20050021018	Anderson et al.	Jan 2005	A1
20050021065	Yamada et al.	Jan 2005	A1
20050021078	Vleugels et al.	Jan 2005	A1
20050033278	McClurken et al.	Feb 2005	A1
20050033337	Muir et al.	Feb 2005	A1
20050070800	Takahashi	Mar 2005	A1
20050080427	Govari et al.	Apr 2005	A1
20050088285	Jei	Apr 2005	A1
20050090817	Phan	Apr 2005	A1
20050096683	Ellins et al.	May 2005	A1
20050099824	Dowling et al.	May 2005	A1
20050107777	West et al.	May 2005	A1
20050131390	Heinrich et al.	Jun 2005	A1
20050143769	White et al.	Jun 2005	A1
20050149108	Cox	Jul 2005	A1
20050165429	Douglas et al.	Jul 2005	A1
20050171522	Christopherson	Aug 2005	A1
20050177184	Easley	Aug 2005	A1
20050182339	Lee et al.	Aug 2005	A1
20050188743	Land	Sep 2005	A1
20050192610	Houser et al.	Sep 2005	A1
20050192611	Houser	Sep 2005	A1
20050206583	Lemelson et al.	Sep 2005	A1
20050222598	Ho et al.	Oct 2005	A1
20050234484	Houser et al.	Oct 2005	A1
20050249667	Tuszynski et al.	Nov 2005	A1
20050256405	Makin et al.	Nov 2005	A1
20050261588	Makin et al.	Nov 2005	A1
20050262175	Iino et al.	Nov 2005	A1
20050267464	Truckai et al.	Dec 2005	A1
20050271807	Iljima et al.	Dec 2005	A1
20050273090	Nieman et al.	Dec 2005	A1
20050288659	Kimura et al.	Dec 2005	A1
20060025757	Heim	Feb 2006	A1
20060030797	Zhou et al.	Feb 2006	A1
20060030848	Craig et al.	Feb 2006	A1
20060058825	Ogura et al.	Mar 2006	A1
20060063130	Hayman et al.	Mar 2006	A1
20060064086	Odom	Mar 2006	A1
20060066181	Bromfield et al.	Mar 2006	A1
20060074442	Noriega et al.	Apr 2006	A1
20060079874	Faller et al.	Apr 2006	A1
20060079879	Faller et al.	Apr 2006	A1
20060095046	Trieu et al.	May 2006	A1
20060109061	Dobson et al.	May 2006	A1
20060159731	Shoshan	Jul 2006	A1
20060190034	Nishizawa et al.	Aug 2006	A1
20060206100	Eskridge et al.	Sep 2006	A1
20060206115	Schomer et al.	Sep 2006	A1
20060211943	Beaupre	Sep 2006	A1
20060217729	Eskridge et al.	Sep 2006	A1
20060224160	Trieu et al.	Oct 2006	A1
20060247558	Yamada	Nov 2006	A1
20060253050	Yoshimine et al.	Nov 2006	A1
20060259026	Godara et al.	Nov 2006	A1
20060264809	Hansmann et al.	Nov 2006	A1
20060264995	Fanton et al.	Nov 2006	A1
20060265035	Yachi et al.	Nov 2006	A1
20060270916	Skwarek et al.	Nov 2006	A1
20060271030	Francis et al.	Nov 2006	A1
20060293656	Shadduck et al.	Dec 2006	A1
20070016235	Tanaka et al.	Jan 2007	A1
20070016236	Beaupre	Jan 2007	A1
20070021738	Hasser et al.	Jan 2007	A1
20070027468	Wales et al.	Feb 2007	A1
20070032704	Gandini et al.	Feb 2007	A1
20070055228	Berg et al.	Mar 2007	A1
20070056596	Fanney et al.	Mar 2007	A1
20070060935	Schwardt et al.	Mar 2007	A1
20070063618	Bromfield	Mar 2007	A1
20070066971	Podhajsky	Mar 2007	A1
20070067123	Jungerman	Mar 2007	A1
20070073185	Nakao	Mar 2007	A1
20070073341	Smith et al.	Mar 2007	A1
20070074584	Talarico et al.	Apr 2007	A1
20070106317	Shelton et al.	May 2007	A1
20070118115	Artale et al.	May 2007	A1
20070130771	Ehlert et al.	Jun 2007	A1
20070135803	Belson	Jun 2007	A1
20070149881	Rabin	Jun 2007	A1
20070156163	Davison et al.	Jul 2007	A1
20070166663	Telles et al.	Jul 2007	A1
20070173803	Wham et al.	Jul 2007	A1
20070173813	Odom	Jul 2007	A1
20070173872	Neuenfeldt	Jul 2007	A1
20070175955	Shelton et al.	Aug 2007	A1
20070185474	Nahen	Aug 2007	A1
20070191712	Messerly et al.	Aug 2007	A1
20070191713	Eichmann et al.	Aug 2007	A1
20070203483	Kim et al.	Aug 2007	A1
20070208336	Kim et al.	Sep 2007	A1
20070208340	Ganz et al.	Sep 2007	A1
