Patent Grant
11317937
In a surgical environment, smart energy devices may be needed in a smart energy architecture environment.
In one general aspect, an ultrasonic surgical instrument comprising: an end effector comprising an ultrasonic blade, an ultrasonic transducer acoustically coupled to the ultrasonic blade, and a control circuit coupled to the ultrasonic transducer. The ultrasonic transducer is configured to ultrasonically oscillate the ultrasonic blade in response to a drive signal. The control circuit is configured to: measure a complex impedance of the ultrasonic transducer, compare the complex impedance to a plurality of reference complex impedance patterns, each of the plurality of reference complex impedance patterns corresponding to a state of the end effector, and determine the state of the end effector according to which of the plurality of reference complex impedance patterns the complex impedance corresponds.
In another general aspect, an ultrasonic generator for driving an ultrasonic surgical instrument comprising an end effector, an ultrasonic blade, and an ultrasonic transducer acoustically coupled to the ultrasonic blade. The ultrasonic transducer is configured to ultrasonically oscillate the ultrasonic blade in response to a drive signal. The ultrasonic generator comprises a control circuit coupled to the ultrasonic transducer. The control circuit is configured to: apply the drive signal to the ultrasonic transducer, measure a complex impedance of the ultrasonic transducer, compare the complex impedance to a plurality of reference complex impedance patterns, each of the plurality of reference complex impedance patterns corresponding to a state of the end effector, and determine the state of the end effector according to which of the plurality of reference complex impedance patterns the complex impedance corresponds.
In another general aspect, a method of controlling an ultrasonic surgical instrument comprising an end effector, an ultrasonic blade, and an ultrasonic transducer acoustically coupled to the ultrasonic blade. The ultrasonic transducer is configured to ultrasonically oscillate the ultrasonic blade in response to a drive signal from a generator. The method comprises: measuring, by a control circuit coupled to the ultrasonic transducer, a complex impedance of the ultrasonic transducer; comparing, by the control circuit, the complex impedance to a plurality of reference complex impedance patterns, each of the plurality of reference complex impedance patterns corresponding to a state of the end effector; and determining, by the control circuit, the state of the end effector according to which of the plurality of reference complex impedance patterns the complex impedance corresponds.
The features of various aspects are set forth with particularity in the appended claims. The various aspects, however, both as to organization and methods of operation, together with further objects and advantages thereof, may best be understood by reference to the following description, taken in conjunction with the accompanying drawings as follows.
Applicant of the present application owns the following U.S. patent applications, filed on Aug. 28, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. patent applications, filed on Aug. 23, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. patent applications, filed on Jun. 30, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. patent applications, filed on Jun. 29, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional patent applications, filed on Jun. 28, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional patent application, filed on Apr. 19, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional patent applications, filed on Mar. 30, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. patent applications, filed on Mar. 29, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional patent applications, filed on Mar. 28, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional patent applications, filed on Mar. 8, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional patent applications, filed on Dec. 28, 2017, the disclosure of each of which is herein incorporated by reference in its entirety:
Before explaining various aspects of surgical devices and generators in detail, it should be noted that the illustrative examples 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 examples may be implemented or incorporated in other aspects, 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 examples for the convenience of the reader and are not for the purpose of limitation thereof. Also, it will be appreciated that one or more of the following-described aspects, expressions of aspects, and/or examples, can be combined with any one or more of the other following-described aspects, expressions of aspects and/or examples.
Various aspects are directed to improved ultrasonic surgical devices, electrosurgical devices and generators for use therewith. Aspects of the ultrasonic surgical devices can be configured for transecting and/or coagulating tissue during surgical procedures, for example. Aspects of the electrosurgical devices can be configured for transecting, coagulating, scaling, welding and/or desiccating tissue during surgical procedures, for example.
Referring to
Other types of robotic systems can be readily adapted for use with the surgical system 102. Various examples of robotic systems and surgical tools that are suitable for use with the present disclosure are described in U.S. Provisional Patent Application Ser. No. 62/611,339, titled ROBOT ASSISTED SURGICAL PLATFORM, filed Dec. 28, 2017, the disclosure of which is herein incorporated by reference in its entirety.
Various examples of cloud-based analytics that are performed by the cloud 104, and are suitable for use with the present disclosure, are described in U.S. Provisional Patent Application Ser. No. 62/611,340, titled CLOUD-BASED MEDICAL ANALYTICS, filed Dec. 28, 2017, the disclosure of which is herein incorporated by reference in its entirety.
In various aspects, the imaging device 124 includes at least one image sensor and one or more optical components. Suitable image sensors include, but are not limited to, Charge-Coupled Device (CCD) sensors and Complementary Metal-Oxide Semiconductor (CMOS) sensors.
The optical components of the imaging device 124 may include one or more illumination sources and/or one or more lenses. The one or more illumination sources may be directed to illuminate portions of the surgical field. The one or more image sensors may receive light reflected or refracted from the surgical field, including light reflected or refracted from tissue and/or surgical instruments.
The one or more illumination sources may be configured to radiate electromagnetic energy in the visible spectrum as well as the invisible spectrum. The visible spectrum, sometimes referred to as the optical spectrum or luminous spectrum, is that portion of the electromagnetic spectrum that is visible to (i.e., can be detected by) the human eye and may be referred to as visible light or simply light. A typical human eye will respond to wavelengths in air that are from about 380 nm to about 750 nm.
The invisible spectrum (i.e., the non-luminous spectrum) is that portion of the electromagnetic spectrum that lies below and above the visible spectrum (i.e., wavelengths below about 380 nm and above about 750 nm). The invisible spectrum is not detectable by the human eye. Wavelengths greater than about 750 nm are longer than the red visible spectrum, and they become invisible infrared (IR), microwave, and radio electromagnetic radiation. Wavelengths less than about 380 nm are shorter than the violet spectrum, and they become invisible ultraviolet, x-ray, and gamma ray electromagnetic radiation.
In various aspects, the imaging device 124 is configured for use in a minimally invasive procedure. Examples of imaging devices suitable for use with the present disclosure include, but not limited to, an arthroscope, angioscope, bronchoscope, choledochoscope, colonoscope, cytoscope, duodenoscope, enteroscope, esophagogastro-duodenoscope (gastroscope), endoscope, laryngoscope, nasopharyngo-neproscope, sigmoidoscope, thoracoscope, and ureteroscope.
In one aspect, the imaging device employs multi-spectrum monitoring to discriminate topography and underlying structures. A multi-spectral image is one that captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or by the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, e.g., IR and ultraviolet. Spectral imaging can allow extraction of additional information the human eye fails to capture with its receptors for red, green, and blue. The use of multi-spectral imaging is described in greater detail under the heading “Advanced Imaging Acquisition Module” in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, the disclosure of which is herein incorporated by reference in its entirety. Multi-spectrum monitoring can be a useful tool in relocating a surgical field after a surgical task is completed to perform one or more of the previously described tests on the treated tissue.
It is axiomatic that strict sterilization of the operating room and surgical equipment is required during any surgery. The strict hygiene and sterilization conditions required in a “surgical theater,” i.e., an operating or treatment room, necessitate the highest possible sterility of all medical devices and equipment. Part of that sterilization process is the need to sterilize anything that comes in contact with the patient or penetrates the sterile field, including the imaging device 124 and its attachments and components. It will be appreciated that the sterile field may be considered a specified area, such as within a tray or on a sterile towel, that is considered free of microorganisms, or the sterile field may be considered an area, immediately around a patient, who has been prepared for a surgical procedure. The sterile field may include the scrubbed team members, who are properly attired, and all furniture and fixtures in the area.
In various aspects, the visualization system 108 includes one or more imaging sensors, one or more image-processing units, one or more storage arrays, and one or more displays that are strategically arranged with respect to the sterile field, as illustrated in
As illustrated in
In one aspect, the hub 106 is also configured to route a diagnostic input or feedback entered by a non-sterile operator at the visualization tower 111 to the primary display 119 within the sterile field, where it can be viewed by a sterile operator at the operating table. In one example, the input can be in the form of a modification to the snapshot displayed on the non-sterile display 107 or 109, which can be routed to the primary display 119 by the hub 106.
Referring to
Referring now to
During a surgical procedure, energy application to tissue, for sealing and/or cutting, is generally associated with smoke evacuation, suction of excess fluid, and/or irrigation of the tissue. Fluid, power, and/or data lines from different sources are often entangled during the surgical procedure. Valuable time can be lost addressing this issue during a surgical procedure. Detangling the lines may necessitate disconnecting the lines from their respective modules, which may require resetting the modules. The hub modular enclosure 136 offers a unified environment for managing the power, data, and fluid lines, which reduces the frequency of entanglement between such lines.
Aspects of the present disclosure present a surgical hub for use in a surgical procedure that involves energy application to tissue at a surgical site. The surgical hub includes a hub enclosure and a combo generator module 140 slidably receivable in a docking station of the hub enclosure. The docking station includes data and power contacts. The combo generator module 140 includes two or more of an ultrasonic energy generator component 141, a bipolar RF energy generator component 144, and a monopolar RF energy generator component 142 that are housed in a single unit. In one aspect, the combo generator module 140 also includes a smoke evacuation component, at least one energy delivery cable for connecting the combo generator module 140 to a surgical instrument, at least one smoke evacuation component configured to evacuate smoke, fluid, and/or particulates generated by the application of therapeutic energy to the tissue, and a fluid line extending from the remote surgical site to the smoke evacuation component.
In one aspect, the fluid line is a first fluid line and a second fluid line extends from the remote surgical site to a suction and irrigation module slidably received in the hub enclosure. In one aspect, the hub enclosure comprises a fluid interface.
Certain surgical procedures may require the application of more than one energy type to the tissue. One energy type may be more beneficial for cutting the tissue, while another different energy type may be more beneficial for sealing the tissue. For example, a bipolar generator 144 can be used to seal the tissue while an ultrasonic generator 141 can be used to cut the sealed tissue. Aspects of the present disclosure present a solution where a hub modular enclosure 136 is configured to accommodate different generators, and facilitate an interactive communication therebetween. One of the advantages of the hub modular enclosure 136 is enabling the quick removal and/or replacement of various modules.
Aspects of the present disclosure present a modular surgical enclosure for use in a surgical procedure that involves energy application to tissue. The modular surgical enclosure includes a first energy-generator module, configured to generate a first energy for application to the tissue, and a first docking station comprising a first docking port that includes first data and power contacts, wherein the first energy-generator module is slidably movable into an electrical engagement with the power and data contacts and wherein the first energy-generator module is slidably movable out of the electrical engagement with the first power and data contacts,
Further to the above, the modular surgical enclosure also includes a second energy-generator module configured to generate a second energy, different than the first energy, for application to the tissue, and a second docking station comprising a second docking port that includes second data and power contacts, wherein the second energy-generator module is slidably movable into an electrical engagement with the power and data contacts, and wherein the second energy-generator module is slidably movable out of the electrical engagement with the second power and data contacts.
In addition, the modular surgical enclosure also includes a communication bus between the first docking port and the second docking port, configured to facilitate communication between the first energy-generator module and the second energy-generator module.
Referring to
In one aspect, the hub modular enclosure 136 comprises a modular power and communication backplane 149 with external and wireless communication headers to enable the removable attachment of the modules 140, 126, 128 and interactive communication therebetween.
In one aspect, the hub modular enclosure 136 includes docking stations, or drawers, 151, herein also referred to as drawers, which are configured to slidably receive the modules 140, 126, 128.
In various aspects, the smoke evacuation module 126 includes a fluid line 154 that conveys captured/collected smoke and/or fluid away from a surgical site and to, for example, the smoke evacuation module 126. Vacuum suction originating from the smoke evacuation module 126 can draw the smoke into an opening of a utility conduit at the surgical site. The utility conduit, coupled to the fluid line, can be in the form of a flexible tube terminating at the smoke evacuation module 126. The utility conduit and the fluid line define a fluid path extending toward the smoke evacuation module 126 that is received in the hub enclosure 136.
In various aspects, the suction/irrigation module 128 is coupled to a surgical tool comprising an aspiration fluid line and a suction fluid line. In one example, the aspiration and suction fluid lines are in the form of flexible tubes extending from the surgical site toward the suction/irrigation module 128. One or more drive systems can be configured to cause irrigation and aspiration of fluids to and from the surgical site.
In one aspect, the surgical tool includes a shaft having an end effector at a distal end thereof and at least one energy treatment associated with the end effector, an aspiration tube, and an irrigation tube. The aspiration tube can have an inlet port at a distal end thereof and the aspiration tube extends through the shaft. Similarly, an irrigation tube can extend through the shaft and can have an inlet port in proximity to the energy deliver implement. The energy deliver implement is configured to deliver ultrasonic and/or RF energy to the surgical site and is coupled to the generator module 140 by a cable extending initially through the shaft.
The irrigation tube can be in fluid communication with a fluid source, and the aspiration tube can be in fluid communication with a vacuum source. The fluid source and/or the vacuum source can be housed in the suction/irrigation module 128. In one example, the fluid source and/or the vacuum source can be housed in the hub enclosure 136 separately from the suction/irrigation module 128. In such example, a fluid interface can be configured to connect the suction/irrigation module 128 to the fluid source and/or the vacuum source.
In one aspect, the modules 140, 126, 128 and/or their corresponding docking stations on the hub modular enclosure 136 may include alignment features that are configured to align the docking ports of the modules into engagement with their counterparts in the docking stations of the hub modular enclosure 136. For example, as illustrated in
In some aspects, the drawers 151 of the hub modular enclosure 136 are the same, or substantially the same size, and the modules are adjusted in size to be received in the drawers 151. For example, the side brackets 155 and/or 156 can be larger or smaller depending on the size of the module. In other aspects, the drawers 151 are different in size and are each designed to accommodate a particular module.
Furthermore, the contacts of a particular module can be keyed for engagement with the contacts of a particular drawer to avoid inserting a module into a drawer with mismatching contacts.
As illustrated in
In various aspects, the imaging module 138 comprises an integrated video processor and a modular light source and is adapted for use with various imaging devices. In one aspect, the imaging device is comprised of a modular housing that can be assembled with a light source module and a camera module. The housing can be a disposable housing. In at least one example, the disposable housing is removably coupled to a reusable controller, a light source module, and a camera module. The light source module and/or the camera module can be selectively chosen depending on the type of surgical procedure. In one aspect, the camera module comprises a CCD sensor. In another aspect, the camera module comprises a CMOS sensor. In another aspect, the camera module is configured for scanned beam imaging. Likewise, the light source module can be configured to deliver a white light or a different light, depending on the surgical procedure.
During a surgical procedure, removing a surgical device from the surgical field and replacing it with another surgical device that includes a different camera or a different light source can be inefficient. Temporarily losing sight of the surgical field may lead to undesirable consequences. The module imaging device of the present disclosure is configured to permit the replacement of a light source module or a camera module midstream during a surgical procedure, without having to remove the imaging device from the surgical field.
In one aspect, the imaging device comprises a tubular housing that includes a plurality of channels. A first channel is configured to slidably receive the camera module, which can be configured for a snap-fit engagement with the first channel. A second channel is configured to slidably receive the light source module, which can be configured for a snap-fit engagement with the second channel. In another example, the camera module and/or the light source module can be rotated into a final position within their respective channels. A threaded engagement can be employed in lieu of the snap-fit engagement.
In various examples, multiple imaging devices are placed at different positions in the surgical field to provide multiple views. The imaging module 138 can be configured to switch between the imaging devices to provide an optimal view. In various aspects, the imaging module 138 can be configured to integrate the images from the different imaging device.
Various image processors and imaging devices suitable for use with the present disclosure are described in U.S. Pat. No. 7,995,045, titled COMBINED SBI AND CONVENTIONAL IMAGE PROCESSOR, which issued on Aug. 9, 2011, which is herein incorporated by reference in its entirety. In addition, U.S. Pat. No. 7,982,776, titled SBI MOTION ARTIFACT REMOVAL APPARATUS AND METHOD, which issued on Jul. 19, 2011, which is herein incorporated by reference in its entirety, describes various systems for removing motion artifacts from image data. Such systems can be integrated with the imaging module 138. Furthermore, U.S. Patent Application Publication No. 2011/0306840, titled CONTROLLABLE MAGNETIC SOURCE TO FIXTURE INTRACORPOREAL APPARATUS, which published on Dec. 15, 2011, and U.S. Patent Application Publication No. 2014/0243597, titled SYSTEM FOR PERFORMING A MINIMALLY INVASIVE SURGICAL PROCEDURE, which published on Aug. 28, 2014, each of which is herein incorporated by reference in its entirety.
Modular devices 1a-1n located in the operating theater may be coupled to the modular communication hub 203. The network hub 207 and/or the network switch 209 may be coupled to a network router 211 to connect the devices 1a-1n to the cloud 204 or the local computer system 210. Data associated with the devices 1a-1n may be transferred to cloud-based computers via the router for remote data processing and manipulation. Data associated with the devices 1a-1n may also be transferred to the local computer system 210 for local data processing and manipulation. Modular devices 2a-2m located in the same operating theater also may be coupled to a network switch 209. The network switch 209 may be coupled to the network hub 207 and/or the network router 211 to connect to the devices 2a-2m to the cloud 204. Data associated with the devices 2a-2n may be transferred to the cloud 204 via the network router 211 for data processing and manipulation. Data associated with the devices 2a-2m may also be transferred to the local computer system 210 for local data processing and manipulation.
It will be appreciated that the surgical data network 201 may be expanded by interconnecting multiple network hubs 207 and/or multiple network switches 209 with multiple network routers 211. The modular communication hub 203 may be contained in a modular control tower configured to receive multiple devices 1a-1n/2a-2m. The local computer system 210 also may be contained in a modular control tower. The modular communication hub 203 is connected to a display 212 to display images obtained by some of the devices 1a-1n/2a-2m, for example during surgical procedures. In various aspects, the devices 1a-1n/2a-2m may include, for example, various modules such as an imaging module 138 coupled to an endoscope, a generator module 140 coupled to an energy-based surgical device, a smoke evacuation module 126, a suction/irrigation module 128, a communication module 130, a processor module 132, a storage array 134, a surgical device coupled to a display, and/or a non-contact sensor module, among other modular devices that may be connected to the modular communication hub 203 of the surgical data network 201.
In one aspect, the surgical data network 201 may comprise a combination of network hub(s), network switch(es), and network router(s) connecting the devices 1a-1n/2a-2m to the cloud. Any one of or all of the devices 1a-1n/2a-2m coupled to the network hub or network switch may collect data in real time and transfer the data to cloud computers for data processing and manipulation. It will be appreciated that cloud computing relies on sharing computing resources rather than having local servers or personal devices to handle software applications. The word “cloud” may be used as a metaphor for “the Internet,” although the term is not limited as such. Accordingly, the term “cloud computing” may be used herein to refer to “a type of Internet-based computing,” where different services—such as servers, storage, and applications—are delivered to the modular communication hub 203 and/or computer system 210 located in the surgical theater (e.g., a fixed, mobile, temporary, or field operating room or space) and to devices connected to the modular communication hub 203 and/or computer system 210 through the Internet. The cloud infrastructure may be maintained by a cloud service provider. In this context, the cloud service provider may be the entity that coordinates the usage and control of the devices 1a-1n/2a-2m located in one or more operating theaters. The cloud computing services can perform a large number of calculations based on the data gathered by smart surgical instruments, robots, and other computerized devices located in the operating theater. The hub hardware enables multiple devices or connections to be connected to a computer that communicates with the cloud computing resources and storage.
Applying cloud computer data processing techniques on the data collected by the devices 1a-1n/2a-2m, the surgical data network provides improved surgical outcomes, reduced costs, and improved patient satisfaction. At least some of the devices 1a-1n/2a-2m may be employed to view tissue states to assess leaks or perfusion of sealed tissue after a tissue sealing and cutting procedure. At least some of the devices 1a-1n/2a-2m may be employed to identify pathology, such as the effects of diseases, using the cloud-based computing to examine data including images of samples of body tissue for diagnostic purposes. This includes localization and margin confirmation of tissue and phenotypes. At least some of the devices 1a-1n/2a-2m may be employed to identify anatomical structures of the body using a variety of sensors integrated with imaging devices and techniques such as overlaying images captured by multiple imaging devices. The data gathered by the devices 1a-1n/2a-2m, including image data, may be transferred to the cloud 204 or the local computer system 210 or both for data processing and manipulation including image processing and manipulation. The data may be analyzed to improve surgical procedure outcomes by determining if further treatment, such as the application of endoscopic intervention, emerging technologies, a targeted radiation, targeted intervention, and precise robotics to tissue-specific sites and conditions, may be pursued. Such data analysis may further employ outcome analytics processing, and using standardized approaches may provide beneficial feedback to either confirm surgical treatments and the behavior of the surgeon or suggest modifications to surgical treatments and the behavior of the surgeon.
In one implementation, the operating theater devices 1a-1n may be connected to the modular communication hub 203 over a wired channel or a wireless channel depending on the configuration of the devices 1a-1n to a network hub. The network hub 207 may be implemented, in one aspect, as a local network broadcast device that works on the physical layer of the Open System Interconnection (OSI) model. The network hub provides connectivity to the devices 1a-1n located in the same operating theater network. The network hub 207 collects data in the form of packets and sends them to the router in half duplex mode. The network hub 207 does not store any media access control/Internet Protocol (MAC/IP) to transfer the device data. Only one of the devices 1a-1n can send data at a time through the network hub 207. The network hub 207 has no routing tables or intelligence regarding where to send information and broadcasts all network data across each connection and to a remote server 213 (
In another implementation, the operating theater devices 2a-2m may be connected to a network switch 209 over a wired channel or a wireless channel. The network switch 209 works in the data link layer of the OSI model. The network switch 209 is a multicast device for connecting the devices 2a-2m located in the same operating theater to the network. The network switch 209 sends data in the form of frames to the network router 211 and works in full duplex mode. Multiple devices 2a-2m can send data at the same time through the network switch 209. The network switch 209 stores and uses MAC addresses of the devices 2a-2m to transfer data.
The network hub 207 and/or the network switch 209 are coupled to the network router 211 for connection to the cloud 204. The network router 211 works in the network layer of the OSI model. The network router 211 creates a route for transmitting data packets received from the network hub 207 and/or network switch 211 to cloud-based computer resources for further processing and manipulation of the data collected by any one of or all the devices 1a-1n/2a-2m. The network router 211 may be employed to connect two or more different networks located in different locations, such as, for example, different operating theaters of the same healthcare facility or different networks located in different operating theaters of different healthcare facilities. The network router 211 sends data in the form of packets to the cloud 204 and works in full duplex mode. Multiple devices can send data at the same time. The network router 211 uses IP addresses to transfer data.
In one example, the network hub 207 may be implemented as a USB hub, which allows multiple USB devices to be connected to a host computer. The USB hub may expand a single USB port into several tiers so that there are more ports available to connect devices to the host system computer. The network hub 207 may include wired or wireless capabilities to receive information over a wired channel or a wireless channel. In one aspect, a wireless USB short-range, high-bandwidth wireless radio communication protocol may be employed for communication between the devices 1a-1n and devices 2a-2m located in the operating theater.
In other examples, the operating theater devices 1a-1n/2a-2m may communicate to the modular communication hub 203 via Bluetooth wireless technology standard for exchanging data over short distances (using short-wavelength UHF radio waves in the ISM band from 2.4 to 2.485 GHz) from fixed and mobile devices and building personal area networks (PANs). In other aspects, the operating theater devices 1a-1n/2a-2m may communicate to the modular communication hub 203 via a number of wireless or wired communication standards or protocols, including but not limited to Wi-Fi (IEEE 802.11 family), WiMAX (IEEE 802.16 family), IEEE 802.20, long-term evolution (LTE), and Ev-DO, HSPA+, HSDPA+, HSUPA+, EDGE, GSM, GPRS, CDMA, TDMA, DECT, and Ethernet derivatives thereof, as well as any other wireless and wired protocols that are designated as 3G, 4G, 5G, and beyond. The computing module may include a plurality of communication modules. For instance, a first communication module may be dedicated to shorter-range wireless communications such as Wi-Fi and Bluetooth, and a second communication module may be dedicated to longer-range wireless communications such as GPS, EDGE, GPRS, CDMA, WiMAX, LTE, Ev-DO, and others.