20070219481	Babaev	Sep 2007	A1
20070232926	Stulen et al.	Oct 2007	A1
20070232928	Wiener et al.	Oct 2007	A1
20070236213	Paden et al.	Oct 2007	A1
20070239101	Kellogg	Oct 2007	A1
20070249941	Salehi et al.	Oct 2007	A1
20070260242	Dycus et al.	Nov 2007	A1
20070265560	Soltani et al.	Nov 2007	A1
20070265613	Edelstein et al.	Nov 2007	A1
20070265616	Couture et al.	Nov 2007	A1
20070265620	Kraas et al.	Nov 2007	A1
20070275348	Lemon	Nov 2007	A1
20070287933	Phan et al.	Dec 2007	A1
20070288055	Lee	Dec 2007	A1
20070299895	Johnson et al.	Dec 2007	A1
20080005213	Holtzman	Jan 2008	A1
20080013809	Zhu et al.	Jan 2008	A1
20080015575	Odom et al.	Jan 2008	A1
20080033465	Schmitz et al.	Feb 2008	A1
20080039746	Hissong et al.	Feb 2008	A1
20080051812	Schmitz et al.	Feb 2008	A1
20080058775	Darian et al.	Mar 2008	A1
20080058845	Shimizu et al.	Mar 2008	A1
20080071269	Hilario et al.	Mar 2008	A1
20080077145	Boyden et al.	Mar 2008	A1
20080082039	Babaev	Apr 2008	A1
20080082098	Tanaka et al.	Apr 2008	A1
20080097501	Blier	Apr 2008	A1
20080114355	Whayne et al.	May 2008	A1
20080114364	Goldin et al.	May 2008	A1
20080122496	Wagner	May 2008	A1
20080125768	Tahara et al.	May 2008	A1
20080147058	Horrell et al.	Jun 2008	A1
20080147062	Truckai et al.	Jun 2008	A1
20080147092	Rogge et al.	Jun 2008	A1
20080171938	Masuda et al.	Jul 2008	A1
20080177268	Daum et al.	Jul 2008	A1
20080188755	Hart	Aug 2008	A1
20080200940	Eichmann et al.	Aug 2008	A1
20080208108	Kimura	Aug 2008	A1
20080208231	Ota et al.	Aug 2008	A1
20080214967	Aranyi et al.	Sep 2008	A1
20080234709	Houser	Sep 2008	A1
20080243162	Shibata et al.	Oct 2008	A1
20080255413	Zemlok et al.	Oct 2008	A1
20080275440	Kratoska et al.	Nov 2008	A1
20080281200	Voic et al.	Nov 2008	A1
20080281315	Gines	Nov 2008	A1
20080287944	Pearson et al.	Nov 2008	A1
20080287948	Newton et al.	Nov 2008	A1
20080296346	Shelton, IV et al.	Dec 2008	A1
20080300588	Groth et al.	Dec 2008	A1
20090012516	Curtis et al.	Jan 2009	A1
20090023985	Ewers	Jan 2009	A1
20090043293	Pankratov et al.	Feb 2009	A1
20090048537	Lydon et al.	Feb 2009	A1
20090048589	Takashino et al.	Feb 2009	A1
20090054886	Yachi et al.	Feb 2009	A1
20090054889	Newton et al.	Feb 2009	A1
20090054894	Yachi	Feb 2009	A1
20090065565	Cao	Mar 2009	A1
20090076506	Baker	Mar 2009	A1
20090082716	Akahoshi	Mar 2009	A1
20090082766	Unger et al.	Mar 2009	A1
20090088785	Masuda	Apr 2009	A1
20090090763	Zemlok et al.	Apr 2009	A1
20090101692	Whitman et al.	Apr 2009	A1
20090118751	Wiener et al.	May 2009	A1
20090143678	Keast et al.	Jun 2009	A1
20090143799	Smith et al.	Jun 2009	A1
20090143800	Deville et al.	Jun 2009	A1
20090157064	Hodel	Jun 2009	A1
20090163807	Sliwa	Jun 2009	A1
20090177119	Heidner et al.	Jul 2009	A1
20090179923	Amundson et al.	Jul 2009	A1
20090182322	D'Amelio et al.	Jul 2009	A1
20090182331	D'Amelio et al.	Jul 2009	A1
20090182332	Long et al.	Jul 2009	A1
20090192441	Gelbart et al.	Jul 2009	A1
20090198272	Kerver et al.	Aug 2009	A1
20090204114	Odom	Aug 2009	A1
20090216157	Yamada	Aug 2009	A1
20090223033	Houser	Sep 2009	A1
20090240244	Malis et al.	Sep 2009	A1
20090248021	McKenna	Oct 2009	A1
20090254077	Craig	Oct 2009	A1
20090254080	Honda	Oct 2009	A1
20090259149	Tahara et al.	Oct 2009	A1
20090264909	Beaupre	Oct 2009	A1
20090270771	Takahashi	Oct 2009	A1
20090270812	Litscher et al.	Oct 2009	A1
20090270853	Yachi et al.	Oct 2009	A1
20090270891	Beaupre	Oct 2009	A1
20090270899	Carusillo et al.	Oct 2009	A1
20090287205	Ingle	Nov 2009	A1
20090292283	Odom	Nov 2009	A1
20090299141	Downey et al.	Dec 2009	A1
20090306639	Nevo et al.	Dec 2009	A1
20090327715	Smith et al.	Dec 2009	A1
20100004508	Naito et al.	Jan 2010	A1
20100022825	Yoshie	Jan 2010	A1
20100030233	Whitman et al.	Feb 2010	A1
20100034605	Huckins et al.	Feb 2010	A1
20100036370	Mirel et al.	Feb 2010	A1
20100042093	Wham et al.	Feb 2010	A9
20100049180	Wells et al.	Feb 2010	A1
20100057118	Dietz et al.	Mar 2010	A1
20100063437	Nelson et al.	Mar 2010	A1
20100063525	Beaupre et al.	Mar 2010	A1
20100063528	Beaupre	Mar 2010	A1
20100081863	Hess et al.	Apr 2010	A1
20100081864	Hess et al.	Apr 2010	A1
20100081883	Murray et al.	Apr 2010	A1
20100094323	Isaacs et al.	Apr 2010	A1
20100106173	Yoshimine	Apr 2010	A1
20100109480	Forslund et al.	May 2010	A1
20100158307	Kubota et al.	Jun 2010	A1
20100168741	Sanai et al.	Jul 2010	A1
20100181966	Sakakibara	Jul 2010	A1
20100187283	Crainich et al.	Jul 2010	A1
20100204721	Young et al.	Aug 2010	A1
20100222714	Muir et al.	Sep 2010	A1
20100222752	Collins, Jr. et al.	Sep 2010	A1
20100228250	Brogna	Sep 2010	A1
20100234906	Koh	Sep 2010	A1
20100274160	Yachi et al.	Oct 2010	A1
20100274278	Fleenor et al.	Oct 2010	A1
20100280368	Can et al.	Nov 2010	A1
20100298743	Nield et al.	Nov 2010	A1
20100331742	Masuda	Dec 2010	A1
20110004233	Muir et al.	Jan 2011	A1
20110015650	Choi et al.	Jan 2011	A1
20110028964	Edwards	Feb 2011	A1
20110071523	Dickhans	Mar 2011	A1
20110106141	Nakamura	May 2011	A1
20110112400	Emery et al.	May 2011	A1
20110125149	El-Galley et al.	May 2011	A1
20110125151	Strauss et al.	May 2011	A1
20110144640	Heinrich et al.	Jun 2011	A1
20110160725	Kabaya et al.	Jun 2011	A1
20110238010	Kirschenman et al.	Sep 2011	A1
20110273465	Konishi et al.	Nov 2011	A1
20110278343	Knodel et al.	Nov 2011	A1
20110279268	Konishi et al.	Nov 2011	A1
20110284014	Cadeddu et al.	Nov 2011	A1
20110290856	Shelton, IV et al.	Dec 2011	A1
20110295295	Shelton, IV et al.	Dec 2011	A1
20110306967	Payne et al.	Dec 2011	A1
20110313415	Fernandez et al.	Dec 2011	A1
20120004655	Kim et al.	Jan 2012	A1
20120016413	Timm et al.	Jan 2012	A1
20120022519	Huang et al.	Jan 2012	A1
20120022526	Aldridge et al.	Jan 2012	A1
20120022583	Sugalski et al.	Jan 2012	A1
20120041358	Mann et al.	Feb 2012	A1
20120053597	Anvari et al.	Mar 2012	A1
20120059286	Hastings et al.	Mar 2012	A1
20120059289	Nield et al.	Mar 2012	A1
20120071863	Lee et al.	Mar 2012	A1
20120078244	Worrell et al.	Mar 2012	A1
20120080344	Shelton, IV	Apr 2012	A1
20120101495	Young et al.	Apr 2012	A1
20120109186	Parrott et al.	May 2012	A1
20120116222	Sawada et al.	May 2012	A1
20120116265	Houser et al.	May 2012	A1
20120116266	Houser et al.	May 2012	A1
20120116381	Houser et al.	May 2012	A1
20120136279	Tanaka et al.	May 2012	A1
20120136347	Brustad et al.	May 2012	A1
20120136386	Kishida et al.	May 2012	A1
20120143211	Kishi	Jun 2012	A1
20120150049	Zielinski et al.	Jun 2012	A1
20120150169	Zielinksi et al.	Jun 2012	A1
20120172904	Muir et al.	Jul 2012	A1
20120191091	Allen	Jul 2012	A1
20120211542	Racenet	Aug 2012	A1
20120253328	Cunningham et al.	Oct 2012	A1
20120265241	Hart et al.	Oct 2012	A1
20120296325	Takashino	Nov 2012	A1
20120296371	Kappus et al.	Nov 2012	A1
20130023925	Mueller	Jan 2013	A1
20130085510	Stefanchik et al.	Apr 2013	A1
20130123776	Monson et al.	May 2013	A1
20130158659	Bergs et al.	Jun 2013	A1