The modular communication hub 203 may serve as a central connection for one or all of the operating theater devices 1a-1n/2a-2m and handles a data type known as frames. Frames carry the data generated by the devices 1a-1n/2a-2m. When a frame is received by the modular communication hub 203, it is amplified and transmitted to the network router 211, which transfers the data to the cloud computing resources by using a number of wireless or wired communication standards or protocols, as described herein.
The modular communication hub 203 can be used as a standalone device or be connected to compatible network hubs and network switches to form a larger network. The modular communication hub 203 is generally easy to install, configure, and maintain, making it a good option for networking the operating theater devices 1a-1n/2a-2m.
The surgical hub 206 employs a non-contact sensor module 242 to measure the dimensions of the operating theater and generate a map of the surgical theater using either ultrasonic or laser-type non-contact measurement devices. An ultrasound-based non-contact sensor module scans the operating theater by transmitting a burst of ultrasound and receiving the echo when it bounces off the perimeter walls of an operating theater as described under the heading “Surgical Hub Spatial Awareness Within an Operating Room” in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, which is herein incorporated by reference in its entirety, in which the sensor module is configured to determine the size of the operating theater and to adjust Bluetooth-pairing distance limits. A laser-based non-contact sensor module scans the operating theater by transmitting laser light pulses, receiving laser light pulses that bounce off the perimeter walls of the operating theater, and comparing the phase of the transmitted pulse to the received pulse to determine the size of the operating theater and to adjust Bluetooth pairing distance limits, for example.
The computer system 210 comprises a processor 244 and a network interface 245. The processor 244 is coupled to a communication module 247, storage 248, memory 249, non-volatile memory 250, and input/output interface 251 via a system bus. The system bus can be any of several types of bus structure(s) including the memory bus or memory controller, a peripheral bus or external bus, and/or a local bus using any variety of available bus architectures including, but not limited to, 9-bit bus, Industrial Standard Architecture (ISA), Micro-Charmel Architecture (MSA), Extended ISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component Interconnect (PCI), USB, Advanced Graphics Port (AGP), Personal Computer Memory Card International Association bus (PCMCIA), Small Computer Systems Interface (SCSI), or any other proprietary bus.
The processor 244 may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In one aspect, the processor may be an LM4F230H5QR ARM Cortex-M4F Processor Core, available from Texas Instruments, for example, comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle serial random access memory (SRAM), an internal read-only memory (ROM) loaded with StellarisWare® software, a 2 KB electrically erasable programmable read-only memory (EEPROM), and/or one or more pulse width modulation (PWM) modules, one or more quadrature encoder inputs (QEI) analogs, one or more 12-bit analog-to-digital converters (ADCs) with 12 analog input channels, details of which are available for the product datasheet.
In one aspect, the processor 244 may comprise a safety controller comprising two controller-based families such as TMS570 and RM4x, known under the trade name Hercules ARM Cortex R4, also by Texas Instruments. The safety controller may be configured specifically for IEC 61508 and ISO 26262 safety critical applications, among others, to provide advanced integrated safety features while delivering scalable performance, connectivity, and memory options.
The system memory includes volatile memory and non-volatile memory. The basic input/output system (BIOS), containing the basic routines to transfer information between elements within the computer system, such as during start-up, is stored in non-volatile memory. For example, the non-volatile memory can include ROM, programmable ROM (PROM), electrically programmable ROM (EPROM), EEPROM, or flash memory. Volatile memory includes random-access memory (RAM), which acts as external cache memory. Moreover, RAM is available in many forms such as SRAM, dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM).
The computer system 210 also includes removable/non-removable, volatile/non-volatile computer storage media, such as for example disk storage. The disk storage includes, but is not limited to, devices like a magnetic disk drive, floppy disk drive, tape drive, Jaz drive, Zip drive, LS-60 drive, flash memory card, or memory stick. In addition, the disk storage can include storage media separately or in combination with other storage media including, but not limited to, an optical disc drive such as a compact disc ROM device (CD-ROM), compact disc recordable drive (CD-R Drive), compact disc rewritable drive (CD-RW Drive), or a digital versatile disc ROM drive (DVD-ROM). To facilitate the connection of the disk storage devices to the system bus, a removable or non-removable interface may be employed.
It is to be appreciated that the computer system 210 includes software that acts as an intermediary between users and the basic computer resources described in a suitable operating environment. Such software includes an operating system. The operating system, which can be stored on the disk storage, acts to control and allocate resources of the computer system. System applications take advantage of the management of resources by the operating system through program modules and program data stored either in the system memory or on the disk storage. It is to be appreciated that various components described herein can be implemented with various operating systems or combinations of operating systems.
A user enters commands or information into the computer system 210 through input device(s) coupled to the I/O interface 251. The input devices include, but are not limited to, a pointing device such as a mouse, trackball, stylus, touch pad, keyboard, microphone, joystick, game pad, satellite dish, scanner, TV tuner card, digital camera, digital video camera, web camera, and the like. These and other input devices connect to the processor through the system bus via interface port(s). The interface port(s) include, for example, a serial port, a parallel port, a game port, and a USB. The output device(s) use some of the same types of ports as input device(s). Thus, for example, a USB port may be used to provide input to the computer system and to output information from the computer system to an output device. An output adapter is provided to illustrate that there are some output devices like monitors, displays, speakers, and printers, among other output devices that require special adapters. The output adapters include, by way of illustration and not limitation, video and sound cards that provide a means of connection between the output device and the system bus. It should be noted that other devices and/or systems of devices, such as remote computer(s), provide both input and output capabilities.
The computer system 210 can operate in a networked environment using logical connections to one or more remote computers, such as cloud computer(s), or local computers. The remote cloud computer(s) can be a personal computer, server, router, network PC, workstation, microprocessor-based appliance, peer device, or other common network node, and the like, and typically includes many or all of the elements described relative to the computer system. For purposes of brevity, only a memory storage device is illustrated with the remote computer(s). The remote computer(s) is logically connected to the computer system through a network interface and then physically connected via a communication connection. The network interface encompasses communication networks such as local area networks (LANs) and wide area networks (WANs). LAN technologies include Fiber Distributed Data Interface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet/IEEE 802.3, Token Ring/IEEE 802.5 and the like. WAN technologies include, but are not limited to, point-to-point links, circuit-switching networks like Integrated Services Digital Networks (ISDN) and variations thereon, packet-switching networks, and Digital Subscriber Lines (DSL).
In various aspects, the computer system 210 of
The communication connection(s) refers to the hardware/software employed to connect the network interface to the bus. While the communication connection is shown for illustrative clarity inside the computer system, it can also be external to the computer system 210. The hardware/software necessary for connection to the network interface includes, for illustrative purposes only, internal and external technologies such as modems, including regular telephone-grade modems, cable modems, and DSL modems, ISDN adapters, and Ethernet cards.
The USB network hub 300 device is implemented with a digital state machine instead of a microcontroller, and no firmware programming is required. Fully compliant USB transceivers are integrated into the circuit for the upstream USB transceiver port 302 and all downstream USB transceiver ports 304, 306, 308. The downstream USB transceiver ports 304, 306, 308 support both full-speed and low-speed devices by automatically setting the slew rate according to the speed of the device attached to the ports. The USB network hub 300 device may be configured either in bus-powered or self-powered mode and includes a hub power logic 312 to manage power.
The USB network hub 300 device includes a serial interface engine 310 (SIE). The SIE 310 is the front end of the USB network hub 300 hardware and handles most of the protocol described in chapter 8 of the USB specification. The SIE 310 typically comprehends signaling up to the transaction level. The functions that it handles could include: packet recognition, transaction sequencing, SOP, EOP, RESET, and RESUME signal detection/generation, clock/data separation, non-return-to-zero invert (NRZI) data encoding/decoding and bit-stuffing, CRC generation and checking (token and data), packet ID (PID) generation and checking/decoding, and/or serial-parallel/parallel-serial conversion. The 310 receives a clock input 314 and is coupled to a suspend/resume logic and frame timer 316 circuit and a hub repeater circuit 318 to control communication between the upstream USB transceiver port 302 and the downstream USB transceiver ports 304, 306, 308 through port logic circuits 320, 322, 324. The SIE 310 is coupled to a command decoder 326 via interface logic to control commands from a serial EEPROM via a serial EEPROM interface 330.
In various aspects, the USB network hub 300 can connect 127 functions configured in up to six logical layers (tiers) to a single computer. Further, the USB network hub 300 can connect to all peripherals using a standardized four-wire cable that provides both communication and power distribution. The power configurations are bus-powered and self-powered modes. The USB network hub 300 may be configured to support four modes of power management: a bus-powered hub, with either individual-port power management or ganged-port power management, and the self-powered hub, with either individual-port power management or ganged-port power management. In one aspect, using a USB cable, the USB network hub 300, the upstream USB transceiver port 302 is plugged into a USB host controller, and the downstream USB transceiver ports 304, 306, 308 are exposed for connecting USB compatible devices, and so forth.
In one aspect, the microcontroller 461 may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In one aspect, the main microcontroller 461 may be an LM4F230H5QR ARM Cortex-M4F Processor Core, available from Texas Instruments, for example, comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle SRAM, and internal ROM loaded with StellarisWare® software, a 2 KB EEPROM, one or more PWM modules, one or more QEI analogs, and/or one or more 12-bit ADCs with 12 analog input channels, details of which are available for the product datasheet.
In one aspect, the microcontroller 461 may comprise a safety controller comprising two controller-based families such as TMS570 and RM4x, known under the trade name Hercules ARM Cortex R4, also by Texas Instruments. The safety controller may be configured specifically for IEC 61508 and ISO 26262 safety critical applications, among others, to provide advanced integrated safety features while delivering scalable performance, connectivity, and memory options.
The microcontroller 461 may be programmed to perform various functions such as precise control over the speed and position of the knife, articulation systems, clamp arm, or a combination of the above. In one aspect, the microcontroller 461 includes a processor 462 and a memory 468. The electric motor 482 may be a brushed direct current (DC) motor with a gearbox and mechanical links to an articulation or knife system. In one aspect, a motor driver 492 may be an A3941 available from Allegro Microsystems, Inc. Other motor drivers may be readily substituted for use in the tracking system 480 comprising an absolute positioning system. A detailed description of an absolute positioning system is described in U.S. Patent Application Publication No. 2017/0296213, titled SYSTEMS AND METHODS FOR CONTROLLING A SURGICAL STAPLING AND CUTTING INSTRUMENT, which published on Oct. 19, 2017, which is herein incorporated by reference in its entirety.
The microcontroller 461 may be programmed to provide precise control over the speed and position of displacement members and articulation systems. The microcontroller 461 may be configured to compute a response in the software of the microcontroller 461. The computed response is compared to a measured response of the actual system to obtain an “observed” response, which is used for actual feedback decisions. The observed response is a favorable, tuned value that balances the smooth, continuous nature of the simulated response with the measured response, which can detect outside influences on the system.
In one aspect, the motor 482 may be controlled by the motor driver 492 and can be employed by the firing system of the surgical instrument or tool. In various forms, the motor 482 may be a brushed DC driving motor having a maximum rotational speed of approximately 25,000 RPM. In other arrangements, the motor 482 may include a brushless motor, a cordless motor, a synchronous motor, a stepper motor, or any other suitable electric motor. The motor driver 492 may comprise an H-bridge driver comprising field-effect transistors (FETs), for example. The motor 482 can be powered by a power assembly releasably mounted to the handle assembly or tool housing for supplying control power to the surgical instrument or tool. The power assembly may comprise a battery which may include a number of battery cells connected in series that can be used as the power source to power the surgical instrument or tool. In certain circumstances, the battery cells of the power assembly may be replaceable and/or rechargeable battery cells. In at least one example, the battery cells can be lithium-ion batteries which can be couplable to and separable from the power assembly.
The motor driver 492 may be an A3941 available from Allegro Microsystems, Inc. The A3941 492 is a full-bridge controller for use with external N-channel power metal-oxide semiconductor field-effect transistors (MOSFETs) specifically designed for inductive loads, such as brush DC motors. The driver 492 comprises a unique charge pump regulator that provides full (>10 V) gate drive for battery voltages down to 7 V and allows the A3941 to operate with a reduced gate drive, down to 5.5 V. A bootstrap capacitor may be employed to provide the above battery supply voltage required for N-channel MOSFETs. An internal charge pump for the high-side drive allows DC (100% duty cycle) operation. The full bridge can be driven in fast or slow decay modes using diode or synchronous rectification. In the slow decay mode, current recirculation can be through the high-side or the low-side FETs. The power FETs are protected from shoot-through by resistor-adjustable dead time. Integrated diagnostics provide indications of undervoltage, overtemperature, and power bridge faults and can be configured to protect the power MOSFETs under most short circuit conditions. Other motor drivers may be readily substituted for use in the tracking system 480 comprising an absolute positioning system.
The tracking system 480 comprises a controlled motor drive circuit arrangement comprising a position sensor 472 according to one aspect of this disclosure. The position sensor 472 for an absolute positioning system provides a unique position signal corresponding to the location of a displacement member. In one aspect, the displacement member represents a longitudinally movable drive member comprising a rack of drive teeth for meshing engagement with a corresponding drive gear of a gear reducer assembly. In other aspects, the displacement member represents the firing member, which could be adapted and configured to include a rack of drive teeth. In yet another aspect, the displacement member represents a longitudinal displacement member to open and close a clamp arm, which can be adapted and configured to include a rack of drive teeth. In other aspects, the displacement member represents a clamp arm closure member configured to close and to open a clamp arm of a stapler, ultrasonic, or electrosurgical device, or combinations of the above. Accordingly, as used herein, the term displacement member is used generically to refer to any movable member of the surgical instrument or tool such as the drive member, the clamp arm, or any element that can be displaced. Accordingly, the absolute positioning system can, in effect, track the displacement of the clamp arm by tracking the linear displacement of the longitudinally movable drive member.
In other aspects, the absolute positioning system can be configured to track the position of a clamp arm in the process of closing or opening. In various other aspects, the displacement member may be coupled to any position sensor 472 suitable for measuring linear displacement. Thus, the longitudinally movable drive member, or clamp arm, or combinations thereof, may be coupled to any suitable linear displacement sensor. Linear displacement sensors may include contact or non-contact displacement sensors. Linear displacement sensors may comprise linear variable differential transformers (LVDT), differential variable reluctance transducers (DVRT), a slide potentiometer, a magnetic sensing system comprising a movable magnet and a series of linearly arranged Hall effect sensors, a magnetic sensing system comprising a fixed magnet and a series of movable, linearly arranged Hall effect sensors, an optical sensing system comprising a movable light source and a series of linearly arranged photo diodes or photo detectors, an optical sensing system comprising a fixed light source and a series of movable linearly, arranged photo diodes or photo detectors, or any combination thereof.
The electric motor 482 can include a rotatable shaft that operably interfaces with a gear assembly that is mounted in meshing engagement with a set, or rack, of drive teeth on the displacement member. A sensor element may be operably coupled to a gear assembly such that a single revolution of the position sensor 472 element corresponds to some linear longitudinal translation of the displacement member. An arrangement of gearing and sensors can be connected to the linear actuator, via a rack and pinion arrangement, or a rotary actuator, via a spur gear or other connection. A power source supplies power to the absolute positioning system and an output indicator may display the output of the absolute positioning system. The displacement member represents the longitudinally movable drive member comprising a rack of drive teeth formed thereon for meshing engagement with a corresponding drive gear of the gear reducer assembly. The displacement member represents the longitudinally movable firing member to open and close a clamp arm.
A single revolution of the sensor element associated with the position sensor 472 is equivalent to a longitudinal linear displacement d1 of the of the displacement member, where d1 is the longitudinal linear distance that the displacement member moves from point “a” to point “b” after a single revolution of the sensor element coupled to the displacement member. The sensor arrangement may be connected via a gear reduction that results in the position sensor 472 completing one or more revolutions for the full stroke of the displacement member. The position sensor 472 may complete multiple revolutions for the full stroke of the displacement member.
A series of switches, where n is an integer greater than one, may be employed alone or in combination with a gear reduction to provide a unique position signal for more than one revolution of the position sensor 472. The state of the switches are fed back to the microcontroller 461 that applies logic to determine a unique position signal corresponding to the longitudinal linear displacement d1+d2+ . . . dn of the displacement member. The output of the position sensor 472 is provided to the microcontroller 461. The position sensor 472 of the sensor arrangement may comprise a magnetic sensor, an analog rotary sensor like a potentiometer, or an array of analog Hall-effect elements, which output a unique combination of position signals or values.
The position sensor 472 may comprise any number of magnetic sensing elements, such as, for example, magnetic sensors classified according to whether they measure the total magnetic field or the vector components of the magnetic field. The techniques used to produce both types of magnetic sensors encompass many aspects of physics and electronics. The technologies used for magnetic field sensing include search coil, fluxgate, optically pumped, nuclear precession, SQUID, Hall-effect, anisotropic magnetoresistance, giant magnetoresistance, magnetic tunnel junctions, giant magnetoimpedance, magnetostrictive/piezoelectric composites, magnetodiode, magnetotransistor, fiber-optic, magneto-optic, and microelectromechanical systems-based magnetic sensors, among others.
In one aspect, the position sensor 472 for the tracking system 480 comprising an absolute positioning system comprises a magnetic rotary absolute positioning system. The position sensor 472 may be implemented as an AS5055EQFT single-chip magnetic rotary position sensor available from Austria Microsystems, AG. The position sensor 472 is interfaced with the microcontroller 461 to provide an absolute positioning system. The position sensor 472 is a low-voltage and low-power component and includes four Hall-effect elements in an area of the position sensor 472 that is located above a magnet. A high-resolution ADC and a smart power management controller are also provided on the chip. A coordinate rotation digital computer (CORDIC) processor, also known as the digit-by-digit method and Volder's algorithm, is provided to implement a simple and efficient algorithm to calculate hyperbolic and trigonometric functions that require only addition, subtraction, bitshift, and table lookup operations. The angle position, alarm bits, and magnetic field information are transmitted over a standard serial communication interface, such as a serial peripheral interface (SPI) interface, to the microcontroller 461. The position sensor 472 provides 12 or 14 bits of resolution. The position sensor 472 may be an AS5055 chip provided in a small QFN 16-pin 4×4×0.85 mm package.
The tracking system 480 comprising an absolute positioning system may comprise and/or be programmed to implement a feedback controller, such as a PID, state feedback, and adaptive controller. A power source converts the signal from the feedback controller into a physical input to the system: in this case the voltage. Other examples include a PWM of the voltage, current, and force. Other sensor(s) may be provided to measure physical parameters of the physical system in addition to the position measured by the position sensor 472. In some aspects, the other sensor(s) can include sensor arrangements such as those described in U.S. Pat. No. 9,345,481, titled STAPLE CARTRIDGE TISSUE THICKNESS SENSOR SYSTEM, which issued on May 24, 2016, which is herein incorporated by reference in its entirety; U.S. Patent Application Publication No. 2014/0263552, titled STAPLE CARTRIDGE TISSUE THICKNESS SENSOR SYSTEM, which published on Sep. 18, 2014, which is herein incorporated by reference in its entirety; and U.S. patent application Ser. No. 15/628,175, titled TECHNIQUES FOR ADAPTIVE CONTROL OF MOTOR VELOCITY OF A SURGICAL STAPLING AND CUTTING INSTRUMENT, filed Jun. 20, 2017, which is herein incorporated by reference in its entirety. In a digital signal processing system, an absolute positioning system is coupled to a digital data acquisition system where the output of the absolute positioning system will have a finite resolution and sampling frequency. The absolute positioning system may comprise a compare-and-combine circuit to combine a computed response with a measured response using algorithms, such as a weighted average and a theoretical control loop, that drive the computed response towards the measured response. The computed response of the physical system takes into account properties like mass, inertia, viscous friction, inductance resistance, etc., to predict what the states and outputs of the physical system will be by knowing the input.
The absolute positioning system provides an absolute position of the displacement member upon power-up of the instrument, without retracting or advancing the displacement member to a reset (zero or home) position as may be required with conventional rotary encoders that merely count the number of steps forwards or backwards that the motor 482 has taken to infer the position of a device actuator, drive bar, knife, or the like.
A sensor 474, such as, for example, a strain gauge or a micro-strain gauge, is configured to measure one or more parameters of the end effector, such as, for example, the amplitude of the strain exerted on the anvil during a clamping operation, which can be indicative of the closure forces applied to the anvil. The measured strain is converted to a digital signal and provided to the processor 462. Alternatively, or in addition to the sensor 474, a sensor 476, such as, for example, a load sensor, can measure the closure force applied by the closure drive system to the anvil in a stapler or a clamp arm in an ultrasonic or electrosurgical instrument. The sensor 476, such as, for example, a load sensor, can measure the firing force applied to a closure member coupled to a clamp arm of the surgical instrument or tool or the force applied by a clamp arm to tissue located in the jaws of an ultrasonic or electrosurgical instrument. Alternatively, a current sensor 478 can be employed to measure the current drawn by the motor 482. The displacement member also may be configured to engage a clamp arm to open or close the clamp arm. The force sensor may be configured to measure the clamping force on tissue. The force required to advance the displacement member can correspond to the current drawn by the motor 482, for example. The measured force is converted to a digital signal and provided to the processor 462.
In one form, the strain gauge sensor 474 can be used to measure the force applied to the tissue by the end effector. A strain gauge can be coupled to the end effector to measure the force on the tissue being treated by the end effector. A system for measuring forces applied to the tissue grasped by the end effector comprises a strain gauge sensor 474, such as, for example, a micro-strain gauge, that is configured to measure one or more parameters of the end effector, for example. In one aspect, the strain gauge sensor 474 can measure the amplitude or magnitude of the strain exerted on a jaw member of an end effector 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 462 of the microcontroller 461. A load sensor 476 can measure the force used to operate the knife element, for example, to cut the tissue captured between the anvil and the staple cartridge. A load sensor 476 can measure the force used to operate the clamp arm element, for example, to capture tissue between the clamp arm and an ultrasonic blade or to capture tissue between the clamp arm and a jaw of an electrosurgical instrument. A magnetic field sensor can be employed to measure the thickness of the captured tissue. The measurement of the magnetic field sensor also may be converted to a digital signal and provided to the processor 462.
The measurements of the tissue compression, the tissue thickness, and/or the force required to close the end effector on the tissue, as respectively measured by the sensors 474, 476, can be used by the microcontroller 461 to characterize the selected position of the firing member and/or the corresponding value of the speed of the firing member. In one instance, a memory 468 may store a technique, an equation, and/or a lookup table which can be employed by the microcontroller 461 in the assessment.
The control system 470 of the surgical instrument or tool also may comprise wired or wireless communication circuits to communicate with the modular communication hub as shown in
In certain instances, the surgical instrument system or tool may include a firing motor 602. The firing motor 602 may be operably coupled to a firing motor drive assembly 604 which can be configured to transmit firing motions, generated by the motor 602 to the end effector, in particular to displace the clamp arm closure member. The closure member may be retracted by reversing the direction of the motor 602, which also causes the clamp arm to open.
In certain instances, the surgical instrument or tool may include a closure motor 603. The closure motor 603 may be operably coupled to a closure motor drive assembly 605 which can be configured to transmit closure motions, generated by the motor 603 to the end effector, in particular to displace a closure tube to close the anvil and compress tissue between the anvil and the staple cartridge. The closure motor 603 may be operably coupled to a closure motor drive assembly 605 which can be configured to transmit closure motions, generated by the motor 603 to the end effector, in particular to displace a closure tube to close the clamp arm and compress tissue between the clamp arm and either an ultrasonic blade or jaw member of an electrosurgical device. The closure motions may cause the end effector to transition from an open configuration to an approximated configuration to capture tissue, for example. The end effector may be transitioned to an open position by reversing the direction of the motor 603.