20130158660	Bergs et al.	Jun 2013	A1
20130165929	Muir et al.	Jun 2013	A1
20130214025	Zemlok et al.	Aug 2013	A1
20130253256	Griffith et al.	Sep 2013	A1
20130253480	Kimball et al.	Sep 2013	A1
20130277410	Fernandez et al.	Oct 2013	A1
20130296843	Boudreaux et al.	Nov 2013	A1
20130334989	Kataoka	Dec 2013	A1
20130345701	Allen, IV et al.	Dec 2013	A1
20140001231	Shelton, IV et al.	Jan 2014	A1
20140001234	Shelton, IV et al.	Jan 2014	A1
20140005640	Shelton, IV et al.	Jan 2014	A1
20140005678	Shelton, IV et al.	Jan 2014	A1
20140005702	Timm et al.	Jan 2014	A1
20140005705	Weir et al.	Jan 2014	A1
20140005718	Shelton, IV et al.	Jan 2014	A1
20140014544	Bugnard et al.	Jan 2014	A1
20140121569	Schafer et al.	May 2014	A1
20140135804	Weisenburgh, II et al.	May 2014	A1
20140180274	Kabaya et al.	Jun 2014	A1
20140194868	Sanai et al.	Jul 2014	A1
20140194874	Dietz et al.	Jul 2014	A1
20140194875	Reschke et al.	Jul 2014	A1
20140207135	Winter	Jul 2014	A1
20140246475	Hall et al.	Sep 2014	A1
20140263541	Leimbach et al.	Sep 2014	A1
20140263552	Hall et al.	Sep 2014	A1
20140276797	Batchelor et al.	Sep 2014	A1
20150032150	Ishida et al.	Jan 2015	A1
20150080876	Worrell et al.	Mar 2015	A1
20150080887	Sobajima et al.	Mar 2015	A1
20150088122	Jensen	Mar 2015	A1
20150112335	Boudreaux et al.	Apr 2015	A1
20150157356	Gee	Jun 2015	A1
20150164533	Felder et al.	Jun 2015	A1
20150164534	Felder et al.	Jun 2015	A1
20150164535	Felder et al.	Jun 2015	A1
20150164536	Czarnecki et al.	Jun 2015	A1
20150164537	Cagle et al.	Jun 2015	A1
20150164538	Aldridge et al.	Jun 2015	A1
20150238260	Nau, Jr.	Aug 2015	A1
20150272581	Leimbach et al.	Oct 2015	A1
20150272659	Boudreaux et al.	Oct 2015	A1
20150282879	Ruelas	Oct 2015	A1
20150289364	Ilkko et al.	Oct 2015	A1
20150313667	Allen, IV	Nov 2015	A1
20160038228	Daniel et al.	Feb 2016	A1
20160045248	Unger et al.	Feb 2016	A1
20160051316	Boudreaux	Feb 2016	A1
20160066909	Swayze et al.	Mar 2016	A1
20160175029	Witt et al.	Jun 2016	A1
20160206342	Robertson et al.	Jul 2016	A1
20160262786	Madan et al.	Sep 2016	A1
20160270842	Strobl et al.	Sep 2016	A1
20160296251	Olson et al.	Oct 2016	A1
20160296252	Olson et al.	Oct 2016	A1
20160296270	Strobl et al.	Oct 2016	A1
20160358849	Jur et al.	Dec 2016	A1
20170086909	Yates et al.	Mar 2017	A1
20170119426	Akagane	May 2017	A1
20170135751	Rothweiler et al.	May 2017	A1
20170164997	Johnson et al.	Jun 2017	A1
20170189095	Danziger et al.	Jul 2017	A1
20170202595	Shelton, IV	Jul 2017	A1
20170296177	Harris et al.	Oct 2017	A1
20170312018	Trees et al.	Nov 2017	A1
20170325874	Noack et al.	Nov 2017	A1
20180014872	Dickerson	Jan 2018	A1
20180098785	Price et al.	Apr 2018	A1
20180146976	Clauda et al.	May 2018	A1
20180235691	Voegele et al.	Aug 2018	A1
20180325517	Wingardner et al.	Nov 2018	A1
20190105067	Boudreaux et al.	Apr 2019	A1
20190201048	Stulen et al.	Jul 2019	A1
20190209201	Boudreaux et al.	Jul 2019	A1
20190262030	Faller et al.	Aug 2019	A1
20190274700	Robertson et al.	Sep 2019	A1
20190282288	Boudreaux	Sep 2019	A1
20190388091	Eschbach et al.	Dec 2019	A1
20200030021	Yates et al.	Jan 2020	A1
20200054382	Yates et al.	Feb 2020	A1
20200078085	Yates et al.	Mar 2020	A1
20200078609	Messerly et al.	Mar 2020	A1
20200085465	Timm et al.	Mar 2020	A1
20200129261	Eschbach	Apr 2020	A1
20200138473	Shelton, IV et al.	May 2020	A1
20200229833	Vakharia et al.	Jul 2020	A1
20200229834	Olson et al.	Jul 2020	A1
20200237434	Scheib et al.	Jul 2020	A1
20200261141	Wiener et al.	Aug 2020	A1
20200268433	Wiener et al.	Aug 2020	A1
20210052313	Shelton, IV et al.	Feb 2021	A1
20210100578	Weir et al.	Apr 2021	A1
20210100579	Shelton, IV et al.	Apr 2021	A1
20210177481	Shelton, IV et al.	Jun 2021	A1
20210177494	Houser et al.	Jun 2021	A1
20210177496	Shelton, IV et al.	Jun 2021	A1
20210186553	Green et al.	Jun 2021	A1
20210186554	Green et al.	Jun 2021	A1
20210196263	Shelton, IV et al.	Jul 2021	A1
20210196265	Shelton, IV et al.	Jul 2021	A1
20210196266	Shelton, IV et al.	Jul 2021	A1
20210196267	Shelton, IV et al.	Jul 2021	A1
20210196268	Shelton, IV et al.	Jul 2021	A1
20210196269	Shelton, IV et al.	Jul 2021	A1
20210196270	Shelton, IV et al.	Jul 2021	A1
20210196271	Shelton, IV et al.	Jul 2021	A1
20210196301	Shelton, IV et al.	Jul 2021	A1
20210196302	Shelton, IV et al.	Jul 2021	A1
20210196305	Strobl	Jul 2021	A1
20210196306	Estera et al.	Jul 2021	A1
20210196307	Shelton, IV	Jul 2021	A1
20210196334	Sarley et al.	Jul 2021	A1
20210196335	Messerly et al.	Jul 2021	A1
20210196336	Faller et al.	Jul 2021	A1
20210196343	Shelton, IV et al.	Jul 2021	A1
20210196344	Shelton, IV et al.	Jul 2021	A1
20210196345	Messerly et al.	Jul 2021	A1
20210196346	Leuck et al.	Jul 2021	A1
20210196349	Fiebig et al.	Jul 2021	A1
20210196350	Fiebig et al.	Jul 2021	A1
20210196351	Sarley et al.	Jul 2021	A1
20210196352	Messerly et al.	Jul 2021	A1
20210196353	Gee et al.	Jul 2021	A1
20210196354	Shelton, IV et al.	Jul 2021	A1
20210196355	Shelton, IV et al.	Jul 2021	A1
20210196356	Shelton, IV et al.	Jul 2021	A1
20210196357	Shelton, IV et al.	Jul 2021	A1
20210196358	Shelton, IV et al.	Jul 2021	A1
20210196359	Shelton, IV et al.	Jul 2021	A1
20210196360	Shelton, IV et al.	Jul 2021	A1
20210196361	Shelton, IV et al.	Jul 2021	A1
20210196362	Shelton, IV et al.	Jul 2021	A1
20210196363	Shelton, IV et al.	Jul 2021	A1
20210196364	Shelton, IV et al.	Jul 2021	A1
20210196365	Shelton, IV et al.	Jul 2021	A1
20210196366	Shelton, IV et al.	Jul 2021	A1
20210196367	Salguero et al.	Jul 2021	A1
20210212744	Shelton, IV et al.	Jul 2021	A1
20210220036	Shelton, IV et al.	Jul 2021	A1
20210236195	Asher et al.	Aug 2021	A1
20210282804	Worrell et al.	Sep 2021	A1
20210393288	Shelton, IV et al.	Dec 2021	A1
20210393314	Wiener et al.	Dec 2021	A1
20210393319	Shelton, IV et al.	Dec 2021	A1

Foreign Referenced Citations (158)

Number	Date	Country
2535467	Apr 1993	CA
2460047	Nov 2001	CN
1634601	Jul 2005	CN
1775323	May 2006	CN
1922563	Feb 2007	CN
2868227	Feb 2007	CN
101474081	Jul 2009	CN
101516285	Aug 2009	CN
101522112	Sep 2009	CN
102100582	Jun 2011	CN
102149312	Aug 2011	CN
202027624	Nov 2011	CN
102792181	Nov 2012	CN
103281982	Sep 2013	CN
103379853	Oct 2013	CN
203468630	Mar 2014	CN
104001276	Aug 2014	CN
104013444	Sep 2014	CN
104434298	Mar 2015	CN
3904558	Aug 1990	DE
9210327	Nov 1992	DE
4300307	Jul 1994	DE
29623113	Oct 1997	DE
20004812	Sep 2000	DE
20021619	Mar 2001	DE
10042606	Aug 2001	DE
10201569	Jul 2003	DE
102012109037	Apr 2014	DE
0171967	Feb 1986	EP
0336742	Oct 1989	EP
0136855	Nov 1989	EP
0705571	Apr 1996	EP
1698289	Sep 2006	EP
1862133	Dec 2007	EP
1972264	Sep 2008	EP
2060238	May 2009	EP
1747761	Oct 2009	EP
2131760	Dec 2009	EP
1214913	Jul 2010	EP
1946708	Jun 2011	EP
1767164	Jan 2013	EP
2578172	Apr 2013	EP
2668922	Dec 2013	EP
2076195	Dec 2015	EP
2510891	Jun 2016	EP
2032221	Apr 1980	GB
2317566	Apr 1998	GB