In certain instances, the surgical instrument or tool may include one or more articulation motors 606a, 606b, for example. The motors 606a, 606b may be operably coupled to respective articulation motor drive assemblies 608a, 608b, which can be configured to transmit articulation motions generated by the motors 606a, 606b to the end effector. In certain instances, the articulation motions may cause the end effector to articulate relative to the shaft, for example.
As described above, the surgical instrument or tool may include a plurality of motors which may be configured to perform various independent functions. In certain instances, the plurality of motors of the surgical instrument or tool can be individually or separately activated to perform one or more functions while the other motors remain inactive. For example, the articulation motors 606a, 606b can be activated to cause the end effector to be articulated while the firing motor 602 remains inactive. Alternatively, the firing motor 602 can be activated to fire the plurality of staples, and/or to advance the cutting edge, while the articulation motor 606 remains inactive. Furthermore, the closure motor 603 may be activated simultaneously with the firing motor 602 to cause the closure tube or closure member to advance distally as described in more detail hereinbelow.
In certain instances, the surgical instrument or tool may include a common control module 610 which can be employed with a plurality of motors of the surgical instrument or tool. In certain instances, the common control module 610 may accommodate one of the plurality of motors at a time. For example, the common control module 610 can be couplable to and separable from the plurality of motors of the robotic surgical instrument individually. In certain instances, a plurality of the motors of the surgical instrument or tool may share one or more common control modules such as the common control module 610. In certain instances, a plurality of motors of the surgical instrument or tool can be individually and selectively engaged with the common control module 610. In certain instances, the common control module 610 can be selectively switched from interfacing with one of a plurality of motors of the surgical instrument or tool to interfacing with another one of the plurality of motors of the surgical instrument or tool.
In at least one example, the common control module 610 can be selectively switched between operable engagement with the articulation motors 606a, 606b and operable engagement with either the firing motor 602 or the closure motor 603. In at least one example, as illustrated in
Each of the motors 602, 603, 606a, 606b may comprise a torque sensor to measure the output torque on the shaft of the motor. The force on an end effector may be sensed in any conventional manner, such as by force sensors on the outer sides of the jaws or by a torque sensor for the motor actuating the jaws.
In various instances, as illustrated in
In certain instances, the microcontroller 620 may include a microprocessor 622 (the “processor”) and one or more non-transitory computer-readable mediums or memory units 624 (the “memory”). In certain instances, the memory 624 may store various program instructions, which when executed may cause the processor 622 to perform a plurality of functions and/or calculations described herein. In certain instances, one or more of the memory units 624 may be coupled to the processor 622, for example. In various aspects, the microcontroller 620 may communicate over a wired or wireless channel, or combinations thereof.
In certain instances, the power source 628 can be employed to supply power to the microcontroller 620, for example. In certain instances, the power source 628 may comprise a battery (or “battery pack” or “power pack”), such as a lithium-ion battery, for example. In certain instances, the battery pack may be configured to be releasably mounted to a handle for supplying power to the surgical instrument 600. A number of battery cells connected in series may be used as the power source 628. In certain instances, the power source 628 may be replaceable and/or rechargeable, for example.
In various instances, the processor 622 may control the motor driver 626 to control the position, direction of rotation, and/or velocity of a motor that is coupled to the common control module 610. In certain instances, the processor 622 can signal the motor driver 626 to stop and/or disable a motor that is coupled to the common control module 610. It should be understood that the term “processor” as used herein includes any suitable microprocessor, microcontroller, or other basic computing device that incorporates the functions of a computer's central processing unit (CPU) on an integrated circuit or, at most, a few integrated circuits. The processor 622 is a multipurpose, programmable device that accepts digital data as input, processes it according to instructions stored in its memory, and provides results as output. It is an example of sequential digital logic, as it has internal memory. Processors operate on numbers and symbols represented in the binary numeral system.
In one instance, the processor 622 may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In certain instances, the microcontroller 620 may be an LM4F230H5QR, available from Texas Instruments, for example. In at least one example, the Texas Instruments LM4F230H5QR is an ARM Cortex-M4F Processor Core comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle SRAM, an internal ROM loaded with StellarisWare® software, a 2 KB EEPROM, one or more PWM modules, one or more QEI analogs, one or more 12-bit ADCs with 12 analog input channels, among other features that are readily available for the product datasheet. Other microcontrollers may be readily substituted for use with the module 4410. Accordingly, the present disclosure should not be limited in this context.
In certain instances, the memory 624 may include program instructions for controlling each of the motors of the surgical instrument 600 that are couplable to the common control module 610. For example, the memory 624 may include program instructions for controlling the firing motor 602, the closure motor 603, and the articulation motors 606a, 606b. Such program instructions may cause the processor 622 to control the firing, closure, and articulation functions in accordance with inputs from algorithms or control programs of the surgical instrument or tool.
In certain instances, one or more mechanisms and/or sensors such as, for example, sensors 630 can be employed to alert the processor 622 to the program instructions that should be used in a particular setting. For example, the sensors 630 may alert the processor 622 to use the program instructions associated with firing, closing, and articulating the end effector. In certain instances, the sensors 630 may comprise position sensors which can be employed to sense the position of the switch 614, for example. Accordingly, the processor 622 may use the program instructions associated with firing the closure member coupled to the clamp arm of the end effector upon detecting, through the sensors 630 for example, that the switch 614 is in the first position 616; the processor 622 may use the program instructions associated with closing the anvil upon detecting, through the sensors 630 for example, that the switch 614 is in the second position 617; and the processor 622 may use the program instructions associated with articulating the end effector upon detecting, through the sensors 630 for example, that the switch 614 is in the third or fourth position 618a, 618b.
In one aspect, the robotic surgical instrument 700 comprises a control circuit 710 configured to control a clamp arm 716 and a closure member 714 portion of an end effector 702, an ultrasonic blade 718 coupled to an ultrasonic transducer 719 excited by an ultrasonic generator 721, a shaft 740, and one or more articulation members 742a, 742b via a plurality of motors 704a-704e. A position sensor 734 may be configured to provide position feedback of the closure member 714 to the control circuit 710. Other sensors 738 may be configured to provide feedback to the control circuit 710. A timer/counter 731 provides timing and counting information to the control circuit 710. An energy source 712 may be provided to operate the motors 704a-704e, and a current sensor 736 provides motor current feedback to the control circuit 710. The motors 704a-704e can be operated individually by the control circuit 710 in an open-loop or closed-loop feedback control.
In one aspect, the control circuit 710 may comprise one or more microcontrollers, microprocessors, or other suitable processors for executing instructions that cause the processor or processors to perform one or more tasks. In one aspect, a timer/counter 731 provides an output signal, such as the elapsed time or a digital count, to the control circuit 710 to correlate the position of the closure member 714 as determined by the position sensor 734 with the output of the timer/counter 731 such that the control circuit 710 can determine the position of the closure member 714 at a specific time (t) relative to a starting position or the time (t) when the closure member 714 is at a specific position relative to a starting position. The timer/counter 731 may be configured to measure elapsed time, count external events, or time external events.
In one aspect, the control circuit 710 may be programmed to control functions of the end effector 702 based on one or more tissue conditions. The control circuit 710 may be programmed to sense tissue conditions, such as thickness, either directly or indirectly, as described herein. The control circuit 710 may be programmed to select a firing control program or closure control program based on tissue conditions. A firing control program may describe the distal motion of the displacement member. Different firing control programs may be selected to better treat different tissue conditions. For example, when thicker tissue is present, the control circuit 710 may be programmed to translate the displacement member at a lower velocity and/or with lower power. When thinner tissue is present, the control circuit 710 may be programmed to translate the displacement member at a higher velocity and/or with higher power. A closure control program may control the closure force applied to the tissue by the clamp arm 716. Other control programs control the rotation of the shaft 740 and the articulation members 742a, 742b.
In one aspect, the control circuit 710 may generate motor set point signals. The motor set point signals may be provided to various motor controllers 708a-708e. The motor controllers 708a-708e may comprise one or more circuits configured to provide motor drive signals to the motors 704a-704e to drive the motors 704a-704e as described herein. In some examples, the motors 704a-704e may be brushed DC electric motors. For example, the velocity of the motors 704a-704e may be proportional to the respective motor drive signals. In some examples, the motors 704a-704e may be brushless DC electric motors, and the respective motor drive signals may comprise a PWM signal provided to one or more stator windings of the motors 704a-704e. Also, in some examples, the motor controllers 708a-708e may be omitted and the control circuit 710 may generate the motor drive signals directly.
In one aspect, the control circuit 710 may initially operate each of the motors 704a-704e in an open-loop configuration for a first open-loop portion of a stroke of the displacement member. Based on the response of the robotic surgical instrument 700 during the open-loop portion of the stroke, the control circuit 710 may select a firing control program in a closed-loop configuration. The response of the instrument may include a translation distance of the displacement member during the open-loop portion, a time elapsed during the open-loop portion, the energy provided to one of the motors 704a-704e during the open-loop portion, a sum of pulse widths of a motor drive signal, etc. After the open-loop portion, the control circuit 710 may implement the selected firing control program for a second portion of the displacement member stroke. For example, during a closed-loop portion of the stroke, the control circuit 710 may modulate one of the motors 704a-704e based on translation data describing a position of the displacement member in a closed-loop manner to translate the displacement member at a constant velocity.
In one aspect, the motors 704a-704e may receive power from an energy source 712. The energy source 712 may be a DC power supply driven by a main alternating current power source, a battery, a super capacitor, or any other suitable energy source. The motors 704a-704e may be mechanically coupled to individual movable mechanical elements such as the closure member 714, clamp arm 716, shaft 740, articulation 742a, and articulation 742b via respective transmissions 706a-706e. The transmissions 706a-706e may include one or more gears or other linkage components to couple the motors 704a-704e to movable mechanical elements. A position sensor 734 may sense a position of the closure member 714. The position sensor 734 may be or include any type of sensor that is capable of generating position data that indicate a position of the closure member 714. In some examples, the position sensor 734 may include an encoder configured to provide a series of pulses to the control circuit 710 as the closure member 714 translates distally and proximally. The control circuit 710 may track the pulses to determine the position of the closure member 714. Other suitable position sensors may be used, including, for example, a proximity sensor. Other types of position sensors may provide other signals indicating motion of the closure member 714. Also, in some examples, the position sensor 734 may be omitted. Where any of the motors 704a-704e is a stepper motor, the control circuit 710 may track the position of the closure member 714 by aggregating the number and direction of steps that the motor 704 has been instructed to execute. The position sensor 734 may be located in the end effector 702 or at any other portion of the instrument. The outputs of each of the motors 704a-704e include a torque sensor 744a-744e to sense force and have an encoder to sense rotation of the drive shaft.
In one aspect, the control circuit 710 is configured to drive a firing member such as the closure member 714 portion of the end effector 702. The control circuit 710 provides a motor set point to a motor control 708a, which provides a drive signal to the motor 704a. The output shaft of the motor 704a is coupled to a torque sensor 744a. The torque sensor 744a is coupled to a transmission 706a which is coupled to the closure member 714. The transmission 706a comprises movable mechanical elements such as rotating elements and a firing member to control the movement of the closure member 714 distally and proximally along a longitudinal axis of the end effector 702. In one aspect, the motor 704a may be coupled to the knife gear assembly, which includes a knife gear reduction set that includes a first knife drive gear and a second knife drive gear. A torque sensor 744a provides a firing force feedback signal to the control circuit 710. The firing force signal represents the force required to fire or displace the closure member 714. A position sensor 734 may be configured to provide the position of the closure member 714 along the firing stroke or the position of the firing member as a feedback signal to the control circuit 710. The end effector 702 may include additional sensors 738 configured to provide feedback signals to the control circuit 710. When ready to use, the control circuit 710 may provide a firing signal to the motor control 708a. In response to the firing signal, the motor 704a may drive the firing member distally along the longitudinal axis of the end effector 702 from a proximal stroke start position to a stroke end position distal to the stroke start position. As the closure member 714 translates distally, the clamp arm 716 closes towards the ultrasonic blade 718.
In one aspect, the control circuit 710 is configured to drive a closure member such as the clamp arm 716 portion of the end effector 702. The control circuit 710 provides a motor set point to a motor control 708b, which provides a drive signal to the motor 704b. The output shaft of the motor 704b is coupled to a torque sensor 744b. The torque sensor 744b is coupled to a transmission 706b which is coupled to the clamp arm 716. The transmission 706b comprises movable mechanical elements such as rotating elements and a closure member to control the movement of the clamp arm 716 from the open and closed positions. In one aspect, the motor 704b is coupled to a closure gear assembly, which includes a closure reduction gear set that is supported in meshing engagement with the closure spur gear. The torque sensor 744b provides a closure force feedback signal to the control circuit 710. The closure force feedback signal represents the closure force applied to the clamp arm 716. The position sensor 734 may be configured to provide the position of the closure member as a feedback signal to the control circuit 710. Additional sensors 738 in the end effector 702 may provide the closure force feedback signal to the control circuit 710. The pivotable clamp arm 716 is positioned opposite the ultrasonic blade 718. When ready to use, the control circuit 710 may provide a closure signal to the motor control 708b. In response to the closure signal, the motor 704b advances a closure member to grasp tissue between the clamp arm 716 and the ultrasonic blade 718.
In one aspect, the control circuit 710 is configured to rotate a shaft member such as the shaft 740 to rotate the end effector 702. The control circuit 710 provides a motor set point to a motor control 708c, which provides a drive signal to the motor 704c. The output shaft of the motor 704c is coupled to a torque sensor 744c. The torque sensor 744c is coupled to a transmission 706c which is coupled to the shaft 740. The transmission 706c comprises movable mechanical elements such as rotating elements to control the rotation of the shaft 740 clockwise or counterclockwise up to and over 360°. In one aspect, the motor 704c is coupled to the rotational transmission assembly, which includes a tube gear segment that is formed on (or attached to) the proximal end of the proximal closure tube for operable engagement by a rotational gear assembly that is operably supported on the tool mounting plate. The torque sensor 744c provides a rotation force feedback signal to the control circuit 710. The rotation force feedback signal represents the rotation force applied to the shaft 740. The position sensor 734 may be configured to provide the position of the closure member as a feedback signal to the control circuit 710. Additional sensors 738 such as a shaft encoder may provide the rotational position of the shaft 740 to the control circuit 710.
In one aspect, the control circuit 710 is configured to articulate the end effector 702. The control circuit 710 provides a motor set point to a motor control 708d, which provides a drive signal to the motor 704d. The output shaft of the motor 704d is coupled to a torque sensor 744d. The torque sensor 744d is coupled to a transmission 706d which is coupled to an articulation member 742a. The transmission 706d comprises movable mechanical elements such as articulation elements to control the articulation of the end effector 702 ±65°. In one aspect, the motor 704d is coupled to an articulation nut, which is rotatably journaled on the proximal end portion of the distal spine portion and is rotatably driven thereon by an articulation gear assembly. The torque sensor 744d provides an articulation force feedback signal to the control circuit 710. The articulation force feedback signal represents the articulation force applied to the end effector 702. Sensors 738, such as an articulation encoder, may provide the articulation position of the end effector 702 to the control circuit 710.
In another aspect, the articulation function of the robotic surgical system 700 may comprise two articulation members, or links, 742a, 742b. These articulation members 742a, 742b are driven by separate disks on the robot interface (the rack) which are driven by the two motors 708d, 708e. When the separate firing motor 704a is provided, each of articulation links 742a, 742b can be antagonistically driven with respect to the other link in order to provide a resistive holding motion and a load to the head when it is not moving and to provide an articulation motion as the head is articulated. The articulation members 742a, 742b attach to the head at a fixed radius as the head is rotated. Accordingly, the mechanical advantage of the push-and-pull link changes as the head is rotated. This change in the mechanical advantage may be more pronounced with other articulation link drive systems.
In one aspect, the one or more motors 704a-704e may comprise a brushed DC motor with a gearbox and mechanical links to a firing member, closure member, or articulation member. Another example includes electric motors 704a-704e that operate the movable mechanical elements such as the displacement member, articulation links, closure tube, and shaft. An outside influence is an unmeasured, unpredictable influence of things like tissue, surrounding bodies, and friction on the physical system. Such outside influence can be referred to as drag, which acts in opposition to one of electric motors 704a-704e. The outside influence, such as drag, may cause the operation of the physical system to deviate from a desired operation of the physical system.
In one aspect, the position sensor 734 may be implemented as an absolute positioning system. In one aspect, the position sensor 734 may comprise a magnetic rotary absolute positioning system implemented as an AS5055EQFT single-chip magnetic rotary position sensor available from Austria Microsystems, AG. The position sensor 734 may interface with the control circuit 710 to provide an absolute positioning system. The position may include multiple Hall-effect elements located above a magnet and coupled to a CORDIC processor, also known as the digit-by-digit method and Volder's algorithm, that is provided to implement a simple and efficient algorithm to calculate hyperbolic and trigonometric functions that require only addition, subtraction, bitshift, and table lookup operations.
In one aspect, the control circuit 710 may be in communication with one or more sensors 738. The sensors 738 may be positioned on the end effector 702 and adapted to operate with the robotic surgical instrument 700 to measure the various derived parameters such as the gap distance versus time, tissue compression versus time, and anvil strain versus time. The sensors 738 may comprise a magnetic sensor, a magnetic field sensor, a strain gauge, a load cell, a pressure sensor, a force sensor, a torque sensor, an inductive sensor such as an eddy current sensor, a resistive sensor, a capacitive sensor, an optical sensor, and/or any other suitable sensor for measuring one or more parameters of the end effector 702. The sensors 738 may include one or more sensors. The sensors 738 may be located on the clamp arm 716 to determine tissue location using segmented electrodes. The torque sensors 744a-744e may be configured to sense force such as firing force, closure force, and/or articulation force, among others. Accordingly, the control circuit 710 can sense (1) the closure load experienced by the distal closure tube and its position, (2) the firing member at the rack and its position, (3) what portion of the ultrasonic blade 718 has tissue on it, and (4) the load and position on both articulation rods.
In one aspect, the one or more sensors 738 may comprise a strain gauge, such as a micro-strain gauge, configured to measure the magnitude of the strain in the clamp arm 716 during a clamped condition. The strain gauge provides an electrical signal whose amplitude varies with the magnitude of the strain. The sensors 738 may comprise a pressure sensor configured to detect a pressure generated by the presence of compressed tissue between the clamp arm 716 and the ultrasonic blade 718. The sensors 738 may be configured to detect impedance of a tissue section located between the clamp arm 716 and the ultrasonic blade 718 that is indicative of the thickness and/or fullness of tissue located therebetween.
In one aspect, the sensors 738 may be implemented as one or more limit switches, electromechanical devices, solid-state switches, Hall-effect devices, magneto-resistive (MR) devices, giant magneto-resistive (GMR) devices, magnetometers, among others. In other implementations, the sensors 738 may be implemented as solid-state switches that operate under the influence of light, such as optical sensors, IR sensors, ultraviolet sensors, among others. Still, the switches may be solid-state devices such as transistors (e.g., FET, junction FET, MOSFET, bipolar, and the like). In other implementations, the sensors 738 may include electrical conductorless switches, ultrasonic switches, accelerometers, and inertial sensors, among others.
In one aspect, the sensors 738 may be configured to measure forces exerted on the clamp arm 716 by the closure drive system. For example, one or more sensors 738 can be at an interaction point between the closure tube and the clamp arm 716 to detect the closure forces applied by the closure tube to the clamp arm 716. The forces exerted on the clamp arm 716 can be representative of the tissue compression experienced by the tissue section captured between the clamp arm 716 and the ultrasonic blade 718. The one or more sensors 738 can be positioned at various interaction points along the closure drive system to detect the closure forces applied to the clamp arm 716 by the closure drive system. The one or more sensors 738 may be sampled in real time during a clamping operation by the processor of the control circuit 710. The control circuit 710 receives real-time sample measurements to provide and analyze time-based information and assess, in real time, closure forces applied to the clamp arm 716.
In one aspect, a current sensor 736 can be employed to measure the current drawn by each of the motors 704a-704e. The force required to advance any of the movable mechanical elements such as the closure member 714 corresponds to the current drawn by one of the motors 704a-704e. The force is converted to a digital signal and provided to the control circuit 710. The control circuit 710 can be configured to simulate the response of the actual system of the instrument in the software of the controller. A displacement member can be actuated to move the closure member 714 in the end effector 702 at or near a target velocity. The robotic surgical instrument 700 can include a feedback controller, which can be one of any feedback controllers, including, but not limited to a PID, a state feedback, a linear-quadratic (LQR), and/or an adaptive controller, for example. The robotic surgical instrument 700 can include a power source to convert the signal from the feedback controller into a physical input such as case voltage, PWM voltage, frequency modulated voltage, current, torque, and/or force, for example. Additional details are disclosed in U.S. patent application Ser. No. 15/636,829, titled CLOSED LOOP VELOCITY CONTROL TECHNIQUES FOR ROBOTIC SURGICAL INSTRUMENT, filed Jun. 29, 2017, which is herein incorporated by reference in its entirety.
The position, movement, displacement, and/or translation of a linear displacement member, such as the closure member 764, can be measured by an absolute positioning system, sensor arrangement, and position sensor 784. Because the closure member 764 is coupled to a longitudinally movable drive member, the position of the closure member 764 can be determined by measuring the position of the longitudinally movable drive member employing the position sensor 784. Accordingly, in the following description, the position, displacement, and/or translation of the closure member 764 can be achieved by the position sensor 784 as described herein. A control circuit 760 may be programmed to control the translation of the displacement member, such as the closure member 764. The control circuit 760, in some examples, may comprise one or more microcontrollers, microprocessors, or other suitable processors for executing instructions that cause the processor or processors to control the displacement member, e.g., the closure member 764, in the manner described. In one aspect, a timer/counter 781 provides an output signal, such as the elapsed time or a digital count, to the control circuit 760 to correlate the position of the closure member 764 as determined by the position sensor 784 with the output of the timer/counter 781 such that the control circuit 760 can determine the position of the closure member 764 at a specific time (t) relative to a starting position. The timer/counter 781 may be configured to measure elapsed time, count external events, or time external events.
The control circuit 760 may generate a motor set point signal 772. The motor set point signal 772 may be provided to a motor controller 758. The motor controller 758 may comprise one or more circuits configured to provide a motor drive signal 774 to the motor 754 to drive the motor 754 as described herein. In some examples, the motor 754 may be a brushed DC electric motor. For example, the velocity of the motor 754 may be proportional to the motor drive signal 774. In some examples, the motor 754 may be a brushless DC electric motor and the motor drive signal 774 may comprise a PWM signal provided to one or more stator windings of the motor 754. Also, in some examples, the motor controller 758 may be omitted, and the control circuit 760 may generate the motor drive signal 774 directly.
The motor 754 may receive power from an energy source 762. The energy source 762 may be or include a battery, a super capacitor, or any other suitable energy source. The motor 754 may be mechanically coupled to the closure member 764 via a transmission 756. The transmission 756 may include one or more gears or other linkage components to couple the motor 754 to the closure member 764. A position sensor 784 may sense a position of the closure member 764. The position sensor 784 may be or include any type of sensor that is capable of generating position data that indicate a position of the closure member 764. In some examples, the position sensor 784 may include an encoder configured to provide a series of pulses to the control circuit 760 as the closure member 764 translates distally and proximally. The control circuit 760 may track the pulses to determine the position of the closure member 764. Other suitable position sensors may be used, including, for example, a proximity sensor. Other types of position sensors may provide other signals indicating motion of the closure member 764. Also, in some examples, the position sensor 784 may be omitted. Where the motor 754 is a stepper motor, the control circuit 760 may track the position of the closure member 764 by aggregating the number and direction of steps that the motor 754 has been instructed to execute. The position sensor 784 may be located in the end effector 752 or at any other portion of the instrument.
The control circuit 760 may be in communication with one or more sensors 788. The sensors 788 may be positioned on the end effector 752 and adapted to operate with the surgical instrument 750 to measure the various derived parameters such as gap distance versus time, tissue compression versus time, and anvil strain versus time. The sensors 788 may comprise a magnetic sensor, a magnetic field sensor, a strain gauge, a pressure sensor, a force sensor, an inductive sensor such as an eddy current sensor, a resistive sensor, a capacitive sensor, an optical sensor, and/or any other suitable sensor for measuring one or more parameters of the end effector 752. The sensors 788 may include one or more sensors.
The one or more sensors 788 may comprise a strain gauge, such as a micro-strain gauge, configured to measure the magnitude of the strain in the clamp arm 766 during a clamped condition. The strain gauge provides an electrical signal whose amplitude varies with the magnitude of the strain. The sensors 788 may comprise a pressure sensor configured to detect a pressure generated by the presence of compressed tissue between the clamp arm 766 and the ultrasonic blade 768. The sensors 788 may be configured to detect impedance of a tissue section located between the clamp arm 766 and the ultrasonic blade 768 that is indicative of the thickness and/or fullness of tissue located therebetween.
The sensors 788 may be is configured to measure forces exerted on the clamp arm 766 by a closure drive system. For example, one or more sensors 788 can be at an interaction point between a closure tube and the clamp arm 766 to detect the closure forces applied by a closure tube to the clamp arm 766. The forces exerted on the clamp arm 766 can be representative of the tissue compression experienced by the tissue section captured between the clamp arm 766 and the ultrasonic blade 768. The one or more sensors 788 can be positioned at various interaction points along the closure drive system to detect the closure forces applied to the clamp arm 766 by the closure drive system. The one or more sensors 788 may be sampled in real time during a clamping operation by a processor of the control circuit 760. The control circuit 760 receives real-time sample measurements to provide and analyze time-based information and assess, in real time, closure forces applied to the clamp arm 766.
A current sensor 786 can be employed to measure the current drawn by the motor 754. The force required to advance the closure member 764 corresponds to the current drawn by the motor 754. The force is converted to a digital signal and provided to the control circuit 760.
The control circuit 760 can be configured to simulate the response of the actual system of the instrument in the software of the controller. A displacement member can be actuated to move a closure member 764 in the end effector 752 at or near a target velocity. The surgical instrument 750 can include a feedback controller, which can be one of any feedback controllers, including, but not limited to a PID, a state feedback, LQR, and/or an adaptive controller, for example. The surgical instrument 750 can include a power source to convert the signal from the feedback controller into a physical input such as case voltage, PWM voltage, frequency modulated voltage, current, torque, and/or force, for example.
The actual drive system of the surgical instrument 750 is configured to drive the displacement member, cutting member, or closure member 764, by a brushed DC motor with gearbox and mechanical links to an articulation and/or knife system. Another example is the electric motor 754 that operates the displacement member and the articulation driver, for example, of an interchangeable shaft assembly. An outside influence is an unmeasured, unpredictable influence of things like tissue, surrounding bodies and friction on the physical system. Such outside influence can be referred to as drag which acts in opposition to the electric motor 754. The outside influence, such as drag, may cause the operation of the physical system to deviate from a desired operation of the physical system.
Various example aspects are directed to a surgical instrument 750 comprising an end effector 752 with motor-driven surgical sealing and cutting implements. For example, a motor 754 may drive a displacement member distally and proximally along a longitudinal axis of the end effector 752. The end effector 752 may comprise a pivotable clamp arm 766 and, when configured for use, an ultrasonic blade 768 positioned opposite the clamp arm 766. A clinician may grasp tissue between the clamp arm 766 and the ultrasonic blade 768, as described herein. When ready to use the instrument 750, the clinician may provide a firing signal, for example by depressing a trigger of the instrument 750. In response to the firing signal, the motor 754 may drive the displacement member distally along the longitudinal axis of the end effector 752 from a proximal stroke begin position to a stroke end position distal of the stroke begin position. As the displacement member translates distally, the closure member 764 with a cutting element positioned at a distal end, may cut the tissue between the ultrasonic blade 768 and the clamp arm 766.
In various examples, the surgical instrument 750 may comprise a control circuit 760 programmed to control the distal translation of the displacement member, such as the closure member 764, for example, based on one or more tissue conditions. The control circuit 760 may be programmed to sense tissue conditions, such as thickness, either directly or indirectly, as described herein. The control circuit 760 may be programmed to select a control program based on tissue conditions. A control program may describe the distal motion of the displacement member. Different control programs may be selected to better treat different tissue conditions. For example, when thicker tissue is present, the control circuit 760 may be programmed to translate the displacement member at a lower velocity and/or with lower power. When thinner tissue is present, the control circuit 760 may be programmed to translate the displacement member at a higher velocity and/or with higher power.
In some examples, the control circuit 760 may initially operate the motor 754 in an open loop configuration for a first open loop portion of a stroke of the displacement member. Based on a response of the instrument 750 during the open loop portion of the stroke, the control circuit 760 may select a firing control program. The response of the instrument may include, a translation distance of the displacement member during the open loop portion, a time elapsed during the open loop portion, energy provided to the motor 754 during the open loop portion, a sum of pulse widths of a motor drive signal, etc. After the open loop portion, the control circuit 760 may implement the selected firing control program for a second portion of the displacement member stroke. For example, during the closed loop portion of the stroke, the control circuit 760 may modulate the motor 754 based on translation data describing a position of the displacement member in a closed loop manner to translate the displacement member at a constant velocity. Additional details are disclosed in U.S. patent application Ser. No. 15/720,852, titled SYSTEM AND METHODS FOR CONTROLLING A DISPLAY OF A SURGICAL INSTRUMENT, filed Sep. 29, 2017, which is herein incorporated by reference in its entirety.
In one aspect, sensors 788 may be implemented as a limit switch, electromechanical device, solid-state switches, Hall-effect devices, MR devices, GMR devices, magnetometers, among others. In other implementations, the sensors 638 may be solid-state switches that operate under the influence of light, such as optical sensors, IR sensors, ultraviolet sensors, among others. Still, the switches may be solid-state devices such as transistors (e.g., FET, junction FET, MOSFET, bipolar, and the like). In other implementations, the sensors 788 may include electrical conductorless switches, ultrasonic switches, accelerometers, and inertial sensors, among others.
In one aspect, the position sensor 784 may be implemented as an absolute positioning system comprising a magnetic rotary absolute positioning system implemented as an AS5055EQFT single-chip magnetic rotary position sensor available from Austria Microsystems, AG. The position sensor 784 may interface with the control circuit 760 to provide an absolute positioning system. The position may include multiple Hall-effect elements located above a magnet and coupled to a CORDIC processor, also known as the digit-by-digit method and Volder's algorithm, that is provided to implement a simple and efficient algorithm to calculate hyperbolic and trigonometric functions that require only addition, subtraction, bitshift, and table lookup operations.
In some examples, the position sensor 784 may be omitted. Where the motor 754 is a stepper motor, the control circuit 760 may track the position of the closure member 764 by aggregating the number and direction of steps that the motor has been instructed to execute. The position sensor 784 may be located in the end effector 792 or at any other portion of the instrument.
The control circuit 760 may be in communication with one or more sensors 788. The sensors 788 may be positioned on the end effector 792 and adapted to operate with the surgical instrument 790 to measure the various derived parameters such as gap distance versus time, tissue compression versus time, and anvil strain versus time. The sensors 788 may comprise a magnetic sensor, a magnetic field sensor, a strain gauge, a pressure sensor, a force sensor, an inductive sensor such as an eddy current sensor, a resistive sensor, a capacitive sensor, an optical sensor, and/or any other suitable sensor for measuring one or more parameters of the end effector 792. The sensors 788 may include one or more sensors.
An RF energy source 794 is coupled to the end effector 792 and is applied to the RF electrode 796 when the RF electrode 796 is provided in the end effector 792 in place of the ultrasonic blade 768 or to work in conjunction with the ultrasonic blade 768. For example, the ultrasonic blade is made of electrically conductive metal and may be employed as the return path for electrosurgical RF current. The control circuit 760 controls the delivery of the RF energy to the RF electrode 796.
Additional details are disclosed in U.S. patent application Ser. No. 15/636,096, titled SURGICAL SYSTEM COUPLABLE WITH STAPLE CARTRIDGE AND RADIO FREQUENCY CARTRIDGE, AND METHOD OF USING SAME, filed Jun. 28, 2017, which is herein incorporated by reference in its entirety.
In various aspects smart ultrasonic energy devices may comprise adaptive algorithms to control the operation of the ultrasonic blade. In one aspect, the ultrasonic blade adaptive control algorithms are configured to identify tissue type and adjust device parameters. In one aspect, the ultrasonic blade control algorithms are configured to parameterize tissue type. An algorithm to detect the collagen/elastic ratio of tissue to tune the amplitude of the distal tip of the ultrasonic blade is described in the following section of the present disclosure. Various aspects of smart ultrasonic energy devices are described herein in connection with
In certain surgical procedures it would be desirable to employ adaptive ultrasonic blade control algorithms. In one aspect, adaptive ultrasonic blade control algorithms may be employed to adjust the parameters of the ultrasonic device based on the type of tissue in contact with the ultrasonic blade. In one aspect, the parameters of the ultrasonic device may be adjusted based on the location of the tissue within the jaws of the ultrasonic end effector, for example, the location of the tissue between the clamp arm and the ultrasonic blade. The impedance of the ultrasonic transducer may be employed to differentiate what percentage of the tissue is located in the distal or proximal end of the end effector. The reactions of the ultrasonic device may be based on the tissue type or compressibility of the tissue. In another aspect, the parameters of the ultrasonic device may be adjusted based on the identified tissue type or parameterization. For example, the mechanical displacement amplitude of the distal tip of the ultrasonic blade may be tuned based on the ration of collagen to elastin tissue detected during the tissue identification procedure. The ratio of collagen to elastin tissue may be detected used a variety of techniques including infrared (IR) surface reflectance and emissivity. The force applied to the tissue by the clamp arm and/or the stroke of the clamp arm to produce gap and compression. Electrical continuity across a jaw equipped with electrodes may be employed to determine what percentage of the jaw is covered with tissue.
The generator module 240 may comprise a patient isolated stage in communication with a non-isolated stage via a power transformer. A secondary winding of the power transformer is contained in the isolated stage and may comprise a tapped configuration (e.g., a center-tapped or a non-center-tapped configuration) to define drive signal outputs for delivering drive signals to different surgical instruments, such as, for example, an ultrasonic surgical instrument, an RF electrosurgical instrument, and a multifunction surgical instrument which includes ultrasonic and RF energy modes that can be delivered alone or simultaneously. In particular, the drive signal outputs may output an ultrasonic drive signal (e.g., a 420V root-mean-square (RMS) drive signal) to an ultrasonic surgical instrument 241, and the drive signal outputs may output an RF electrosurgical drive signal (e.g., a 100V RMS drive signal) to an RF electrosurgical instrument 241. Aspects of the generator module 240 are described herein with reference to
The generator module 240 or the device/instrument 235 or both are coupled to the modular control tower 236 connected to multiple operating theater devices such as, for example, intelligent surgical instruments, robots, and other computerized devices located in the operating theater, as described with reference to
A first voltage sensing circuit 912 is coupled across the terminals labeled ENERGY1 and the RETURN path to measure the output voltage therebetween. A second voltage sensing circuit 924 is coupled across the terminals labeled ENERGY2 and the RETURN path to measure the output voltage therebetween. A current sensing circuit 914 is disposed in series with the RETURN leg of the secondary side of the power transformer 908 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 912, 924 are provided to respective isolation transformers 916, 922 and the output of the current sensing circuit 914 is provided to another isolation transformer 918. The outputs of the isolation transformers 916, 928, 922 in the on the primary side of the power transformer 908 (non-patient isolated side) are provided to a one or more ADC circuit 926. The digitized output of the ADC circuit 926 is provided to the processor 902 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 902 and patient isolated circuits is provided through an interface circuit 920. Sensors also may be in electrical communication with the processor 902 by way of the interface circuit 920.
In one aspect, the impedance may be determined by the processor 902 by dividing the output of either the first voltage sensing circuit 912 coupled across the terminals labeled ENERGY1/RETURN or the second voltage sensing circuit 924 coupled across the terminals labeled ENERGY2/RETURN by the output of the current sensing circuit 914 disposed in series with the RETURN leg of the secondary side of the power transformer 908. The outputs of the first and second voltage sensing circuits 912, 924 are provided to separate isolations transformers 916, 922 and the output of the current sensing circuit 914 is provided to another isolation transformer 916. The digitized voltage and current sensing measurements from the ADC circuit 926 are provided the processor 902 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
As shown in
Additional details are disclosed in U.S. Patent Application Publication No. 2017/0086914, titled TECHNIQUES FOR OPERATING GENERATOR FOR DIGITALLY GENERATING ELECTRICAL SIGNAL WAVEFORMS AND SURGICAL INSTRUMENTS, which published on Mar. 30, 2017, which is herein incorporated by reference in its entirety.
As used throughout this description, the term “wireless” and its derivatives may be used to describe circuits, devices, systems, methods, techniques, communications channels, etc., that may communicate data through the use of modulated electromagnetic radiation through a non-solid medium. The term does not imply that the associated devices do not contain any wires, although in some aspects they might not. The communication module may implement any of a number of wireless or wired communication standards or protocols, including but not limited to Wi-Fi (IEEE 802.11 family), WiMAX (IEEE 802.16 family), IEEE 802.20, long term evolution (LTE), Ev-DO, HSPA+, HSDPA+, HSUPA+, EDGE, GSM, GPRS, CDMA, TDMA, DECT, Bluetooth, Ethernet derivatives thereof, as well as any other wireless and wired protocols that are designated as 3G, 4G, 5G, and beyond. The computing module may include a plurality of communication modules. For instance, a first communication module may be dedicated to shorter range wireless communications such as Wi-Fi and Bluetooth and a second communication module may be dedicated to longer range wireless communications such as GPS, EDGE, GPRS, CDMA, WiMAX, LTE, Ev-DO, and others.
As used herein a processor or processing unit is an electronic circuit which performs operations on some external data source, usually memory or some other data stream. The term is used herein to refer to the central processor (central processing unit) in a system or computer systems (especially systems on a chip (SoCs)) that combine a number of specialized “processors.”
As used herein, a system on a chip or system on chip (SoC or SOC) is an integrated circuit (also known as an “IC” or “chip”) that integrates all components of a computer or other electronic systems. It may contain digital, analog, mixed-signal, and often radio-frequency functions—all on a single substrate. A SoC integrates a microcontroller (or microprocessor) with advanced peripherals like graphics processing unit (GPU), Wi-Fi module, or coprocessor. A SoC may or may not contain built-in memory.
As used herein, a microcontroller or controller is a system that integrates a microprocessor with peripheral circuits and memory. A microcontroller (or MCU for microcontroller unit) may be implemented as a small computer on a single integrated circuit. It may be similar to a SoC; an SoC may include a microcontroller as one of its components. A microcontroller may contain one or more core processing units (CPUs) along with memory and programmable input/output peripherals. Program memory in the form of Ferroelectric RAM, NOR flash or OTP ROM is also often included on chip, as well as a small amount of RAM. Microcontrollers may be employed for embedded applications, in contrast to the microprocessors used in personal computers or other general purpose applications consisting of various discrete chips.
As used herein, the term controller or microcontroller may be a stand-alone IC or chip device that interfaces with a peripheral device. This may be a link between two parts of a computer or a controller on an external device that manages the operation of (and connection with) that device.
Any of the processors or microcontrollers described herein, may be implemented by any single core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In one aspect, the processor may be an LM4F230H5QR ARM Cortex-M4F Processor Core, available from Texas Instruments, for example, comprising on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle serial random access memory (SRAM), internal read-only memory (ROM) loaded with StellarisWare® software, 2 KB electrically erasable programmable read-only memory (EEPROM), one or more pulse width modulation (PWM) modules, one or more quadrature encoder inputs (QEI) analog, one or more 12-bit Analog-to-Digital Converters (ADC) with 12 analog input channels, details of which are available for the product datasheet.
In one aspect, the processor may comprise a safety controller comprising two controller-based families such as TMS570 and RM4x known under the trade name Hercules ARM Cortex R4, also by Texas Instruments. The safety controller may be configured specifically for IEC 61508 and ISO 26262 safety critical applications, among others, to provide advanced integrated safety features while delivering scalable performance, connectivity, and memory options.
Modular devices include the modules (as described in connection with
The generator 1100 is configured to drive multiple surgical instruments 1104, 1106, 1108. The first surgical instrument is an ultrasonic surgical instrument 1104 and comprises a handpiece 1105 (HP), an ultrasonic transducer 1120, a shaft 1126, and an end effector 1122. The end effector 1122 comprises an ultrasonic blade 1128 acoustically coupled to the ultrasonic transducer 1120 and a clamp arm 1140. The handpiece 1105 comprises a trigger 1143 to operate the clamp arm 1140 and a combination of the toggle buttons 1134a, 1134b, 1134c to energize and drive the ultrasonic blade 1128 or other function. The toggle buttons 1134a, 1134b, 1134c can be configured to energize the ultrasonic transducer 1120 with the generator 1100.
The generator 1100 also is configured to drive a second surgical instrument 1106. The second surgical instrument 1106 is an RF electrosurgical instrument and comprises a handpiece 1107 (HP), a shaft 1127, and an end effector 1124. The end effector 1124 comprises electrodes in clamp arms 1142a, 1142b and return through an electrical conductor portion of the shaft 1127. The electrodes are coupled to and energized by a bipolar energy source within the generator 1100. The handpiece 1107 comprises a trigger 1145 to operate the clamp arms 1142a, 1142b and an energy button 1135 to actuate an energy switch to energize the electrodes in the end effector 1124.
The generator 1100 also is configured to drive a multifunction surgical instrument 1108. The multifunction surgical instrument 1108 comprises a handpiece 1109 (HP), a shaft 1129, and an end effector 1125. The end effector 1125 comprises an ultrasonic blade 1149 and a clamp arm 1146. The ultrasonic blade 1149 is acoustically coupled to the ultrasonic transducer 1120. The handpiece 1109 comprises a trigger 1147 to operate the clamp arm 1146 and a combination of the toggle buttons 1137a, 1137b, 1137c to energize and drive the ultrasonic blade 1149 or other function. The toggle buttons 1137a, 1137b, 1137c can be configured to energize the ultrasonic transducer 1120 with the generator 1100 and energize the ultrasonic blade 1149 with a bipolar energy source also contained within the generator 1100.
The generator 1100 is configurable for use with a variety of surgical instruments. According to various forms, the generator 1100 may be configurable for use with different surgical instruments of different types including, for example, the ultrasonic surgical instrument 1104, the RF electrosurgical instrument 1106, and the multifunction surgical instrument 1108 that integrates RF and ultrasonic energies delivered simultaneously from the generator 1100. Although in the form of
The generator 1100 may be activated to provide the drive signal to the ultrasonic transducer 1120 in any suitable manner. For example, the generator 1100 may comprise a foot switch 1430 (
Additionally or alternatively, the one or more switches may comprise a toggle button 1134c that, when depressed, causes the generator 1100 to provide a pulsed output (
It will be appreciated that a device 1104 may comprise any combination of the toggle buttons 1134a, 1134b, 1134c (
In certain aspects, a two-position switch may be provided as an alternative to a toggle button 1134c (
In some aspects, the RF electrosurgical end effector 1124, 1125 (
In various aspects, the generator 1100 may comprise several separate functional elements, such as modules and/or blocks, as shown in
In accordance with the described aspects, the ultrasonic generator module may produce a drive signal or signals of particular voltages, currents, and frequencies (e.g. 55,500 cycles per second, or Hz). The drive signal or signals may be provided to the ultrasonic device 1104, and specifically to the transducer 1120, which may operate, for example, as described above. In one aspect, the generator 1100 may be configured to produce a drive signal of a particular voltage, current, and/or frequency output signal that can be stepped with high resolution, accuracy, and repeatability.
In accordance with the described aspects, the electrosurgery/RF generator module 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 the electrodes of the electrosurgical device 1106, for example, as described above. Accordingly, the generator 1100 may be configured for therapeutic purposes by applying electrical energy to the tissue sufficient for treating the tissue (e.g., coagulation, cauterization, tissue welding, etc.).
The generator 1100 may comprise an input device 2150 (
The generator 1100 may also comprise an output device 2140 (
Although certain modules and/or blocks of the generator 1100 may be described by way of example, it can be appreciated that a greater or lesser number of modules and/or blocks may be used and still fall within the scope of the aspects. Further, although various aspects may be described in terms of modules and/or blocks to facilitate description, such modules 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 aspect, the ultrasonic generator drive module and electrosurgery/RF drive module 1110 (
In one aspect, the modules comprise a hardware component implemented as a processor for executing program instructions for monitoring various measurable characteristics of the devices 1104, 1106, 1108 and generating a corresponding output drive signal or signals for operating the devices 1104, 1106, 1108. In aspects in which the generator 1100 is used in conjunction with the device 1104, the drive signal may drive the ultrasonic transducer 1120 in cutting and/or coagulation operating modes. Electrical characteristics of the device 1104 and/or tissue may be measured and used to control operational aspects of the generator 1100 and/or provided as feedback to the user. In aspects in which the generator 1100 is used in conjunction with the device 1106, the drive signal may supply electrical energy (e.g., RF energy) to the end effector 1124 in cutting, coagulation and/or desiccation modes. Electrical characteristics of the device 1106 and/or tissue may be measured and used to control operational aspects of the generator 1100 and/or provided as feedback to the user. In various aspects, as previously discussed, the hardware components may be implemented as DSP, PLD, ASIC, circuits, and/or registers. In one aspect, the processor may be configured to store and execute computer software program instructions to generate the step function output signals for driving various components of the devices 1104, 1106, 1108, such as the ultrasonic transducer 1120 and the end effectors 1122, 1124, 1125.
An electromechanical ultrasonic system includes an ultrasonic transducer, a waveguide, and an ultrasonic blade. The electromechanical ultrasonic system has an initial resonant frequency defined by the physical properties of the ultrasonic transducer, the waveguide, and the ultrasonic blade. The ultrasonic transducer is excited by an alternating voltage Vg(t) and current Ig(t) signal equal to the resonant frequency of the electromechanical ultrasonic system. When the electromechanical ultrasonic system is at resonance, the phase difference between the voltage Vg(t) and current Ig(t) signals is zero. Stated another way, at resonance the inductive impedance is equal to the capacitive impedance. As the ultrasonic blade heats up, the compliance of the ultrasonic blade (modeled as an equivalent capacitance) causes the resonant frequency of the electromechanical ultrasonic system to shift. Thus, the inductive impedance is no longer equal to the capacitive impedance causing a mismatch between the drive frequency and the resonant frequency of the electromechanical ultrasonic system. The system is now operating “off-resonance.” The mismatch between the drive frequency and the resonant frequency is manifested as a phase difference between the voltage Vg(t) and current Ig(t) signals applied to the ultrasonic transducer. The generator electronics can easily monitor the phase difference between the voltage Vg(t) and current Ig(t) signals and can continuously adjust the drive frequency until the phase difference is once again zero. At this point, the new drive frequency is equal to the new resonant frequency of the electromechanical ultrasonic system. The change in phase and/or frequency can be used as an indirect measurement of the ultrasonic blade temperature.
As shown in
Various aspects of the generator 1100 may not rely on a tuning inductor Lt to monitor the motional branch current Im(t). Instead, the generator 1100 may use the measured value of the static capacitance C0 in between applications of power for a specific ultrasonic surgical device 1104 (along with drive signal voltage and current feedback data) to determine values of the motional branch current Im(t) on a dynamic and ongoing basis (e.g., in real-time). Such aspects of the generator 1100 are therefore able to provide virtual tuning to simulate a system that is tuned or resonant with any value of static capacitance C0 at any frequency, and not just at a single resonant frequency dictated by a nominal value of the static capacitance C0.