S50100891	Aug 1975	JP
S5968513	May 1984	JP
S59141938	Aug 1984	JP
S62221343	Sep 1987	JP
S62227343	Oct 1987	JP
S62292153	Dec 1987	JP
S62292154	Dec 1987	JP
S63109386	May 1988	JP
S63315049	Dec 1988	JP
H01151452	Jun 1989	JP
H01198540	Aug 1989	JP
H0271510	May 1990	JP
H02286149	Nov 1990	JP
H02292193	Dec 1990	JP
H0337061	Feb 1991	JP
H0425707	Feb 1992	JP
H0464351	Feb 1992	JP
H0430508	Mar 1992	JP
H04152942	May 1992	JP
H 0541716	Feb 1993	JP
H0595955	Apr 1993	JP
H05115490	May 1993	JP
H0670938	Mar 1994	JP
H06104503	Apr 1994	JP
H0824266	Jan 1996	JP
H08229050	Sep 1996	JP
H08275951	Oct 1996	JP
H08299351	Nov 1996	JP
H08336545	Dec 1996	JP
H09130655	May 1997	JP
H09135553	May 1997	JP
H09140722	Jun 1997	JP
H105237	Jan 1998	JP
10127654	May 1998	JP
H10295700	Nov 1998	JP
H11128238	May 1999	JP
2000210299	Aug 2000	JP
2000271142	Oct 2000	JP
2000271145	Oct 2000	JP
2000287987	Oct 2000	JP
2001029353	Feb 2001	JP
2002059380	Feb 2002	JP
2002186901	Jul 2002	JP
2002263579	Sep 2002	JP
2002330977	Nov 2002	JP
2003000612	Jan 2003	JP
2003010201	Jan 2003	JP
2003116870	Apr 2003	JP
2003126104	May 2003	JP
2003126110	May 2003	JP
2003153919	May 2003	JP
2003339730	Dec 2003	JP
2004129871	Apr 2004	JP
2004147701	May 2004	JP
2005003496	Jan 2005	JP
2005027026	Jan 2005	JP
2005074088	Mar 2005	JP
2005337119	Dec 2005	JP
2006068396	Mar 2006	JP
2006081664	Mar 2006	JP
2006114072	Apr 2006	JP
2006217716	Aug 2006	JP
2006288431	Oct 2006	JP
2007037568	Feb 2007	JP
200801876	Jan 2008	JP
200833644	Feb 2008	JP
2008188160	Aug 2008	JP
D1339835	Aug 2008	JP
2010009686	Jan 2010	JP
2010121865	Jun 2010	JP
2012071186	Apr 2012	JP
2012235658	Nov 2012	JP
100789356	Dec 2007	KR
2154437	Aug 2000	RU
22035	Mar 2002	RU
2201169	Mar 2003	RU
2405603	Dec 2010	RU
2013119977	Nov 2014	RU
850068	Jul 1981	SU
WO-8103272	Nov 1981	WO
WO-9308757	May 1993	WO
WO-9314708	Aug 1993	WO
WO-9421183	Sep 1994	WO
WO-9424949	Nov 1994	WO
WO-9639086	Dec 1996	WO
WO-9800069	Jan 1998	WO
WO-9840015	Sep 1998	WO
WO-9920213	Apr 1999	WO
WO-9923960	May 1999	WO
WO-0024330	May 2000	WO
WO-0064358	Nov 2000	WO
WO-0128444	Apr 2001	WO
WO-0167970	Sep 2001	WO
WO-0172251	Oct 2001	WO
WO-0195810	Dec 2001	WO
WO-03095028	Nov 2003	WO
WO-2004037095	May 2004	WO
WO-2004078051	Sep 2004	WO
WO-2004098426	Nov 2004	WO
WO-2007008710	Jan 2007	WO
WO-2008118709	Oct 2008	WO
WO-2008130793	Oct 2008	WO
WO-2010027109	Mar 2010	WO
WO-2010104755	Sep 2010	WO
WO-2011008672	Jan 2011	WO
WO-2011044343	Apr 2011	WO
WO-2011052939	May 2011	WO
WO-2011060031	May 2011	WO
WO-2012044606	Apr 2012	WO
WO-2012088535	Jun 2012	WO
WO-2012150567	Nov 2012	WO

Non-Patent Literature Citations (58)

Entry
Arnoczky et al., “Thermal Modification of Conective Tissues: Basic Science Considerations and Clinical Implications,” J. Am Acad Orthop Surg, vol. 8, No. 5, pp. 305-313 (Sep./Oct. 2000).
Hörmann et al., “Reversible and irreversible denaturation of collagen fibers.” Biochemistry, 10, pp. 932-937 (1971).
Technology Overview, printed from www.harmonicscalpel.com, Internet site, website accessed on Jun. 13, 2007, (3 pages).
Sherrit et al., “Novel Horn Designs for Ultrasonic/Sonic Cleaning Welding, Soldering, Cutting and Drilling,” Proc. SPIE Smart Structures Conference, vol. 4701, Paper No. 34, San Diego, CA, pp. 353-360, Mar. 2002.
Lim et al., “A Review of Mechanism Used in Laparoscopic Surgical Instruments,” Mechanism and Machine Theory, vol. 38, pp. 1133-1147, (2003).