Power may be supplied to a power rail of the power amplifier 1620 by a switch-mode regulator 1700. In certain aspects the switch-mode regulator 1700 may comprise an adjustable buck regulator, for example. As discussed above, the non-isolated stage 1540 may further comprise a processor 1740, which in one aspect may comprise a DSP processor such as an ADSP-21469 SHARC DSP, available from Analog Devices, Norwood, Mass., for example. In certain aspects the processor 1740 may control operation of the switch-mode power converter 1700 responsive to voltage feedback data received from the power amplifier 1620 by the processor 1740 via an analog-to-digital converter (ADC) 1760. In one aspect, for example, the processor 1740 may receive as input, via the ADC 1760, the waveform envelope of a signal (e.g., an RF signal) being amplified by the power amplifier 1620. The processor 1740 may then control the switch-mode regulator 1700 (e.g., via a pulse-width modulated (PWM) output) such that the rail voltage supplied to the power amplifier 1620 tracks the waveform envelope of the amplified signal. By dynamically modulating the rail voltage of the power amplifier 1620 based on the waveform envelope, the efficiency of the power amplifier 1620 may be significantly improved relative to a fixed rail voltage amplifier scheme. The processor 1740 may be configured for wired or wireless communication.
In certain aspects and as discussed in further detail in connection with
The non-isolated stage 1540 may further comprise an ADC 1780 and an ADC 1800 coupled to the output of the power transformer 1560 via respective isolation transformers 1820, 1840 for respectively sampling the voltage and current of drive signals output by the generator 1100. In certain aspects, the ADCs 1780, 1800 may be configured to sample at high speeds (e.g., 80 Msps) to enable oversampling of the drive signals. In one aspect, for example, the sampling speed of the ADCs 1780, 1800 may enable approximately 200× (depending on drive frequency) oversampling of the drive signals. In certain aspects, the sampling operations of the ADCs 1780, 1800 may be performed by a single ADC receiving input voltage and current signals via a two-way multiplexer. The use of high-speed sampling in aspects of the generator 1100 may enable, among other things, calculation of the complex current flowing through the motional branch (which may be used in certain aspects to implement DDS-based waveform shape control described above), 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 1780, 1800 may be received and processed (e.g., FIFO buffering, multiplexing) by the programmable logic device 1660 and stored in data memory for subsequent retrieval by, for example, the processor 1740. As noted above, voltage and current feedback data may be used as input to an algorithm for pre-distorting or modifying LUT waveform samples on a dynamic and ongoing basis. In certain aspects, 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 programmable logic device 1660 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 algorithm.
In certain aspects, 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 aspect, for example, voltage and current feedback data may be used to determine impedance phase, e.g., the phase difference between the voltage and current drive signals. 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 harmonic distortion and correspondingly enhancing impedance phase measurement accuracy. The determination of phase impedance and a frequency control signal may be implemented in the processor 1740, for example, with the frequency control signal being supplied as input to a DDS control algorithm implemented by the programmable logic device 1660.
The impedance phase may be determined through Fourier analysis. In one aspect, the phase difference between the generator voltage Vg(t) and generator current Ig(t) driving signals may be determined using the Fast Fourier Transform (FFT) or the Discrete Fourier Transform (DFT) as follows:
Evaluating the Fourier Transform at the frequency of the sinusoid yields:
Other approaches include weighted least-squares estimation, Kalman filtering, and space-vector-based techniques. Virtually all of the processing in an FFT or DFT technique may be performed in the digital domain with the aid of the 2-channel high speed ADC 1780, 1800, for example. In one technique, the digital signal samples of the voltage and current signals are Fourier transformed with an FFT or a DFT. The phase angle φ at any point in time can be calculated by:
φ=2πƒt+φ0
where φ is the phase angle, f is the frequency, t is time, and φ0 is the phase at t=0.
Another technique for determining the phase difference between the voltage Vg(t) and current Ig(t) signals is the zero-crossing method and produces highly accurate results. For voltage Vg(t) and current Ig(t) signals having the same frequency, each negative to positive zero-crossing of voltage signal Vg(t) triggers the start of a pulse, while each negative to positive zero-crossing of current signal Ig(t) triggers the end of the pulse. The result is a pulse train with a pulse width proportional to the phase angle between the voltage signal and the current signal. In one aspect, the pulse train may be passed through an averaging filter to yield a measure of the phase difference. Furthermore, if the positive to negative zero crossings also are used in a similar manner, and the results averaged, any effects of DC and harmonic components can be reduced. In one implementation, the analog voltage Vg(t) and current Ig(t) signals are converted to digital signals that are high if the analog signal is positive and low if the analog signal is negative. High accuracy phase estimates require sharp transitions between high and low. In one aspect, a Schmitt trigger along with an RC stabilization network may be employed to convert the analog signals into digital signals. In other aspects, an edge triggered RS flip-flop and ancillary circuitry may be employed. In yet another aspect, the zero-crossing technique may employ an eXclusive OR (XOR) gate.
Other techniques for determining the phase difference between the voltage and current signals include Lissajous figures and monitoring the image; methods such as the three-voltmeter method, the crossed-coil method, vector voltmeter and vector impedance methods; and using phase standard instruments, phase-locked loops, and other techniques as described in Phase Measurement, Peter O'Shea, 2000 CRC Press LLC, <http://www.engnetbase.com>, which is incorporated herein by reference.
In another aspect, 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 aspects, control of the current amplitude may be implemented by control algorithm, such as, for example, a proportional-integral-derivative (PID) control algorithm, in the processor 1740. Variables controlled by the control algorithm to suitably control the current amplitude of the drive signal may include, for example, the scaling of the LUT waveform samples stored in the programmable logic device 1660 and/or the full-scale output voltage of the DAC 1680 (which supplies the input to the power amplifier 1620) via a DAC 1860.
The non-isolated stage 1540 may further comprise a processor 1900 for providing, among other things, user interface (UI) functionality. In one aspect, the processor 1900 may comprise an Atmel AT91 SAM9263 processor having an ARM 926EJ-S core, available from Atmel Corporation, San Jose, Calif., for example. Examples of UI functionality supported by the processor 1900 may include audible and visual user feedback, communication with peripheral devices (e.g., via a Universal Serial Bus (USB) interface), communication with a foot switch 1430, communication with an input device 2150 (e.g., a touch screen display) and communication with an output device 2140 (e.g., a speaker). The processor 1900 may communicate with the processor 1740 and the programmable logic device (e.g., via a serial peripheral interface (SPI) bus). Although the processor 1900 may primarily support UI functionality, it may also coordinate with the processor 1740 to implement hazard mitigation in certain aspects. For example, the processor 1900 may be programmed to monitor various aspects of user input and/or other inputs (e.g., touch screen inputs 2150, foot switch 1430 inputs, temperature sensor inputs 2160) and may disable the drive output of the generator 1100 when an erroneous condition is detected.
In certain aspects, both the processor 1740 (
The non-isolated stage 1540 may further comprise a controller 1960 (
In certain aspects, when the generator 1100 is in a “power off” state, the controller 1960 may continue to receive operating power (e.g., via a line from a power supply of the generator 1100, such as the power supply 2110 (
In certain aspects, the controller 1960 may cause the generator 1100 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 aspects, the isolated stage 1520 may comprise an instrument interface circuit 1980 to, for example, provide a communication interface between a control circuit of a surgical device (e.g., a control circuit comprising handpiece switches) and components of the non-isolated stage 1540, such as, for example, the programmable logic device 1660, the processor 1740 and/or the processor 1900. The instrument interface circuit 1980 may exchange information with components of the non-isolated stage 1540 via a communication link that maintains a suitable degree of electrical isolation between the stages 1520, 1540, such as, for example, an infrared (IR)-based communication link. Power may be supplied to the instrument interface circuit 1980 using, for example, a low-dropout voltage regulator powered by an isolation transformer driven from the non-isolated stage 1540.
In one aspect, the instrument interface circuit 1980 may comprise a programmable logic device 2000 (e.g., an FPGA) in communication with a signal conditioning circuit 2020 (
In one aspect, the instrument interface circuit 1980 may comprise a first data circuit interface 2040 to enable information exchange between the programmable logic device 2000 (or other element of the instrument interface circuit 1980) and a first data circuit disposed in or otherwise associated with a surgical device. In certain aspects, for example, a first data circuit 2060 may be disposed in a cable integrally attached to a surgical device handpiece, or in an adaptor for interfacing a specific surgical device type or model with the generator 1100. In certain aspects, the first data circuit may comprise a non-volatile storage device, such as an electrically erasable programmable read-only memory (EEPROM) device. In certain aspects and referring again to
In certain aspects, the first data circuit 2060 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 1980 (e.g., by the programmable logic device 2000), transferred to a component of the non-isolated stage 1540 (e.g., to programmable logic device 1660, processor 1740 and/or processor 1900) for presentation to a user via an output device 2140 and/or for controlling a function or operation of the generator 1100. Additionally, any type of information may be communicated to first data circuit 2060 for storage therein via the first data circuit interface 2040 (e.g., using the programmable logic device 2000). 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 handpiece (e.g., instrument 1106 may be detachable from handpiece 1107) to promote instrument interchangeability and/or disposability. In such cases, known 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, it may be impractical to design a surgical device to maintain backward compatibility with generators that lack the requisite data reading functionality due to, for example, differing signal schemes, design complexity and cost. Other aspects of instruments 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.
Additionally, aspects of the generator 1100 may enable communication with instrument-based data circuits. For example, the generator 1100 may be configured to communicate with a second data circuit (e.g., a data circuit) contained in an instrument (e.g., instrument 1104, 1106 or 1108) of a surgical device. The instrument interface circuit 1980 may comprise a second data circuit interface 2100 to enable this communication. In one aspect, the second data circuit interface 2100 may comprise a tri-state digital interface, although other interfaces may also be used. In certain aspects, the second data circuit may generally be any circuit for transmitting and/or receiving data. In one aspect, 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. Additionally or alternatively, any type of information may be communicated to the second data circuit for storage therein via the second data circuit interface 2100 (e.g., using the programmable logic device 2000). 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 aspects, the second data circuit may transmit data acquired by one or more sensors (e.g., an instrument-based temperature sensor). In certain aspects, the second data circuit may receive data from the generator 1100 and provide an indication to a user (e.g., an LED indication or other visible indication) based on the received data.
In certain aspects, the second data circuit and the second data circuit interface 2100 may be configured such that communication between the programmable logic device 2000 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 handpiece to the generator 1100).
In one aspect, for example, information may be communicated to and from the second data circuit using a one-wire bus communication scheme implemented on existing cabling, such as one of the conductors used transmit interrogation signals from the signal conditioning circuit 2020 to a control circuit in a handpiece. 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 can be implemented over a common physical channel (either with or without frequency-band separation), 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 aspects, the isolated stage 1520 may comprise at least one blocking capacitor 2960-1 (
In certain aspects, the non-isolated stage 1540 may comprise a power supply 2110 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. As discussed above, the power supply 2110 may further comprise one or more DC/DC voltage converters 2130 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 1100. As discussed above in connection with the controller 1960, one or more of the DC/DC voltage converters 2130 may receive an input from the controller 1960 when activation of the “on/off” input device 2150 by a user is detected by the controller 1960 to enable operation of, or wake, the DC/DC voltage converters 2130.
The multiplexed current and voltage feedback samples may be received by a parallel data acquisition port (PDAP) implemented within block 2144 of the processor 1740. The PDAP may comprise a packing unit for implementing any of a number of methodologies for correlating the multiplexed feedback samples with a memory address. In one aspect, for example, feedback samples corresponding to a particular LUT sample output by the programmable logic device 1660 may be stored at one or more memory addresses that are correlated or indexed with the LUT address of the LUT sample. In another aspect, feedback samples corresponding to a particular LUT sample output by the programmable logic device 1660 may be stored, along with the LUT address of the LUT sample, at a common memory location. In any event, the feedback samples may be stored such that the address of the LUT sample from which a particular set of feedback samples originated may be subsequently ascertained. As discussed above, synchronization of the LUT sample addresses and the feedback samples in this way contributes to the correct timing and stability of the pre-distortion algorithm. A direct memory access (DMA) controller implemented at block 2166 of the processor 1740 may store the feedback samples (and any LUT sample address data, where applicable) at a designated memory location 2180 of the processor 1740 (e.g., internal RAM).
Block 2200 of the processor 1740 may implement a pre-distortion algorithm for pre-distorting or modifying the LUT samples stored in the programmable logic device 1660 on a dynamic, ongoing basis. As discussed above, pre-distortion of the LUT samples may compensate for various sources of distortion present in the output drive circuit of the generator 1100. The pre-distorted LUT samples, when processed through the drive circuit, will therefore result in a drive signal having the desired waveform shape (e.g., sinusoidal) for optimally driving the ultrasonic transducer.
At block 2220 of the pre-distortion algorithm, the current through the motional branch of the ultrasonic transducer is determined. The motional branch current may be determined using Kirchhoff's Current Law based on, for example, the current and voltage feedback samples stored at memory location 2180 (which, when suitably scaled, may be representative of Ig and Vg in the model of
At block 2240 of the pre-distortion algorithm, each motional branch current sample determined at block 2220 is compared to a sample of a desired current waveform shape to determine a difference, or sample amplitude error, between the compared samples. For this determination, the sample of the desired current waveform shape may be supplied, for example, from a waveform shape LUT 2260 containing amplitude samples for one cycle of a desired current waveform shape. The particular sample of the desired current waveform shape from the LUT 2260 used for the comparison may be dictated by the LUT sample address associated with the motional branch current sample used in the comparison. Accordingly, the input of the motional branch current to block 2240 may be synchronized with the input of its associated LUT sample address to block 2240. The LUT samples stored in the programmable logic device 1660 and the LUT samples stored in the waveform shape LUT 2260 may therefore be equal in number. In certain aspects, the desired current waveform shape represented by the LUT samples stored in the waveform shape LUT 2260 may be a fundamental sine wave. Other waveform shapes may be desirable. For example, it is contemplated that a fundamental sine wave for driving main longitudinal motion of an ultrasonic transducer superimposed with one or more other drive signals at other frequencies, such as a third order harmonic for driving at least two mechanical resonances for beneficial vibrations of transverse or other modes, could be used.
Each value of the sample amplitude error determined at block 2240 may be transmitted to the LUT of the programmable logic device 1660 (shown at block 2280 in
Current and voltage amplitude measurements, power measurements and impedance measurements may be determined at block 2300 of the processor 1740 based on the current and voltage feedback samples stored at memory location 2180. Prior to the determination of these quantities, the feedback samples may be suitably scaled and, in certain aspects, processed through a suitable filter 2320 to remove noise resulting from, for example, the data acquisition process and induced harmonic components. The filtered voltage and current samples may therefore substantially represent the fundamental frequency of the generator's drive output signal. In certain aspects, the filter 2320 may be a finite impulse response (FIR) filter applied in the frequency domain. Such aspects may use the Fast Fourier Transform (FFT) of the output drive signal current and voltage signals. In certain aspects, the resulting frequency spectrum may be used to provide additional generator functionality. In one aspect, for example, the ratio of the second and/or third order harmonic component relative to the fundamental frequency component may be used as a diagnostic indicator.
At block 2340 (
At block 2360, a root mean square (RMS) calculation may be applied to a sample size of the voltage feedback samples representing an integral number of cycles of the drive signal to determine a measurement Vrms representing the drive signal output voltage.
At block 2380, the current and voltage feedback samples may be multiplied point by point, and a mean calculation is applied to samples representing an integral number of cycles of the drive signal to determine a measurement Pr of the generator's real output power.
At block 2400, measurement Pa of the generator's apparent output power may be determined as the product Vrms·Irms.
At block 2420, measurement Zm of the load impedance magnitude may be determined as the quotient Vrms/Irms.
In certain aspects, the quantities Irms, Vrms, Pr, Pa and Zm determined at blocks 2340, 2360, 2380, 2400 and 2420 may be used by the generator 1100 to implement any of a number of control and/or diagnostic processes. In certain aspects, any of these quantities may be communicated to a user via, for example, an output device 2140 integral with the generator 1100 or an output device 2140 connected to the generator 1100 through a suitable communication interface (e.g., a USB interface). Various diagnostic processes may include, without limitation, handpiece integrity, instrument integrity, instrument attachment integrity, instrument overload, approaching instrument overload, frequency lock failure, over-voltage condition, over-current condition, over-power condition, voltage sense failure, current sense failure, audio indication failure, visual indication failure, short circuit condition, power delivery failure, or blocking capacitor failure, for example.
Block 2440 of the processor 1740 may implement a phase control algorithm for determining and controlling the impedance phase of an electrical load (e.g., the ultrasonic transducer) driven by the generator 1100. As discussed above, by controlling the frequency of the drive signal to minimize or reduce the difference between the determined impedance phase and an impedance phase setpoint (e.g., 0°), the effects of harmonic distortion may be minimized or reduced, and the accuracy of the phase measurement increased.
The phase control algorithm receives as input the current and voltage feedback samples stored in the memory location 2180. Prior to their use in the phase control algorithm, the feedback samples may be suitably scaled and, in certain aspects, processed through a suitable filter 2460 (which may be identical to filter 2320) to remove noise resulting from the data acquisition process and induced harmonic components, for example. The filtered voltage and current samples may therefore substantially represent the fundamental frequency of the generator's drive output signal.
At block 2480 of the phase control algorithm, the current through the motional branch of the ultrasonic transducer is determined. This determination may be identical to that described above in connection with block 2220 of the pre-distortion algorithm. The output of block 2480 may thus be, for each set of stored current and voltage feedback samples associated with a LUT sample, a motional branch current sample.
At block 2500 of the phase control algorithm, impedance phase is determined based on the synchronized input of motional branch current samples determined at block 2480 and corresponding voltage feedback samples. In certain aspects, the impedance phase is determined as the average of the impedance phase measured at the rising edge of the waveforms and the impedance phase measured at the falling edge of the waveforms.
At block 2520 of the of the phase control algorithm, the value of the impedance phase determined at block 2220 is compared to phase setpoint 2540 to determine a difference, or phase error, between the compared values.
At block 2560 (
Block 2580 of the processor 1740 may implement an algorithm for modulating the current amplitude of the drive signal in order to control the drive signal current, voltage and power in accordance with user specified setpoints, or in accordance with requirements specified by other processes or algorithms implemented by the generator 1100. Control of these quantities may be realized, for example, by scaling the LUT samples in the LUT 2280 and/or by adjusting the full-scale output voltage of the DAC 1680 (which supplies the input to the power amplifier 1620) via a DAC 1860. Block 2600 (which may be implemented as a PID controller in certain aspects) may receive, as input, current feedback samples (which may be suitably scaled and filtered) from the memory location 2180. The current feedback samples may be compared to a “current demand” Id value dictated by the controlled variable (e.g., current, voltage or power) to determine if the drive signal is supplying the necessary current. In aspects in which drive signal current is the control variable, the current demand Id may be specified directly by a current setpoint 2620A (Isp). For example, an RMS value of the current feedback data (determined as in block 2340) may be compared to user-specified RMS current setpoint Isp to determine the appropriate controller action. If, for example, the current feedback data indicates an RMS value less than the current setpoint Isp, LUT scaling and/or the full-scale output voltage of the DAC 1680 may be adjusted by the block 2600 such that the drive signal current is increased. Conversely, block 2600 may adjust LUT scaling and/or the full-scale output voltage of the DAC 1680 to decrease the drive signal current when the current feedback data indicates an RMS value greater than the current setpoint Isp.
In aspects in which the drive signal voltage is the control variable, the current demand Id may be specified indirectly, for example, based on the current required to maintain a desired voltage setpoint 2620B (Vsp) given the load impedance magnitude Zm measured at block 2420 (e.g. Id=Vsp/Zm). Similarly, in aspects in which drive signal power is the control variable, the current demand Id may be specified indirectly, for example, based on the current required to maintain a desired power setpoint 2620C (Psp) given the voltage Vrms measured at blocks 2360 (e.g. Id=Psp/Vrms).
Block 2680 (
Block 2700 of the processor 1740 may implement a switch-mode converter control algorithm for dynamically modulating the rail voltage of the power amplifier 1620 based on the waveform envelope of the signal being amplified, thereby improving the efficiency of the power amplifier 1620. In certain aspects, characteristics of the waveform envelope may be determined by monitoring one or more signals contained in the power amplifier 1620. In one aspect, for example, characteristics of the waveform envelope may be determined by monitoring the minima of a drain voltage (e.g., a MOSFET drain voltage) that is modulated in accordance with the envelope of the amplified signal. A minima voltage signal may be generated, for example, by a voltage minima detector coupled to the drain voltage. The minima voltage signal may be sampled by ADC 1760, with the output minima voltage samples being received at block 2720 of the switch-mode converter control algorithm. Based on the values of the minima voltage samples, block 2740 may control a PWM signal output by a PWM generator 2760, which, in turn, controls the rail voltage supplied to the power amplifier 1620 by the switch-mode regulator 1700. In certain aspects, as long as the values of the minima voltage samples are less than a minima target 2780 input into block 2720, the rail voltage may be modulated in accordance with the waveform envelope as characterized by the minima voltage samples. When the minima voltage samples indicate low envelope power levels, for example, block 2740 may cause a low rail voltage to be supplied to the power amplifier 1620, with the full rail voltage being supplied only when the minima voltage samples indicate maximum envelope power levels. When the minima voltage samples fall below the minima target 2780, block 2740 may cause the rail voltage to be maintained at a minimum value suitable for ensuring proper operation of the power amplifier 1620.
A drive circuit 2986 provides left and right ultrasonic energy outputs. A digital signal that represents the signal waveform is provided to the SCL-A, SDA-A inputs of the analog multiplexer 2980 from a control circuit, such as the control circuit 3200 (
In one aspect, the main processor 3214 is coupled to the electrical circuit 2900 (
In one aspect, the main processor 3214 may be an LM 4F230H5QR, available from Texas Instruments, for example. In at least one example, the Texas Instruments LM4F230H5QR is an ARM Cortex-M4F Processor Core comprising on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle serial random access memory (SRAM), internal read-only memory (ROM) loaded with StellarisWare® software, 2 KB electrically erasable programmable read-only memory (EEPROM), one or more pulse width modulation (PWM) modules, one or more quadrature encoder inputs (QED analog, one or more 12-bit Analog-to-Digital Converters (ADC) with 12 analog input channels, among other features that are readily available from the product datasheet. Other processors may be readily substituted and, accordingly, the present disclosure should not be limited in this context.
One feature of the present disclosure that severs dependency on high voltage (120 VAC) input power (a characteristic of general ultrasonic cutting devices) is the utilization of low-voltage switching throughout the wave-forming process and the amplification of the driving signal only directly before the transformer stage. For this reason, in one aspect of the present disclosure, power is derived from only a battery, or a group of batteries, small enough to fit either within a handle assembly. State-of-the-art battery technology provides powerful batteries of a few centimeters in height and width and a few millimeters in depth. By combining the features of the present disclosure to provide a self-contained and self-powered ultrasonic device, a reduction in manufacturing cost may be achieved.
The output of the power supply 3304 is fed to and powers the processor 3302. The processor 3302 receives and outputs signals and, as will be described below, functions according to custom logic or in accordance with computer programs that are executed by the processor 3302. As discussed above, the electrical circuit 3300 can also include a memory 3326, preferably, random access memory (RAM), that stores computer-readable instructions and data.
The output of the power supply 3304 also is directed to the switch 3306 having a duty cycle controlled by the processor 3302. By controlling the on-time for the switch 3306, the processor 3302 is able to dictate the total amount of power that is ultimately delivered to the transducer 1120. In one aspect, the switch 3306 is a MOSFET, although other switches and switching configurations are adaptable as well. The output of the switch 3306 is fed to a drive circuit 3308 that contains, for example, a phase detecting phase-locked loop (PLL) and/or a low-pass filter and/or a voltage-controlled oscillator. The output of the switch 3306 is sampled by the processor 3302 to determine the voltage and current of the output signal (VIN and IIN, respectively). These values are used in a feedback architecture to adjust the pulse width modulation of the switch 3306. For instance, the duty cycle of the switch 3306 can vary from about 20% to about 80%, depending on the desired and actual output from the switch 3306.
The drive circuit 3308, which receives the signal from the switch 3306, includes an oscillatory circuit that turns the output of the switch 3306 into an electrical signal having an ultrasonic frequency, e.g., 55 kHz (VCO). As explained above, a smoothed-out version of this ultrasonic waveform is ultimately fed to the ultrasonic transducer 1120 to produce a resonant sine wave along an ultrasonic transmission waveguide.
At the output of the drive circuit 3308 is a transformer 3310 that is able to step up the low voltage signal(s) to a higher voltage. It is noted that upstream switching, prior to the transformer 3310, is performed at low (e.g., battery driven) voltages, something that, to date, has not been possible for ultrasonic cutting and cautery devices. This is at least partially due to the fact that the device advantageously uses low on-resistance MOSFET switching devices. Low on-resistance MOSFET switches are advantageous, as they produce lower switching losses and less heat than a traditional MOSFET device and allow higher current to pass through. Therefore, the switching stage (pre-transformer) can be characterized as low voltage/high current. To ensure the lower on-resistance of the amplifier MOSFET(s), the MOSFET(s) are run, for example, at 10 V. In such a case, a separate 10 VDC power supply can be used to feed the MOSFET gate, which ensures that the MOSFET is fully on and a reasonably low on resistance is achieved. In one aspect of the present disclosure, the transformer 3310 steps up the battery voltage to 120 V root-mean-square (RMS). Transformers are known in the art and are, therefore, not explained here in detail.
In the circuit configurations described, circuit component degradation can negatively impact the circuit performance of the circuit. One factor that directly affects component performance is heat. Known circuits generally monitor switching temperatures (e.g., MOSFET temperatures). However, because of the technological advancements in MOSFET designs, and the corresponding reduction in size, MOSFET temperatures are no longer a valid indicator of circuit loads and heat. For this reason, in accordance with at least one aspect of the present disclosure, the sensing circuit 3314 senses the temperature of the transformer 3310. This temperature sensing is advantageous as the transformer 3310 is run at or very close to its maximum temperature during use of the device. Additional temperature will cause the core material, e.g., the ferrite, to break down and permanent damage can occur. The present disclosure can respond to a maximum temperature of the transformer 3310 by, for example, reducing the driving power in the transformer 3310, signaling the user, turning the power off, pulsing the power, or other appropriate responses.
In one aspect of the present disclosure, the processor 3302 is communicatively coupled to the end effector (e.g. 1122, 1125), which is used to place material in physical contact with the ultrasonic blade (e.g. 1128, 1149). Sensors are provided that measure, at the end effector, a clamping force value (existing within a known range) and, based upon the received clamping force value, the processor 3302 varies the motional voltage VM. Because high force values combined with a set motional rate can result in high blade temperatures, a temperature sensor 3332 can be communicatively coupled to the processor 3302, where the processor 3302 is operable to receive and interpret a signal indicating a current temperature of the blade from the temperature sensor 3336 and to determine a target frequency of blade movement based upon the received temperature. In another aspect, force sensors such as strain gages or pressure sensors may be coupled to the trigger (e.g. 1143, 1147) to measure the force applied to the trigger by the user. In another aspect, force sensors such as strain gages or pressure sensors may be coupled to a switch button such that displacement intensity corresponds to the force applied by the user to the switch button.
In accordance with at least one aspect of the present disclosure, the PLL portion of the drive circuit 3308, which is coupled to the processor 3302, is able to determine a frequency of waveguide movement and communicate that frequency to the processor 3302. The processor 3302 stores this frequency value in the memory 3326 when the device is turned off. By reading the clock 3330, the processor 3302 is able to determine an elapsed time after the device is shut off and retrieve the last frequency of waveguide movement if the elapsed time is less than a predetermined value. The device can then start up at the last frequency, which, presumably, is the optimum frequency for the current load.
In another aspect, the present disclosure provides a modular battery powered handheld surgical instrument with multistage generator circuits. Disclosed is a surgical instrument that includes a battery assembly, a handle assembly, and a shaft assembly where the battery assembly and the shaft assembly are configured to mechanically and electrically connect to the handle assembly. The battery assembly includes a control circuit configured to generate a digital waveform. The handle assembly includes a first stage circuit configured to receive the digital waveform, convert the digital waveform into an analog waveform, and amplify the analog waveform. The shaft assembly includes a second stage circuit coupled to the first stage circuit to receive, amplify, and apply the analog waveform to a load.
In one aspect, the present disclosure provides a surgical instrument, comprising: a battery assembly, comprising a control circuit comprising a battery, a memory coupled to the battery, and a processor coupled to the memory and the battery, wherein the processor is configured to generate a digital waveform; a handle assembly comprising a first stage circuit coupled to the processor, the first stage circuit comprising a digital-to-analog (DAC) converter and a first stage amplifier circuit, wherein the DAC is configured to receive the digital waveform and convert the digital waveform into an analog waveform, wherein the first stage amplifier circuit is configured to receive and amplify the analog waveform; and a shaft assembly comprising a second stage circuit coupled to the first stage amplifier circuit to receive the analog waveform, amplify the analog waveform, and apply the analog waveform to a load; wherein the battery assembly and the shaft assembly are configured to mechanically and electrically connect to the handle assembly.
The load may comprise any one of an ultrasonic transducer, an electrode, or a sensor, or any combinations thereof. The first stage circuit may comprise a first stage ultrasonic drive circuit and a first stage high-frequency current drive circuit. The control circuit may be configured to drive the first stage ultrasonic drive circuit and the first stage high-frequency current drive circuit independently or simultaneously. The first stage ultrasonic drive circuit may be configured to couple to a second stage ultrasonic drive circuit. The second stage ultrasonic drive circuit may be configured to couple to an ultrasonic transducer. The first stage high-frequency current drive circuit may be configured to couple to a second stage high-frequency drive circuit. The second stage high-frequency drive circuit may be configured to couple to an electrode.
The first stage circuit may comprise a first stage sensor drive circuit. The first stage sensor drive circuit may be configured to a second stage sensor drive circuit. The second stage sensor drive circuit may be configured to couple to a sensor.
In another aspect, the present disclosure provides a surgical instrument, comprising: a battery assembly, comprising a control circuit comprising a battery, a memory coupled to the battery, and a processor coupled to the memory and the battery, wherein the processor is configured to generate a digital waveform; a handle assembly comprising a common first stage circuit coupled to the processor, the common first stage circuit comprising a digital-to-analog (DAC) converter and a common first stage amplifier circuit, wherein the DAC is configured to receive the digital waveform and convert the digital waveform into an analog waveform, wherein the common first stage amplifier circuit is configured to receive and amplify the analog waveform; and a shaft assembly comprising a second stage circuit coupled to the common first stage amplifier circuit to receive the analog waveform, amplify the analog waveform, and apply the analog waveform to a load; wherein the battery assembly and the shaft assembly are configured to mechanically and electrically connect to the handle assembly.
The load may comprise any one of an ultrasonic transducer, an electrode, or a sensor, or any combinations thereof. The common first stage circuit may be configured to drive ultrasonic, high-frequency current, or sensor circuits. The common first stage drive circuit may be configured to couple to a second stage ultrasonic drive circuit, a second stage high-frequency drive circuit, or a second stage sensor drive circuit. The second stage ultrasonic drive circuit may be configured to couple to an ultrasonic transducer, the second stage high-frequency drive circuit is configured to couple to an electrode, and the second stage sensor drive circuit is configured to couple to a sensor.
In another aspect, the present disclosure provides a surgical instrument, comprising a control circuit comprising a memory coupled to a processor, wherein the processor is configured to generate a digital waveform; a handle assembly comprising a common first stage circuit coupled to the processor, the common first stage circuit configured to receive the digital waveform, convert the digital waveform into an analog waveform, and amplify the analog waveform; and a shaft assembly comprising a second stage circuit coupled to the common first stage circuit to receive and amplify the analog waveform; wherein the shaft assembly is configured to mechanically and electrically connect to the handle assembly.
The common first stage circuit may be configured to drive ultrasonic, high-frequency current, or sensor circuits. The common first stage drive circuit may be configured to couple to a second stage ultrasonic drive circuit, a second stage high-frequency drive circuit, or a second stage sensor drive circuit. The second stage ultrasonic drive circuit may be configured to couple to an ultrasonic transducer, the second stage high-frequency drive circuit is configured to couple to an electrode, and the second stage sensor drive circuit is configured to couple to a sensor.
Turning now to
The first stage circuits 3404 (e.g., the first stage ultrasonic drive circuit 3420, the first stage RF drive circuit 3422, and the first stage sensor drive circuit 3424) are located in a handle assembly 3412 of the surgical instrument. The control circuit 3200 provides the ultrasonic drive signal to the first stage ultrasonic drive circuit 3420 via outputs SCL-A, SDA-A of the control circuit 3200. The first stage ultrasonic drive circuit 3420 is described in detail in connection with
The control circuit 3200 is configured to detect which modules are plugged into the control circuit 3200. For example, the control circuit 3200 is configured to detect whether the first stage ultrasonic drive circuit 3420, the first stage RF drive circuit 3422, or the first stage sensor drive circuit 3424 located in the handle assembly 3412 is connected to the battery assembly 3410. Likewise, each of the first stage circuits 3404 can detect which second stage circuits 3406 are connected thereto and that information is provided back to the control circuit 3200 to determine the type of signal waveform to generate. Similarly, each of the second stage circuits 3406 can detect which third stage circuits 3408 or components are connected thereto and that information is provided back to the control circuit 3200 to determine the type of signal waveform to generate.
In one aspect, the second stage circuits 3406 (e.g., the ultrasonic drive second stage circuit 3430, the RF drive second stage circuit 3432, and the sensor drive second stage circuit 3434) are located in the shaft assembly 3414 of the surgical instrument. The first stage ultrasonic drive circuit 3420 provides a signal to the second stage ultrasonic drive circuit 3430 via outputs US-Left/US-Right. The second stage ultrasonic drive circuit 3430 can include, for example, a transformer, filter, amplifier, and/or signal conditioning circuits. The first stage high-frequency (RF) current drive circuit 3422 provides a signal to the second stage RF drive circuit 3432 via outputs RF-Left/RF-Right. In addition to a transformer and blocking capacitors, the second stage RF drive circuit 3432 also may include filter, amplifier, and signal conditioning circuits. The first stage sensor drive circuit 3424 provides a signal to the second stage sensor drive circuit 3434 via outputs Sensor-1/Sensor-2. The second stage sensor drive circuit 3434 may include filter, amplifier, and signal conditioning circuits depending on the type of sensor. The outputs of the second stage circuits 3406 are provided to the inputs of the third stage circuits 3408.
In one aspect, the third stage circuits 3408 (e.g., the ultrasonic transducer 1120, the RF electrodes 3074a, 3074b, and the sensors 3440) may be located in various assemblies 3416 of the surgical instruments. In one aspect, the second stage ultrasonic drive circuit 3430 provides a drive signal to the ultrasonic transducer 1120 piezoelectric stack. In one aspect, the ultrasonic transducer 1120 is located in the ultrasonic transducer assembly of the surgical instrument. In other aspects, however, the ultrasonic transducer 1120 may be located in the handle assembly 3412, the shaft assembly 3414, or the end effector. In one aspect, the second stage RF drive circuit 3432 provides a drive signal to the RF electrodes 3074a, 3074b, which are generally located in the end effector portion of the surgical instrument. In one aspect, the second stage sensor drive circuit 3434 provides a drive signal to various sensors 3440 located throughout the surgical instrument.
As shown in the example of
A drive circuit 3686 provides Left and Right RF energy outputs. A digital signal that represents the signal waveform is provided to the SCL-A, SDA-A inputs of the analog multiplexer 3680 from a control circuit, such as the control circuit 3200 (
In one aspect, the ultrasonic or high-frequency current generators of the surgical system 1000 may be configured to generate the electrical signal waveform digitally such that the desired using a predetermined number of phase points stored in a lookup table to digitize the wave shape. The phase points may be stored in a table defined in a memory, a field programmable gate array (FPGA), or any suitable non-volatile memory.
The waveform signal may be configured to control at least one of an output current, an output voltage, or an output power of an ultrasonic transducer and/or an RF electrode, or multiples thereof (e.g. two or more ultrasonic transducers and/or two or more RF electrodes). Further, where the surgical instrument comprises an ultrasonic components, the waveform signal may be configured to drive at least two vibration modes of an ultrasonic transducer of the at least one surgical instrument. Accordingly, a generator may be configured to provide a waveform signal to at least one surgical instrument wherein the waveform signal corresponds to at least one wave shape of a plurality of wave shapes in a table. Further, the waveform signal provided to the two surgical instruments may comprise two or more wave shapes. The table may comprise information associated with a plurality of wave shapes and the table may be stored within the generator. In one aspect or example, the table may be a direct digital synthesis table, which may be stored in an FPGA of the generator. The table may be addressed by anyway that is convenient for categorizing wave shapes. According to one aspect, the table, which may be a direct digital synthesis table, is addressed according to a frequency of the waveform signal. Additionally, the information associated with the plurality of wave shapes may be stored as digital information in the table.
The analog electrical signal waveform may be configured to control at least one of an output current, an output voltage, or an output power of an ultrasonic transducer and/or an RF electrode, or multiples thereof (e.g., two or more ultrasonic transducers and/or two or more RF electrodes). Further, where the surgical instrument comprises ultrasonic components, the analog electrical signal waveform may be configured to drive at least two vibration modes of an ultrasonic transducer of the at least one surgical instrument. Accordingly, the generator circuit may be configured to provide an analog electrical signal waveform to at least one surgical instrument wherein the analog electrical signal waveform corresponds to at least one wave shape of a plurality of wave shapes stored in a lookup table 4104. Further, the analog electrical signal waveform provided to the two surgical instruments may comprise two or more wave shapes. The lookup table 4104 may comprise information associated with a plurality of wave shapes and the lookup table 4104 may be stored either within the generator circuit or the surgical instrument. In one aspect or example, the lookup table 4104 may be a direct digital synthesis table, which may be stored in an FPGA of the generator circuit or the surgical instrument. The lookup table 4104 may be addressed by anyway that is convenient for categorizing wave shapes. According to one aspect, the lookup table 4104, which may be a direct digital synthesis table, is addressed according to a frequency of the desired analog electrical signal waveform. Additionally, the information associated with the plurality of wave shapes may be stored as digital information in the lookup table 4104.
With the widespread use of digital techniques in instrumentation and communications systems, a digitally-controlled method of generating multiple frequencies from a reference frequency source has evolved and is referred to as direct digital synthesis. The basic architecture is shown in
Because the DDS circuit 4100 is a sampled data system, issues involved in sampling must be considered: quantization noise, aliasing, filtering, etc. For instance, the higher order harmonics of the DAC circuit 4108 output frequencies fold back into the Nyquist bandwidth, making them unfilterable, whereas, the higher order harmonics of the output of phase-locked-loop (PLL) based synthesizers can be filtered. The lookup table 4104 contains signal data for an integral number of cycles. The final output frequency fout can be changed changing the reference clock frequency fc or by reprogramming the PROM.
The DDS circuit 4100 may comprise multiple lookup tables 4104 where the lookup table 4104 stores a waveform represented by a predetermined number of samples, wherein the samples define a predetermined shape of the waveform. Thus multiple waveforms having a unique shape can be stored in multiple lookup tables 4104 to provide different tissue treatments based on instrument settings or tissue feedback. Examples of waveforms include high crest factor RF electrical signal waveforms for surface tissue coagulation, low crest factor RF electrical signal waveform for deeper tissue penetration, and electrical signal waveforms that promote efficient touch-up coagulation. In one aspect, the DDS circuit 4100 can create multiple wave shape lookup tables 4104 and during a tissue treatment procedure (e.g., “on-the-fly” or in virtual real time based on user or sensor inputs) switch between different wave shapes stored in separate lookup tables 4104 based on the tissue effect desired and/or tissue feedback.
Accordingly, switching between wave shapes can be based on tissue impedance and other factors, for example. In other aspects, the lookup tables 4104 can store electrical signal waveforms shaped to maximize the power delivered into the tissue per cycle (i.e., trapezoidal or square wave). In other aspects, the lookup tables 4104 can store wave shapes synchronized in such way that they make maximizing power delivery by the multifunction surgical instrument of surgical system 1000 while delivering RF and ultrasonic drive signals. In yet other aspects, the lookup tables 4104 can store electrical signal waveforms to drive ultrasonic and RF therapeutic, and/or sub-therapeutic, energy simultaneously while maintaining ultrasonic frequency lock. Custom wave shapes specific to different instruments and their tissue effects can be stored in the non-volatile memory of the generator circuit or in the non-volatile memory (e.g., EEPROM) of the surgical system 1000 and be fetched upon connecting the multifunction surgical instrument to the generator circuit. An example of an exponentially damped sinusoid, as used in many high crest factor “coagulation” waveforms is shown in
A more flexible and efficient implementation of the DDS circuit 4100 employs a digital circuit called a Numerically Controlled Oscillator (NCO). A block diagram of a more flexible and efficient digital synthesis circuit such as a DDS circuit 4200 is shown in
The DDS circuit 4200 includes a sample clock that generates the clock frequency fc, the phase accumulator 4206, and the lookup table 4210 (e.g., phase to amplitude converter). The content of the phase accumulator 4206 is updated once per clock cycle fc. When time the phase accumulator 4206 is updated, the digital number, M, stored in the parallel delta phase register 4204 is added to the number in the phase register 4208 by the adder circuit 4216. Assuming that the number in the parallel delta phase register 4204 is 00 . . . 01 and that the initial contents of the phase accumulator 4206 is 00 . . . 00. The phase accumulator 4206 is updated by 00 . . . 01 per clock cycle. If the phase accumulator 4206 is 32-bits wide, 232 clock cycles (over 4 billion) are required before the phase accumulator 4206 returns to 00 . . . 00, and the cycle repeats.
A truncated output 4218 of the phase accumulator 4206 is provided to a phase-to amplitude converter lookup table 4210 and the output of the lookup table 4210 is coupled to a DAC circuit 4212. The truncated output 4218 of the phase accumulator 4206 serves as the address to a sine (or cosine) lookup table. An address in the lookup table corresponds to a phase point on the sinewave from 0° to 360°. The lookup table 4210 contains the corresponding digital amplitude information for one complete cycle of a sinewave. The lookup table 4210 therefore maps the phase information from the phase accumulator 4206 into a digital amplitude word, which in turn drives the DAC circuit 4212. The output of the DAC circuit is a first analog signal 4220 and is filtered by a filter 4214. The output of the filter 4214 is a second analog signal 4222, which is provided to a power amplifier coupled to the output of the generator circuit.
In one aspect, the electrical signal waveform may be digitized into 1024 (210) phase points, although the wave shape may be digitized is any suitable number of 2n phase points ranging from 256 (28) to 281,474,976,710,656 (248), where n is a positive integer, as shown in TABLE 1. The electrical signal waveform may be expressed as An(θn), where a normalized amplitude An at a point n is represented by a phase angle θn is referred to as a phase point at point n. The number of discrete phase points n determines the tuning resolution of the DDS circuit 4200 (as well as the DDS circuit 4100 shown in
TABLE 1 specifies the electrical signal waveform digitized into a number of phase points.
The generator circuit algorithms and digital control circuits scan the addresses in the lookup table 4210, which in turn provides varying digital input values to the DAC circuit 4212 that feeds the filter 4214 and the power amplifier. The addresses may be scanned according to a frequency of interest. Using the lookup table enables generating various types of shapes that can be converted into an analog output signal by the DAC circuit 4212, filtered by the filter 4214, amplified by the power amplifier coupled to the output of the generator circuit, and fed to the tissue in the form of RF energy or fed to an ultrasonic transducer and applied to the tissue in the form of ultrasonic vibrations which deliver energy to the tissue in the form of heat. The output of the amplifier can be applied to an RF electrode, multiple RF electrodes simultaneously, an ultrasonic transducer, multiple ultrasonic transducers simultaneously, or a combination of RF and ultrasonic transducers, for example. Furthermore, multiple wave shape tables can be created, stored, and applied to tissue from a generator circuit.
With reference back to
For a phase accumulator 4206 configured to accumulate n-bits (n generally ranges from 24 to 32 in most DDS systems, but as previously discussed n may be selected from a wide range of options), there are 2n possible phase points. The digital word in the delta phase register, M, represents the amount the phase accumulator is incremented per clock cycle. If fc is the clock frequency, then the frequency of the output sinewave is equal to:
The above equation is known as the DDS “tuning equation.” Note that the frequency resolution of the system is equal to
For n=32, the resolution is greater than one part in four billion. In one aspect of the DDS circuit 4200, not all of the bits out of the phase accumulator 4206 are passed on to the lookup table 4210, but are truncated, leaving only the first 13 to 15 most significant bits (MSBs), for example. This reduces the size of the lookup table 4210 and does not affect the frequency resolution. The phase truncation only adds a small but acceptable amount of phase noise to the final output.
The electrical signal waveform may be characterized by a current, voltage, or power at a predetermined frequency. Further, where any one of the surgical instruments of surgical system 1000 comprises ultrasonic components, the electrical signal waveform may be configured to drive at least two vibration modes of an ultrasonic transducer of the at least one surgical instrument. Accordingly, the generator circuit may be configured to provide an electrical signal waveform to at least one surgical instrument wherein the electrical signal waveform is characterized by a predetermined wave shape stored in the lookup table 4210 (or lookup table 4104,
In one aspect, the generator circuit may be configured to provide electrical signal waveforms to at least two surgical instruments simultaneously. The generator circuit also may be configured to provide the electrical signal waveform, which may be characterized two or more wave shapes, via an output channel of the generator circuit to the two surgical instruments simultaneously. For example, in one aspect the electrical signal waveform comprises a first electrical signal to drive an ultrasonic transducer (e.g., ultrasonic drive signal), a second RF drive signal, and/or a combination thereof. In addition, an electrical signal waveform may comprise a plurality of ultrasonic drive signals, a plurality of RF drive signals, and/or a combination of a plurality of ultrasonic and RF drive signals.
In addition, a method of operating the generator circuit according to the present disclosure comprises generating an electrical signal waveform and providing the generated electrical signal waveform to any one of the surgical instruments of surgical system 1000, where generating the electrical signal waveform comprises receiving information associated with the electrical signal waveform from a memory. The generated electrical signal waveform comprises at least one wave shape. Furthermore, providing the generated electrical signal waveform to the at least one surgical instrument comprises providing the electrical signal waveform to at least two surgical instruments simultaneously.
The generator circuit as described herein may allow for the generation of various types of direct digital synthesis tables. Examples of wave shapes for RF/Electrosurgery signals suitable for treating a variety of tissue generated by the generator circuit include RF signals with a high crest factor (which may be used for surface coagulation in RF mode), a low crest factor RF signals (which may be used for deeper tissue penetration), and waveforms that promote efficient touch-up coagulation. The generator circuit also may generate multiple wave shapes employing a direct digital synthesis lookup table 4210 and, on the fly, can switch between particular wave shapes based on the desired tissue effect. Switching may be based on tissue impedance and/or other factors.