Gooch et al., “Recommended Infection-Control Practices for Dentistry, 1993,” Published: May 28, 1993; [retrieved on Aug. 23, 2008]. Retrieved from the internet: URL: http//wonder.cdc.gov/wonder/prevguid/p0000191/p0000191.asp (15 pages).
Dean, D.A., “Electrical Impedance Spectroscopy Study of Biological Tissues,” J. Electrostat, 66(3-4), Mar. 2008, pp. 165-177. Accessed Apr. 10, 2018: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2597841/.
Covidien Brochure, The LigaSure Precise™ Instrument, dated Mar. 2011 (2 pages).
AST Products, Inc., “Principles of Video Contact Angle Analysis,” 20 pages, (2006).
Chen et al., “Heat-Induced Changes in the Mechanics of a Collagenous Tissue: Isothermal Free Shrinkage,” Transactions of the ASME, vol. 119, pp. 372-378 (Nov. 1997).
Chen et al., “Heat-Induced Changes in the Mechanics of a Collagenous Tissue: Isothermal, Isotonic Shrinkage,” Transactions of the ASME, vol. 120, pp. 382-388 (Jun. 1998).
Chen et al., “Heat-induced changes in the mechanics of a collagenous tissue: pseudoelastic behavior at 37° C.,” Journal of Biomechanics, 31, pp. 211-216 (1998).
Chen et al., “Phenomenological Evolution Equations for Heat-Induced Shrinkage of a Collagenous Tissue,” IEEE Transactions on Biomedical Engineering, vol. 45, No. 10, pp. 1234-1240 (Oct. 1998).
Moraleda et al., A Temperature Sensor Based on a Polymer Optical Fiber Macro-Bend, Sensors 2013, 13, 13076-13089, doi: 10.3390/s131013076, ISSN 1424-8220.
Leonard I. Malis, M.D., “The Value of Irrigation During Bipolar Coagulation,” 1989.
Huston et al., “Magnetic and Magnetostrictive Properties of Cube Textured Nickel for Magnetostrictive Transducer Applications,” IEEE Transactions on Magnetics, vol. 9(4), pp. 636-640 (Dec. 1973).
Orr et al., “Overview of Bioheat Transfer,” pp. 367-384 in Optical-Thermal Response of Laser-Irradiated Tissue, A. J. Welch and M. J. C. van Gemert, eds., Plenum, New York (1995).
Incropera et al., Fundamentals of Heat and Mass Transfer, Wiley, New York (1990). (Book—not attached).
F. A. Duck, “Optical Properties of Tissue Including Ultraviolet and Infrared Radiation,” pp. 43-71 in Physical Properties of Tissue (1990).
Campbell et al, “Thermal Imaging in Surgery,” p. 19-3, in Medical Infrared Imaging, N. A. Diakides and J. D. Bronzino, Eds. (2008).
http://www.dotmed.com/listing/electrosurical-unit/ethicon/ultracision-g110-/1466724.
Gerhard, Glen C., “Surgical Electrotechnology: Quo Vadis?,” IEEE Transactions on Biomedical Engineering, vol. BME-31, No. 12, pp. 787-792, Dec. 1984.
Fowler, K.R., “A Programmable, Arbitrary Waveform Electrosurgical Device,” IEEE Engineering in Medicine and Biology Society 10th Annual International Conference, pp. 1324, 1325 (1988).
Sullivan, “Cost-Constrained Selection of Strand Diameter and Number in a Litz-Wire Transformer Winding,” IEEE Transactions on Power Electronics, vol. 16, No. 2, Mar. 2001, pp. 281-288.
Graff, K.F., “Elastic Wave Propagation in a Curved Sonic Transmission Line,” IEEE Transactions on Sonics and Ultrasonics, SU-17(1), 1-6 (1970).
Makarov, S. N., Ochmann, M., Desinger, K., “The longitudinal vibration response of a curved fiber used for laser ultrasound surgical therapy,” Journal of the Acoustical Society of America 102, 1191-1199 (1997).
Morley, L. S. D., “Elastic Waves in a Naturally Curved Rod,” Quarterly Journal of Mechanics and Applied Mathematics, 14: 155-172 (1961).
Walsh, S. J., White, R. G., “Vibrational Power Transmission in Curved Beams,” Journal of Sound and Vibration, 233(3), 455-488 (2000).
Covidien Brochure, [Value Analysis Brief], LigaSure Advance™ Pistol Grip, dated Rev. Apr. 2010 (7 pages).
Wright, et al., “Time-Temperature Equivalence of Heat-Induced Changes in Cells and Proteins,” Feb. 1998. ASME Journal of Biomechanical Engineering, vol. 120, pp. 22-26.
Covidien Brochure, LigaSure Impact™ Instrument LF4318, dated Feb. 2013 (3 pages).
Covidien Brochure, LigaSure Atlas™ Hand Switching Instruments, dated Dec. 2008 (2 pages).
Covidien Brochure, The LigaSure™ 5 mm Blunt Tip Sealer/Divider Family, dated Apr. 2013 (2 pages).