In addition to traditional sine/cosine wave shapes, the generator circuit may be configured to generate wave shape(s) that maximize the power into tissue per cycle (i.e., trapezoidal or square wave). The generator circuit may provide wave shape(s) that are synchronized to maximize the power delivered to the load when driving RF and ultrasonic signals simultaneously and to maintain ultrasonic frequency lock, provided that the generator circuit includes a circuit topology that enables simultaneously driving RF and ultrasonic signals. Further, custom wave shapes specific to instruments and their tissue effects can be stored in a non-volatile memory (NVM) or an instrument EEPROM and can be fetched upon connecting any one of the surgical instruments of surgical system 1000 to the generator circuit.
The DDS circuit 4200 may comprise multiple lookup tables 4104 where the lookup table 4210 stores a waveform represented by a predetermined number of phase points (also may be referred to as samples), wherein the phase points define a predetermined shape of the waveform. Thus multiple waveforms having a unique shape can be stored in multiple lookup tables 4210 to provide different tissue treatments based on instrument settings or tissue feedback. Examples of waveforms include high crest factor RF electrical signal waveforms for surface tissue coagulation, low crest factor RF electrical signal waveform for deeper tissue penetration, and electrical signal waveforms that promote efficient touch-up coagulation. In one aspect, the DDS circuit 4200 can create multiple wave shape lookup tables 4210 and during a tissue treatment procedure (e.g., “on-the-fly” or in virtual real time based on user or sensor inputs) switch between different wave shapes stored in different lookup tables 4210 based on the tissue effect desired and/or tissue feedback.
Accordingly, switching between wave shapes can be based on tissue impedance and other factors, for example. In other aspects, the lookup tables 4210 can store electrical signal waveforms shaped to maximize the power delivered into the tissue per cycle (i.e., trapezoidal or square wave). In other aspects, the lookup tables 4210 can store wave shapes synchronized in such way that they make maximizing power delivery by any one of the surgical instruments of surgical system 1000 when delivering RF and ultrasonic drive signals. In yet other aspects, the lookup tables 4210 can store electrical signal waveforms to drive ultrasonic and RF therapeutic, and/or sub-therapeutic, energy simultaneously while maintaining ultrasonic frequency lock. Generally, the output wave shape may be in the form of a sine wave, cosine wave, pulse wave, square wave, and the like. Nevertheless, the more complex and custom wave shapes specific to different instruments and their tissue effects can be stored in the non-volatile memory of the generator circuit or in the non-volatile memory (e.g., EEPROM) of the surgical instrument and be fetched upon connecting the surgical instrument to the generator circuit. One example of a custom wave shape is an exponentially damped sinusoid as used in many high crest factor “coagulation” waveforms, as shown in
In the context of controlling the displacement of a closure tube, the control system 12950 may be configured such that the primary set point SP1 is a desired closure force value and the primary controller 12952 is configured to receive the closure force from a torque sensor coupled to the output of a closure motor and determine a set point SP2 motor velocity for the closure motor. In other aspects, the closure force may be measured with strain gauges, load cells, or other suitable force sensors. The closure motor velocity set point SP2 is compared to the actual velocity of the closure tube, which is determined by the secondary controller 12955. The actual velocity of the closure tube may be measured by comparing measuring the displacement of the closure tube with the position sensor and measuring elapsed time with a timer/counter. Other techniques, such as linear or rotary encoders may be employed to measure displacement of the closure tube. The output 12968 of the secondary process 12960 is the actual velocity of the closure tube. This closure tube velocity output 12968 is provided to the primary process 12958 which determines the force acting on the closure tube and is fed back to the adder 12962, which subtracts the measured closure force from the primary set point SP1. The primary set point SP, may be an upper threshold or a lower threshold. Based on the output of the adder 12962, the primary controller 12952 controls the velocity and direction of the closure motor. The secondary controller 12955 controls the velocity of the closure motor based on the actual velocity of closure tube measured by the secondary process 12960 and the secondary set point SP2, which is based on a comparison of the actual firing force and the firing force upper and lower thresholds.
In accordance with the PID algorithm, the “P” element 12974 accounts for present values of the error. For example, if the error is large and positive, the control output will also be large and positive. In accordance with the present disclosure, the error term e(t) is the different between the desired closure force and the measured closure force of the closure tube. The “I” element 12976 accounts for past values of the error. For example, if the current output is not sufficiently strong, the integral of the error will accumulate over time, and the controller will respond by applying a stronger action. The “D” element 12978 accounts for possible future trends of the error, based on its current rate of change. For example, continuing the P example above, when the large positive control output succeeds in bringing the error closer to zero, it also puts the process on a path to large negative error in the near future. In this case, the derivative turns negative and the D module reduces the strength of the action to prevent this overshoot.
It will be appreciated that other variables and set points may be monitored and controlled in accordance with the feedback control systems 12950, 12970. For example, the adaptive closure member velocity control algorithm described herein may measure at least two of the following parameters: firing member stroke location, firing member load, displacement of cutting element, velocity of cutting element, closure tube stroke location, closure tube load, among others.
Ultrasonic surgical devices, such as ultrasonic scalpels, are finding increasingly widespread applications in surgical procedures by virtue of their unique performance characteristics. Depending upon specific device configurations and operational parameters, ultrasonic surgical devices can provide substantially simultaneous transection of tissue and homeostasis by coagulation, desirably minimizing patient trauma. An ultrasonic surgical device may comprise a handpiece containing an ultrasonic transducer, and an instrument coupled to the ultrasonic transducer having a distally-mounted end effector (e.g., a blade tip) to cut and seal tissue. In some cases, the instrument may be permanently affixed to the handpiece. In other cases, the instrument may be detachable from the handpiece, as in the case of a disposable instrument or an interchangeable instrument. The end effector transmits ultrasonic energy to tissue brought into contact with the end effector to realize cutting and sealing action. Ultrasonic surgical devices of this nature can be configured for open surgical use, laparoscopic, or endoscopic surgical procedures including robotic-assisted procedures.
Ultrasonic energy cuts and coagulates tissue using temperatures lower than those used in electrosurgical procedures and can be transmitted to the end effector by an ultrasonic generator in communication with the handpiece. Vibrating at high frequencies (e.g., 55,500 cycles per second), the ultrasonic blade denatures protein in the tissue to form a sticky coagulum. Pressure exerted on tissue by the blade surface collapses blood vessels and allows the coagulum to form a hemostatic seal. A surgeon can control the cutting speed and coagulation by the force applied to the tissue by the end effector, the time over which the force is applied, and the selected excursion level of the end effector.
The ultrasonic transducer may be modeled as an equivalent circuit comprising a first branch having a static capacitance and a second “motional” branch having a serially connected inductance, resistance and capacitance that define the electromechanical properties of a resonator. Known ultrasonic generators may include a tuning inductor for tuning out the static capacitance at a resonant frequency so that substantially all of a generator's drive signal current flows into the motional branch. Accordingly, by using a tuning inductor, the generator's drive signal current represents the motional branch current, and the generator is thus able to control its drive signal to maintain the ultrasonic transducer's resonant frequency. The tuning inductor may also transform the phase impedance plot of the ultrasonic transducer to improve the generator's frequency lock capabilities. However, the tuning inductor must be matched with the specific static capacitance of an ultrasonic transducer at the operational resonant frequency. In other words, a different ultrasonic transducer having a different static capacitance requires a different tuning inductor.
Additionally, in some ultrasonic generator architectures, the generator's drive signal exhibits asymmetrical harmonic distortion that complicates impedance magnitude and phase measurements. For example, the accuracy of impedance phase measurements may be reduced due to harmonic distortion in the current and voltage signals.
Moreover, electromagnetic interference in noisy environments decreases the ability of the generator to maintain lock on the ultrasonic transducer's resonant frequency, increasing the likelihood of invalid control algorithm inputs.
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 may comprise a handpiece and 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 may also comprise 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 handpiece. 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 300 kHz to 1 MHz, as described in EN60601-2-2:2009+A11:2011, Definition 201.3.218−HIGH FREQUENCY. For example, the frequencies in monopolar RF applications are typically restricted to less than 5 MHz. However, in bipolar RF applications, the frequency can be almost any value. Frequencies above 200 kHz are typically used for monopolar applications in order to avoid the unwanted stimulation of nerves and muscles which would result from the use of low frequency current. Lower frequencies may be used for bipolar techniques if a 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. It is generally recognized that 10 mA is the lower threshold of thermal effects on tissue.
During its operation, 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 may be 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 may be useful for removing, shrinking, or sculpting soft tissue while simultaneously sealing blood vessels. RF energy may work particularly well on connective tissue, which is primarily comprised of collagen and shrinks when contacted by heat.
Due to their unique drive signal, sensing and feedback needs, ultrasonic and electrosurgical devices have generally required different generators. Additionally, in cases where the instrument is disposable or interchangeable with a handpiece, ultrasonic and electrosurgical generators are limited in their ability to recognize the particular instrument configuration being used and to optimize control and diagnostic processes accordingly. Moreover, capacitive coupling between the non-isolated and patient-isolated circuits of the generator, especially in cases where higher voltages and frequencies are used, may result in exposure of a patient to unacceptable levels of leakage current.
Furthermore, due to their unique drive signal, sensing and feedback needs, ultrasonic and electrosurgical devices have generally required different user interfaces for the different generators. In such conventional ultrasonic and electrosurgical devices, one user interface is configured for use with an ultrasonic instrument whereas a different user interface may be configured for use with an electrosurgical instrument. Such user interfaces include hand and/or foot activated user interfaces such as hand activated switches and/or foot activated switches. As various aspects of combined generators for use with both ultrasonic and electrosurgical instruments are contemplated in the subsequent disclosure, additional user interfaces that are configured to operate with both ultrasonic and/or electrosurgical instrument generators also are contemplated.
Additional user interfaces for providing feedback, whether to the user or other machine, are contemplated within the subsequent disclosure to provide feedback indicating an operating mode or status of either an ultrasonic and/or electrosurgical instrument. Providing user and/or machine feedback for operating a combination ultrasonic and/or electrosurgical instrument will require providing sensory feedback to a user and electrical/mechanical/electro-mechanical feedback to a machine. Feedback devices that incorporate visual feedback devices (e.g., an LCD display screen, LED indicators), audio feedback devices (e.g., a speaker, a buzzer) or tactile feedback devices (e.g., haptic actuators) for use in combined ultrasonic and/or electrosurgical instruments are contemplated in the subsequent disclosure.
Other electrical surgical instruments include, without limitation, irreversible and/or reversible electroporation, and/or microwave technologies, among others. Accordingly, the techniques disclosed herein are applicable to ultrasonic, bipolar or monopolar RF (electrosurgical), irreversible and/or reversible electroporation, and/or microwave based surgical instruments, among others.
Various aspects are directed to improved ultrasonic surgical devices, electrosurgical devices and generators for use therewith. Aspects of the ultrasonic surgical devices can be configured for transecting and/or coagulating tissue during surgical procedures, for example. Aspects of the electrosurgical devices can be configured for transecting, coagulating, scaling, welding and/or desiccating tissue during surgical procedures, for example.
Aspects of the generator utilize high-speed analog-to-digital sampling (e.g., approximately 200× oversampling, depending on frequency) of the generator drive signal current and voltage, along with digital signal processing, to provide a number of advantages and benefits over known generator architectures. In one aspect, for example, based on current and voltage feedback data, a value of the ultrasonic transducer static capacitance, and a value of the drive signal frequency, the generator may determine the motional branch current of an ultrasonic transducer. This provides the benefit of a virtually tuned system, and simulates the presence of a system that is tuned or resonant with any value of the static capacitance (e.g., C0 in
High-speed analog-to-digital sampling of the generator drive signal current and voltage, along with digital signal processing, may also enable precise digital filtering of the samples. For example, aspects of the generator may utilize a low-pass digital filter (e.g., a finite impulse response (FIR) filter) that rolls off between a fundamental drive signal frequency and a second-order harmonic to reduce the asymmetrical harmonic distortion and EMI-induced noise in current and voltage feedback samples. The filtered current and voltage feedback samples represent substantially the fundamental drive signal frequency, thus enabling a more accurate impedance phase measurement with respect to the fundamental drive signal frequency and an improvement in the generator's ability to maintain resonant frequency lock. The accuracy of the impedance phase measurement may be further enhanced by averaging falling edge and rising edge phase measurements, and by regulating the measured impedance phase to 0°.
Various aspects of the generator may also utilize the high-speed analog-to-digital sampling of the generator drive signal current and voltage, along with digital signal processing, to determine real power consumption and other quantities with a high degree of precision. This may allow the generator to implement a number of useful algorithms, such as, for example, controlling the amount of power delivered to tissue as the impedance of the tissue changes and controlling the power delivery to maintain a constant rate of tissue impedance increase. Some of these algorithms are used to determine the phase difference between the generator drive signal current and voltage signals. At resonance, the phase difference between the current and voltage signals is zero. The phase changes as the ultrasonic system goes off-resonance. Various algorithms may be employed to detect the phase difference and adjust the drive frequency until the ultrasonic system returns to resonance, i.e., the phase difference between the current and voltage signals goes to zero. The phase information also may be used to infer the conditions of the ultrasonic blade. As discussed with particularity below, the phase changes as a function of the temperature of the ultrasonic blade. Therefore, the phase information may be employed to control the temperature of the ultrasonic blade. This may be done, for example, by reducing the power delivered to the ultrasonic blade when the ultrasonic blade runs too hot and increasing the power delivered to the ultrasonic blade when the ultrasonic blade runs too cold.
Various aspects of the generator may have a wide frequency range and increased output power necessary to drive both ultrasonic surgical devices and electrosurgical devices. The lower voltage, higher current demand of electrosurgical devices may be met by a dedicated tap on a wideband power transformer, thereby eliminating the need for a separate power amplifier and output transformer. Moreover, sensing and feedback circuits of the generator may support a large dynamic range that addresses the needs of both ultrasonic and electrosurgical applications with minimal distortion.
Various aspects may provide a simple, economical means for the generator to read from, and optionally write to, a data circuit (e.g., a single-wire bus device, such as a one-wire protocol EEPROM known under the trade name “1-Wire”) disposed in an instrument attached to the handpiece using existing multi-conductor generator/handpiece cables. In this way, the generator is able to retrieve and process instrument-specific data from an instrument attached to the handpiece. This may enable the generator to provide better control and improved diagnostics and error detection. Additionally, the ability of the generator to write data to the instrument makes possible new functionality in terms of, for example, tracking instrument usage and capturing operational data. Moreover, the use of frequency band permits the backward compatibility of instruments containing a bus device with existing generators.
Disclosed aspects of the generator provide active cancellation of leakage current caused by unintended capacitive coupling between non-isolated and patient-isolated circuits of the generator. In addition to reducing patient risk, the reduction of leakage current may also lessen electromagnetic emissions.
In one aspect shown, the plurality of circuit segments 7402, 7414, 7416, 7420, 7424, 7428, 7434, 7440 start first in the standby mode, transition second to the sleep mode, and transition third to the operational mode. However, in other aspects, the plurality of circuit segments may transition from any one of the three modes to any other one of the three modes. For example, the plurality of circuit segments may transition directly from the standby mode to the operational mode. Individual circuit segments may be placed in a particular state by the voltage control circuit 7408 based on the execution by a processor of machine executable instructions. The states comprise a deenergized state, a low energy state, and an energized state. The deenergized state corresponds to the sleep mode, the low energy state corresponds to the standby mode, and the energized state corresponds to the operational mode. Transition to the low energy state may be achieved by, for example, the use of a potentiometer.
In one aspect, the plurality of circuit segments 7402, 7414, 7416, 7420, 7424, 7428, 7434, 7440 may transition from the sleep mode or the standby mode to the operational mode in accordance with an energization sequence. The plurality of circuit segments also may transition from the operational mode to the standby mode or the sleep mode in accordance with a deenergization sequence. The energization sequence and the deenergization sequence may be different. In some aspects, the energization sequence comprises energizing only a subset of circuit segments of the plurality of circuit segments. In some aspects, the deenergization sequence comprises deenergizing only a subset of circuit segments of the plurality of circuit segments.
Referring back to the system diagram 7400 in
In some aspects, the wake up circuit 7404 comprises an accelerometer button sensor 7405. In aspects, the transition circuit segment 7402 is configured to be in an energized state while other circuit segments of the plurality of circuit segments of the segmented circuit 7401 are configured to be in a low energy state, a deenergized state or an energized state. The accelerometer button sensor 7405 may monitor movement or acceleration of the surgical instrument 6480 described herein. For example, the movement may be a change in orientation or rotation of the surgical instrument. The surgical instrument may be moved in any direction relative to a three dimensional Euclidean space by for example, a user of the surgical instrument. When the accelerometer button sensor 7405 senses movement or acceleration, the accelerometer button sensor 7405 sends a signal to the voltage control circuit 7408 to cause the voltage control circuit 7408 to apply voltage to the processor circuit segment 7414 to transition the processor and a volatile memory to an energized state. In aspects, the processor and the volatile memory are in an energized state before the voltage control circuit 7409 applies voltage to the processor and the volatile memory. In the operational mode, the processor may initiate an energization sequence or a deenergization sequence. In various aspects, the accelerometer button sensor 7405 may also send a signal to the processor to cause the processor to initiate an energization sequence or a deenergization sequence. In some aspects, the processor initiates an energization sequence when the majority of individual circuit segments are in a low energy state or a deenergized state. In other aspects, the processor initiates a deenergization sequence when the majority of individual circuit segments are in an energized state.
Additionally or alternatively, the accelerometer button sensor 7405 may sense external movement within a predetermined vicinity of the surgical instrument. For example, the accelerometer button sensor 7405 may sense a user of the surgical instrument 6480 described herein moving a hand of the user within the predetermined vicinity. When the accelerometer button sensor 7405 senses this external movement, the accelerometer button sensor 7405 may send a signal to the voltage control circuit 7408 and a signal to the processor, as previously described. After receiving the sent signal, the processor may initiate an energization sequence or a deenergization sequence to transition one or more circuit segments between the three modes. In aspects, the signal sent to the voltage control circuit 7408 is sent to verify that the processor is in operational mode. In some aspects, the accelerometer button sensor 7405 may sense when the surgical instrument has been dropped and send a signal to the processor based on the sensed drop. For example, the signal can indicate an error in the operation of an individual circuit segment. One or more sensors may sense damage or malfunctioning of the affected individual circuit segments. Based on the sensed damage or malfunctioning, the POST controller 7412 may perform a POST of the corresponding individual circuit segments.
An energization sequence or a deenergization sequence may be defined based on the accelerometer button sensor 7405. For example, the accelerometer button sensor 7405 may sense a particular motion or a sequence of motions that indicates the selection of a particular circuit segment of the plurality of circuit segments. Based on the sensed motion or series of sensed motions, the accelerometer button sensor 7405 may transmit a signal comprising an indication of one or more circuit segments of the plurality of circuit segments to the processor when the processor is in an energized state. Based on the signal, the processor determines an energization sequence comprising the selected one or more circuit segments. Additionally or alternatively, a user of the surgical instruments 6480 described herein may select a number and order of circuit segments to define an energization sequence or a deenergization sequence based on interaction with a graphical user interface (GUI) of the surgical instrument.
In various aspects, the accelerometer button sensor 7405 may send a signal to the voltage control circuit 7408 and a signal to the processor only when the accelerometer button sensor 7405 detects movement of the surgical instrument 6480 described herein or external movement within a predetermined vicinity above a predetermined threshold. For example, a signal may only be sent if movement is sensed for 5 or more seconds or if the surgical instrument is moved 5 or more inches. In other aspects, the accelerometer button sensor 7405 may send a signal to the voltage control circuit 7408 and a signal to the processor only when the accelerometer button sensor 7405 detects oscillating movement of the surgical instrument. A predetermined threshold reduces inadvertent transition of circuit segments of the surgical instrument. As previously described, the transition may comprise a transition to operational mode according to an energization sequence, a transition to low energy mode according to a deenergization sequence, or a transition to sleep mode according to a deenergization sequence. In some aspects, the surgical instrument comprises an actuator that may be actuated by a user of the surgical instrument. The actuation is sensed by the accelerometer button sensor 7405. The actuator may be a slider, a toggle switch, or a momentary contact switch. Based on the sensed actuation, the accelerometer button sensor 7405 may send a signal to the voltage control circuit 7408 and a signal to the processor.
The boost current circuit 7406 is coupled to a battery. The boost current circuit 7406 is a current amplifier, such as a relay or transistor, and is configured to amplify the magnitude of a current of an individual circuit segment. The initial magnitude of the current corresponds to the source voltage provided by the battery to the segmented circuit 7401. Suitable relays include solenoids. Suitable transistors include field-effect transistors (FET), MOSFET, and bipolar junction transistors (BJT). The boost current circuit 7406 may amplify the magnitude of the current corresponding to an individual circuit segment or circuit which requires more current draw during operation of the surgical instruments 6480 described herein. For example, an increase in current to the motor control circuit segment 7428 may be provided when a motor of the surgical instrument requires more input power. The increase in current provided to an individual circuit segment may cause a corresponding decrease in current of another circuit segment or circuit segments. Additionally or alternatively, the increase in current may correspond to voltage provided by an additional voltage source operating in conjunction with the battery.
The voltage control circuit 7408 is coupled to the battery. The voltage control circuit 7408 is configured to provide voltage to or remove voltage from the plurality of circuit segments. The voltage control circuit 7408 is also configured to increase or reduce voltage provided to the plurality of circuit segments of the segmented circuit 7401. In various aspects, the voltage control circuit 7408 comprises a combinational logic circuit such as a multiplexer (MUX) to select inputs, a plurality of electronic switches, and a plurality of voltage converters. An electronic switch of the plurality of electronic switches may be configured to switch between an open and closed configuration to disconnect or connect an individual circuit segment to or from the battery. The plurality of electronic switches may be solid state devices such as transistors or other types of switches such as wireless switches, ultrasonic switches, accelerometers, inertial sensors, among others. The combinational logic circuit is configured to select an individual electronic switch for switching to an open configuration to enable application of voltage to the corresponding circuit segment. The combination logic circuit also is configured to select an individual electronic switch for switching to a closed configuration to enable removal of voltage from the corresponding circuit segment. By selecting a plurality of individual electronic switches, the combination logic circuit may implement a deenergization sequence or an energization sequence. The plurality of voltage converters may provide a stepped-up voltage or a stepped-down voltage to the plurality of circuit segments. The voltage control circuit 7408 may also comprise a microprocessor and memory device.
The safety controller 7410 is configured to perform safety checks for the circuit segments. In some aspects, the safety controller 7410 performs the safety checks when one or more individual circuit segments are in the operational mode. The safety checks may be performed to determine whether there are any errors or defects in the functioning or operation of the circuit segments. The safety controller 7410 may monitor one or more parameters of the plurality of circuit segments. The safety controller 7410 may verify the identity and operation of the plurality of circuit segments by comparing the one or more parameters with predefined parameters. For example, if an RF energy modality is selected, the safety controller 7410 may verify that an articulation parameter of the shaft matches a predefined articulation parameter to verify the operation of the RF energy modality of the surgical instrument 6480 described herein. In some aspects, the safety controller 7410 may monitor, by the sensors, a predetermined relationship between one or more properties of the surgical instrument to detect a fault. A fault may arise when the one or more properties are inconsistent with the predetermined relationship. When the safety controller 7410 determines that a fault exists, an error exists, or that some operation of the plurality of circuit segments was not verified, the safety controller 7410 prevents or disables operation of the particular circuit segment where the fault, error or verification failure originated.
The POST controller 7412 performs a POST to verify proper operation of the plurality of circuit segments. In some aspects, the POST is performed for an individual circuit segment of the plurality of circuit segments prior to the voltage control circuit 7408 applying a voltage to the individual circuit segment to transition the individual circuit segment from standby mode or sleep mode to operational mode. If the individual circuit segment does not pass the POST, the particular circuit segment does not transition from standby mode or sleep mode to operational mode. POST of the handle circuit segment 7416 may comprise, for example, testing whether the handle control sensors 7418 sense an actuation of a handle control of the surgical instrument 6480 described herein. In some aspects, the POST controller 7412 may transmit a signal to the accelerometer button sensor 7405 to verify the operation of the individual circuit segment as part of the POST. For example, after receiving the signal, the accelerometer button sensor 7405 may prompt a user of the surgical instrument to move the surgical instrument to a plurality of varying locations to confirm operation of the surgical instrument. The accelerometer button sensor 7405 may also monitor an output of a circuit segment or a circuit of a circuit segment as part of the POST. For example, the accelerometer button sensor 7405 can sense an incremental motor pulse generated by the motor 7432 to verify operation. A motor controller of the motor control circuit 7430 may be used to control the motor 7432 to generate the incremental motor pulse.