Erbe Electrosurgery VIO® S, (2012), p. 7, 12 pages, accessed Mar. 31, 2014 at http://www.erbe-med. com/erbe/media/Marketing materialien/85140170 ERBE EN VIO 200 S D027541.
Jang, J. et al. “Neuro-fuzzy and Soft Computing.” Prentice Hall, 1997, pp. 13-89, 199-293, 335-393, 453-496, 535-549.
Sullivan, “Optimal Choice for Number of Strands in a Litz-Wire Transformer Winding,” IEEE Transactions on Power Electronics, vol. 14, No. 2, Mar. 1999, pp. 283-291.
Weir, C.E., “Rate of shrinkage of tendon collagen—heat, entropy and free energy of activation of the shrinkage of untreated tendon. Effect of acid salt, pickle, and tannage on the activation of tendon collagen.” Journal of the American Leather Chemists Association, 44, pp. 108-140 (1949).
Henriques. F.C., “Studies in thermal injury V. The predictability and the significance of thermally induced rate processes leading to irreversible epidermal injury.” Archives of Pathology, 434, pp. 489-502 (1947).
Wall et al., “Thermal modification of collagen,” J Shoulder Elbow Surg, No. 8, pp. 339-344 (Jul./Aug. 1999).
Harris et al., “Kinetics of Thermal Damage to a Collagenous Membrane Under Biaxial Isotonic Loading,” IEEE Transactions on Biomedical Engineering, vol. 51, No. 2, pp. 371-379 (Feb. 2004).
Harris et al., “Altered Mechanical Behavior of Epicardium Due to Isothermal Heating Under Biaxial Isotonic Loads,” Journal of Biomechanical Engineering, vol. 125, pp. 381-388 (Jun. 2003).
Lee et al., “A multi-sample denaturation temperature tester for collagenous biomaterials,” Med. Eng. Phy., vol. 17, No. 2, pp. 115-121 (Mar. 1995).
Moran et al., “Thermally Induced Shrinkage of Joint Capsule,” Clinical Orthopaedics and Related Research, No. 281, pp. 248-255 (Dec. 2000).
Wells et al., “Altered Mechanical Behavior of Epicardium Under Isothermal Biaxial Loading,” Transactions of the ASME, Journal of Biomedical Engineering, vol. 126, pp. 492-497 (Aug. 2004).
Gibson, “Magnetic Refrigerator Successfully Tested,” U.S. Department of Energy Research News, accessed online on Aug. 6, 2010 at http://www.eurekalert.org/features/doe/2001-11/dl-mrs062802.php (Nov. 1, 2001).
Humphrey, J.D., “Continuum Thermomechanics and the Clinical Treatment of Disease and Injury,” Appl. Mech. Rev., vol. 56, No. 2 pp. 231-260 (Mar. 2003).
National Semiconductors Temperature Sensor Handbook—http://www.national.com/appinfo/tempsensors/files/temphb.pdf; accessed online: Apr. 1, 2011.
Hayashi et al., “The Effect of Thermal Heating on the Length and Histologic Properties of the Glenohumeral Joint Capsule,” American Journal of Sports Medicine, vol. 25, Issue 1, 11 pages (Jan. 1997), URL: http://www.mdconsult.com/das/article/body/156183648-2/jorg=journal&source=MI&sp=1 . . . , accessed Aug. 25, 2009.
Douglas, S.C. “Introduction to Adaptive Filter”. Digital Signal Processing Handbook. Ed. Vijay K. Madisetti and Douglas B. Williams. Boca Raton: CRC Press LLC, 1999.
Kurt Gieck & Reiner Gieck, Engineering Formulas § Z.7 (7th ed. 1997).
Glaser and Subak-Sharpe, Integrated Circuit Engineering, Addison-Wesley Publishing, Reading, MA (1979). (book—not attached).
Covidien 501 (k) Summary Sonicision, dated Feb. 24, 2011 (7 pages).
http://www.megadyne.com/es_generator.php.
LaCourse, J.R.; Vogt, M.C.; Miller, W.T., III; Selikowitz, S.M., “Spectral Analysis Interpretation of Electrosurgical Generator Nerve and Muscle Stimulation,” IEEE Transactions on Biomedical Engineering, vol. 35, No. 7, pp. 505-509, Jul. 1988.
https://www.kjmagnetics.com/fieldcalculator.asp, retrieved Jul. 11, 2016, backdated to Nov. 11, 2011 via https://web.archive.org/web/20111116164447/http://www.kjmagnetics.com/fieldcalculator.asp.
http://www.apicalinstr.com/generators.htm.
http://www.medicalexpo.com/medical-manufacturer/electrosurgical-generator-6951.html.
http://www.valleylab.com/product/es/generators/index.html.

Related Publications (1)

	Number	Date	Country
	20200222111 A1	Jul 2020	US

Provisional Applications (6)

Number	Date	Country
62330669	May 2016	US
62279635	Jan 2016	US
62235368	Sep 2015	US
62235466	Sep 2015	US
62235260	Sep 2015	US
62186984	Jun 2015	US

Continuations (1)

	Number	Date	Country
Parent	15177430	Jun 2016	US
Child	16744848		US

Surgical instrument with user adaptable techniques

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