In various aspects, the surgical instrument 6480 described herein may comprise additional accelerometer button sensors. The POST controller 7412 may also execute a control program stored in the memory device of the voltage control circuit 7408. The control program may cause the POST controller 7412 to transmit a signal requesting a matching encrypted parameter from a plurality of circuit segments. Failure to receive a matching encrypted parameter from an individual circuit segment indicates to the POST controller 7412 that the corresponding circuit segment is damaged or malfunctioning. In some aspects, if the POST controller 7412 determines based on the POST that the processor is damaged or malfunctioning, the POST controller 7412 may send a signal to one or more secondary processors to cause one or more secondary processors to perform critical functions that the processor is unable to perform. In some aspects, if the POST controller 7412 determines based on the POST that one or more circuit segments do not operate properly, the POST controller 7412 may initiate a reduced performance mode of those circuit segments operating properly while locking out those circuit segments that fail POST or do not operate properly. A locked out circuit segment may function similarly to a circuit segment in standby mode or sleep mode.
The processor circuit segment 7414 comprises the processor and the volatile memory. The processor is configured to initiate an energization or a deenergization sequence. To initiate the energization sequence, the processor transmits an energizing signal to the voltage control circuit 7408 to cause the voltage control circuit 7408 to apply voltage to the plurality or a subset of the plurality of circuit segments in accordance with the energization sequence. To initiate the deenergization sequence, the processor transmits a deenergizing signal to the voltage control circuit 7408 to cause the voltage control circuit 7408 to remove voltage from the plurality or a subset of the plurality of circuit segments in accordance with the deenergization sequence.
The handle circuit segment 7416 comprises handle control sensors 7418. The handle control sensors 7418 may sense an actuation of one or more handle controls of the surgical instrument 6480 described herein. In various aspects, the one or more handle controls comprise a clamp control, a release button, an articulation switch, an energy activation button, and/or any other suitable handle control. The user may activate the energy activation button to select between an RF energy mode, an ultrasonic energy mode or a combination RF and ultrasonic energy mode. The handle control sensors 7418 may also facilitate attaching a modular handle to the surgical instrument. For example, the handle control sensors 7418 may sense proper attachment of the modular handle to the surgical instrument and indicate the sensed attachment to a user of the surgical instrument. The LCD display 7426 may provide a graphical indication of the sensed attachment. In some aspects, the handle control sensors 7418 senses actuation of the one or more handle controls. Based on the sensed actuation, the processor may initiate either an energization sequence or a deenergization sequence.
The communication circuit segment 7420 comprises a communication circuit 7422. The communication circuit 7422 comprises a communication interface to facilitate signal communication between the individual circuit segments of the plurality of circuit segments. In some aspects, the communication circuit 7422 provides a path for the modular components of the surgical instrument 6480 described herein to communicate electrically. For example, a modular shaft and a modular transducer, when attached together to the handle of the surgical instrument, can upload control programs to the handle through the communication circuit 7422.
The display circuit segment 7424 comprises a LCD display 7426. The LCD display 7426 may comprise a liquid crystal display screen, LED indicators, etc. In some aspects, the LCD display 7426 is an organic light-emitting diode (OLED) screen. A display may be placed on, embedded in, or located remotely from the surgical instrument 6480 described herein. For example, the display can be placed on the handle of the surgical instrument. The display is configured to provide sensory feedback to a user. In various aspects, the LCD display 7426 further comprises a backlight. In some aspects, the surgical instrument may also comprise audio feedback devices such as a speaker or a buzzer and tactile feedback devices such as a haptic actuator.
The motor control circuit segment 7428 comprises a motor control circuit 7430 coupled to a motor 7432. The motor 7432 is coupled to the processor by a driver and a transistor, such as a FET. In various aspects, the motor control circuit 7430 comprises a motor current sensor in signal communication with the processor to provide a signal indicative of a measurement of the current draw of the motor to the processor. The processor transmits the signal to the display. The display receives the signal and displays the measurement of the current draw of the motor 7432. The processor may use the signal, for example, to monitor that the current draw of the motor 7432 exists within an acceptable range, to compare the current draw to one or more parameters of the plurality of circuit segments, and to determine one or more parameters of a patient treatment site. In various aspects, the motor control circuit 7430 comprises a motor controller to control the operation of the motor. For example, the motor control circuit 7430 controls various motor parameters, such as by adjusting the velocity, torque and acceleration of the motor 7432. The adjusting is done based on the current through the motor 7432 measured by the motor current sensor.
In various aspects, the motor control circuit 7430 comprises a force sensor to measure the force and torque generated by the motor 7432. The motor 7432 is configured to actuate a mechanism of the surgical instruments 6480 described herein. For example, the motor 7432 is configured to control actuation of the shaft of the surgical instrument to realize clamping, rotation and articulation functionality. For example, the motor 7432 may actuate the shaft to realize a clamping motion with jaws of the surgical instrument. The motor controller may determine whether the material clamped by the jaws is tissue or metal. The motor controller may also determine the extent to which the jaws clamp the material. For example, the motor controller may determine how open or closed the jaws are based on the derivative of sensed motor current or motor voltage. In some aspects, the motor 7432 is configured to actuate the transducer to cause the transducer to apply torque to the handle or to control articulation of the surgical instrument. The motor current sensor may interact with the motor controller to set a motor current limit. When the current meets the predefined threshold limit, the motor controller initiates a corresponding change in a motor control operation. For example, exceeding the motor current limit causes the motor controller to reduce the current draw of the motor.
The energy treatment circuit segment 7434 comprises a RF amplifier and safety circuit 7436 and an ultrasonic signal generator circuit 7438 to implement the energy modular functionality of the surgical instrument 6480 described herein. In various aspects, the RF amplifier and safety circuit 7436 is configured to control the RF modality of the surgical instrument by generating an RF signal. The ultrasonic signal generator circuit 7438 is configured to control the ultrasonic energy modality by generating an ultrasonic signal. The RF amplifier and safety circuit 7436 and an ultrasonic signal generator circuit 7438 may operate in conjunction to control the combination RF and ultrasonic energy modality.
The shaft circuit segment 7440 comprises a shaft module controller 7442, a modular control actuator 7444, one or more end effector sensors 7446, and a non volatile memory 7448. The shaft module controller 7442 is configured to control a plurality of shaft modules comprising the control programs to be executed by the processor. The plurality of shaft modules implements a shaft modality, such as ultrasonic, combination ultrasonic and RF, RF I-blade, and RF-opposable jaw. The shaft module controller 7442 can select shaft modality by selecting the corresponding shaft module for the processor to execute. The modular control actuator 7444 is configured to actuate the shaft according to the selected shaft modality. After actuation is initiated, the shaft articulates the end effector according to the one or more parameters, routines or programs specific to the selected shaft modality and the selected end effector modality. The one or more end effector sensors 7446 located at the end effector may include force sensors, temperature sensors, current sensors or motion sensors. The one or more end effector sensors 7446 transmit data about one or more operations of the end effector, based on the energy modality implemented by the end effector. In various aspects, the energy modalities include an ultrasonic energy modality, a RF energy modality, or a combination of the ultrasonic energy modality and the RF energy modality. The non volatile memory 7448 stores the shaft control programs. A control program comprises one or more parameters, routines or programs specific to the shaft. In various aspects, the non volatile memory 7448 may be an ROM, EPROM, EEPROM or flash memory. The non volatile memory 7448 stores the shaft modules corresponding to the selected shaft of the surgical instrument 6480 described herein in. The shaft modules may be changed or upgraded in the non volatile memory 7448 by the shaft module controller 7442, depending on the surgical instrument shaft to be used in operation.
The drive mechanism 7930 includes a selector gearbox assembly 7938 that can be located in the handle assembly of the surgical instrument. Proximal to the selector gearbox assembly 7938 is a function selection module which includes a first motor 7942 that functions to selectively move gear elements within the selector gearbox assembly 7938 to selectively position one of the drivetrains 7932, 7934, 7936 into engagement with an input drive component of an optional second motor 7944 and motor drive circuit 7946 (shown in dashed line to indicate that the second motor 7944 and motor drive circuit 7946 are optional components).
Still referring to
The surgical instrument further includes a microcontroller 7952 (“controller”). In certain instances, the controller 7952 may include a microprocessor 7954 (“processor”) and one or more computer readable mediums or memory units 7956 (“memory”). In certain instances, the memory 7956 may store various program instructions, which when executed may cause the processor 7954 to perform a plurality of functions and/or calculations described herein. The power source 7950 can be configured to supply power to the controller 7952, for example.
The processor 7954 may be in communication with the motor control circuit 7946. In addition, the memory 7956 may store program instructions, which when executed by the processor 7954 in response to a user input 7958 or feedback elements 7960, may cause the motor control circuit 7946 to motivate the motor 7942 to generate at least one rotational motion to selectively move gear elements within the selector gearbox assembly 7938 to selectively position one of the drivetrains 7932, 7934, 7936 into engagement with the input drive component of the second motor 7944. Furthermore, the processor 7954 can be in communication with the motor control circuit 7948. The memory 7956 also may store program instructions, which when executed by the processor 7954 in response to a user input 7958, may cause the motor control circuit 7948 to motivate the motor 7944 to generate at least one rotational motion to drive the drivetrain engaged with the input drive component of the second motor 7948, for example.
The controller 7952 and/or other controllers of the present disclosure may be implemented using integrated and/or discrete hardware elements, software elements, and/or a combination of both. Examples of integrated hardware elements may include processors, microprocessors, microcontrollers, integrated circuits, ASICs, PLDs, DSPs, FPGAs, logic gates, registers, semiconductor devices, chips, microchips, chip sets, microcontrollers, system on a chip (SoC), and/or single in-line package (SIP). Examples of discrete hardware elements may include circuits and/or circuit elements such as logic gates, field effect transistors, bipolar transistors, resistors, capacitors, inductors, and/or relays. In certain instances, the controller 7952 may include a hybrid circuit comprising discrete and integrated circuit elements or components on one or more substrates, for example.
In certain instances, the controller 7952 and/or other controllers of the present disclosure may be an LM 4F230H5QR, available from Texas Instruments, for example. In certain instances, the Texas Instruments LM4F230H5QR is an ARM Cortex-M4F Processor Core comprising on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle SRAM, internal ROM loaded with StellarisWare® software, 2 KB EEPROM, one or more PWM modules, one or more QEI analog, one or more 12-bit ADC with 12 analog input channels, among other features that are readily available. Other microcontrollers may be readily substituted for use with the present disclosure. Accordingly, the present disclosure should not be limited in this context.
In various instances, one or more of the various steps described herein can be performed by a finite state machine comprising either a combinational logic circuit or a sequential logic circuit, where either the combinational logic circuit or the sequential logic circuit is coupled to at least one memory circuit. The at least one memory circuit stores a current state of the finite state machine. The combinational or sequential logic circuit is configured to cause the finite state machine to the steps. The sequential logic circuit may be synchronous or asynchronous. In other instances, one or more of the various steps described herein can be performed by a circuit that includes a combination of the processor 7958 and the finite state machine, for example.
In various instances, it can be advantageous to be able to assess the state of the functionality of a surgical instrument to ensure its proper function. It is possible, for example, for the drive mechanism, as explained above, which is configured to include various motors, drivetrains, and/or gear components in order to perform the various operations of the surgical instrument, to wear out over time. This can occur through normal use, and in some instances the drive mechanism can wear out faster due to abuse conditions. In certain instances, a surgical instrument can be configured to perform self-assessments to determine the state, e.g. health, of the drive mechanism and it various components.
For example, the self-assessment can be used to determine when the surgical instrument is capable of performing its function before a re-sterilization or when some of the components should be replaced and/or repaired. Assessment of the drive mechanism and its components, including but not limited to the rotation drivetrain 7932, the closure drivetrain 7934, and/or the firing drivetrain 7936, can be accomplished in a variety of ways. The magnitude of deviation from a predicted performance can be used to determine the likelihood of a sensed failure and the severity of such failure. Several metrics can be used including: Periodic analysis of repeatably predictable events, Peaks or drops that exceed an expected threshold, and width of the failure.
In various instances, a signature waveform of a properly functioning drive mechanism or one or more of its components can be employed to assess the state of the drive mechanism or the one or more of its components. One or more vibration sensors can be arranged with respect to a properly functioning drive mechanism or one or more of its components to record various vibrations that occur during operation of the properly functioning drive mechanism or the one or more of its components. The recorded vibrations can be employed to create the signature waveform. Future waveforms can be compared against the signature waveform to assess the state of the drive mechanism and its components.
Still referring to
The outputs of the voltage and current sensors 132018, 132020 are applied to another phase/frequency detector 132022 to determine the phase angle between the voltage and current as measured by the voltage and current sensors 132018, 132020. The output of the phase/frequency detector 132022 is applied to one channel of a high speed analog to digital converter 132024 (ADC) and is provided to the processor 132004 therethrough. Optionally, the outputs of the voltage and current sensors 132018, 132020 may be applied to respective channels of the two-channel ADC 132024 and provided to the processor 132004 for zero crossing, FFT, or other algorithm described herein for determining the phase angle between the voltage and current signals applied to the ultrasonic electromechanical system 132002.
Optionally the tuning voltage Vt, which is proportional to the output frequency fo, may be fed back to the processor 132004 via the ADC 132024. This provides the processor 132004 with a feedback signal proportional to the output frequency fo and can use this feedback to adjust and control the output frequency fo.
The ultrasonic transducer impedance Zg(t) can be measured as the ratio of the drive signal generator voltage Vg(t) and current Ig(t) drive signals:
As shown in
With reference now back to
As previously described, an electromechanical ultrasonic system includes an ultrasonic transducer, a waveguide, and an ultrasonic blade. As previously discussed, the ultrasonic transducer may be modeled as an equivalent series resonant circuit (see
Stated in another way, at resonance, the analogous inductive impedance of the electromechanical ultrasonic system is equal to the analogous capacitive impedance of the electromechanical ultrasonic system. As the ultrasonic blade heats up, for example due to frictional engagement with tissue, the compliance of the ultrasonic blade (modeled as an analogous capacitance) causes the resonant frequency of the electromechanical ultrasonic system to shift. In the present example, the resonant frequency of the electromechanical ultrasonic system decreases as the temperature of the ultrasonic blade increases. Thus, the analogous inductive impedance of the electromechanical ultrasonic system is no longer equal to the analogous capacitive impedance of the electromechanical ultrasonic system causing a mismatch between the drive frequency and the new resonant frequency of the electromechanical ultrasonic system. Thus, with a hot ultrasonic blade, the electromechanical ultrasonic system operates “off-resonance.” The mismatch between the drive frequency and the resonant frequency is manifested as a phase angle φ between the voltage Vg(t) and current Ig(t) signals applied to the ultrasonic transducer.
As previously discussed, the generator electronics can easily monitor the phase angle φ between the voltage Vg(t) and current Ig(t) signals applied to the ultrasonic transducer. The phase angle φ may be determined through Fourier analysis, weighted least-squares estimation, Kalman filtering, space-vector-based techniques, zero-crossing method, Lissajous figures, three-voltmeter method, crossed-coil method, vector voltmeter and vector impedance methods, phase standard instruments, phase-locked loops, among other techniques previously described. The generator can continuously monitor the phase angle φ and adjust the drive frequency until the phase angle φ goes to zero. At this point, the new drive frequency is equal to the new resonant frequency of the electromechanical ultrasonic system. The change in phase angle φ and/or generator drive frequency can be used as an indirect or inferred measurement of the temperature of the ultrasonic blade.
A variety of techniques are available to estimate temperature from the data in these spectra. Most notably, a time variant, non-linear set of state space equations can be employed to model the dynamic relationship between the temperature of the ultrasonic blade and the measured impedance
across a range of generator drive frequencies, where the range of generator drive frequencies is specific to device model.
One aspect of estimating or inferring the temperature of an ultrasonic blade may include three steps. First, define a state space model of temperature and frequency that is time and energy dependent. To model temperature as a function of frequency content, a set of non-linear state space equations are used to model the relationship between the electromechanical resonant frequency and the temperature of the ultrasonic blade. Second, apply a Kalman filter to improve the accuracy of the temperature estimator and state space model over time. Third, a state estimator is provided in the feedback loop of the Kalman filter to control the power applied to the ultrasonic transducer, and hence the ultrasonic blade, to regulate the temperature of the ultrasonic blade. The three steps are described hereinbelow.
The first step is to define a state space model of temperature and frequency that is time and energy dependent. To model temperature as a function of frequency content, a set of non-linear state space equations are used to model the relationship between the electromechanical resonant frequency and the temperature of the ultrasonic blade. In one aspect, the state space model is given by:
The state space model represents the rate of change of the natural frequency of the electromechanical ultrasonic system {dot over (F)}n and the rate of change of the temperature {dot over (T)} of the ultrasonic blade with respect to natural frequency Fn(t), temperature T(t), energy E(t), and time t. {dot over (y)} represents the observability of variables that are measurable and observable such as the natural frequency Fn(t) of the electromechanical ultrasonic system, the temperature T(t) of the ultrasonic blade, the energy E(t) applied to the ultrasonic blade, and time t. The temperature T(t) of the ultrasonic blade is observable as an estimate.
The second step is to apply a Kalman filter to improve temperature estimator and state space model.
which represents the impedance across an ultrasonic transducer measured at a variety of frequencies, in accordance with at least one aspect of the present disclosure.
The Kalman filter 133020 may be employed to improve the performance of the temperature estimate and allows for the augmentation of external sensors, models, or prior information to improve temperature prediction in the midst of noisy data. The Kalman filter 133020 includes a regulator 133022 and a plant 133024. In control theory a plant 133024 is the combination of process and actuator. A plant 133024 may be referred to with a transfer function which indicates the relation between an input signal and the output signal of a system. The regulator 133022 includes a state estimator 133026 and a controller K 133028. The state regulator 133026 includes a feedback loop 133030. The state regulator 133026 receives y, the output of the plant 133024, as an input and a feedback variable u. The state estimator 133026 is an internal feedback system that converges to the true value of the state of the system. The output of the state estimator 133026 is {circumflex over (x)}, the full feedback control variable including Fn(t) of the electromechanical ultrasonic system, the estimate of the temperature T(t) of the ultrasonic blade, the energy E(t) applied to the ultrasonic blade, the phase angle φ, and time t. The input into the controller K 133028 is {circumflex over (x)} and the output of the controller K 133028 u is fed back to the state estimator 133026 and t of the plant 133024.
Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe and thus calculating the maximum likelihood estimate of actual measurements. The algorithm works in a two-step process. In a prediction step, the Kalman filter 133020 produces estimates of the current state variables, along with their uncertainties. Once the outcome of the next measurement (necessarily corrupted with some amount of error, including random noise) is observed, these estimates are updated using a weighted average, with more weight being given to estimates with higher certainty. The algorithm is recursive and can run in real time, using only the present input measurements and the previously calculated state and its uncertainty matrix; no additional past information is required.
The Kalman filter 133020 uses a dynamics model of the electromechanical ultrasonic system, known control inputs to that system, and multiple sequential measurements (observations) of the natural frequency and phase angle of the applied signals (e.g., magnitude and phase of the electrical impedance of the ultrasonic transducer) to the ultrasonic transducer to form an estimate of the varying quantities of the electromechanical ultrasonic system (its state) to predict the temperature of the ultrasonic blade portion of the electromechanical ultrasonic system that is better than an estimate obtained using only one measurement alone. As such, the Kalman filter 133020 is an algorithm that includes sensor and data fusion to provide the maximum likelihood estimate of the temperature of the ultrasonic blade.
The Kalman filter 133020 deals effectively with uncertainty due to noisy measurements of the applied signals to the ultrasonic transducer to measure the natural frequency and phase shift data and also deals effectively with uncertainty due to random external factors. The Kalman filter 133020 produces an estimate of the state of the electromechanical ultrasonic system as an average of the predicted state of the system and of the new measurement using a weighted average. Weighted values provide better (i.e., smaller) estimated uncertainty and are more “trustworthy” than unweighted values The weights may be calculated from the covariance, a measure of the estimated uncertainty of the prediction of the system's state. The result of the weighted average is a new state estimate that lies between the predicted and measured state, and has a better estimated uncertainty than either alone. This process is repeated at every time step, with the new estimate and its covariance informing the prediction used in the following iteration. This recursive nature of the Kalman filter 133020 requires only the last “best guess,” rather than the entire history, of the state of the electromechanical ultrasonic system to calculate a new state.
The relative certainty of the measurements and current state estimate is an important consideration, and it is common to discuss the response of the filter in terms of the gain K of the Kalman filter 133020. The Kalman gain K is the relative weight given to the measurements and current state estimate, and can be “tuned” to achieve particular performance. With a high gain K, the Kalman filter 133020 places more weight on the most recent measurements, and thus follows them more responsively. With a low gain K, the Kalman filter 133020 follows the model predictions more closely. At the extremes, a high gain close to one will result in a more jumpy estimated trajectory, while low gain close to zero will smooth out noise but decrease the responsiveness.
When performing the actual calculations for the Kalman filter 133020 (as discussed below), the state estimate and covariances are coded into matrices to handle the multiple dimensions involved in a single set of calculations. This allows for a representation of linear relationships between different state variables (such as position, velocity, and acceleration) in any of the transition models or covariances. Using a Kalman filter 133020 does not assume that the errors are Gaussian. However, the Kalman filter 133020 yields the exact conditional probability estimate in the special case that all errors are Gaussian-distributed.
The third step uses a state estimator 133026 in the feedback loop 133032 of the Kalman filter 133020 for control of power applied to the ultrasonic transducer, and hence the ultrasonic blade, to regulate the temperature of the ultrasonic blade.
which is the impedance across the ultrasonic transducer measured at a variety of frequencies, in accordance with at least one aspect of the present disclosure.
The prior probability distribution 133042 includes a state variance defined by the expression:
(σk−)2=σk−12+σP
The state variance (σk−) is used to predict the next state of the system, which is represented as the prediction (state) probability distribution 133044. The observation probability distribution 133046 is the probability distribution of the actual observation of the state of the system where the observation variance σm is used to define the gain, which is given by the following expression:
Power input is decreased to ensure that the temperature (as estimated by the state estimator and of the Kalman filter) is controlled.
In one aspect, the initial proof of concept assumed a static, linear relationship between the natural frequency of the electromechanical ultrasonic system and the temperature of the ultrasonic blade. By reducing the power as a function of the natural frequency of the electromechanical ultrasonic system (i.e., regulating temperature with feedback control), the temperature of the ultrasonic blade tip could be controlled directly. In this example, the temperature of the distal tip of the ultrasonic blade can be controlled to not exceed the melting point of the Teflon pad.
When an ultrasonic blade is immersed in a fluid-filled surgical field, the ultrasonic blade cools down during activation rendering less effective for sealing and cutting tissue in contact therewith. The cooling down of the ultrasonic blade may lead to longer activation times and/or hemostasis issues because adequate heat is not delivered to the tissue. In order to overcome the cooling of the ultrasonic blade, more energy delivery may be required to shorten the transection times and achieve suitable hemostasis under these fluid immersion conditions. Using a frequency-temperature feedback control system, if the ultrasonic blade temperature is detected to, either start out below, or remain below a certain temperature for a certain period of time, the output power of the generator can be increased to compensate for cooling due to blood/saline/other fluid present in the surgical field.
Accordingly, the frequency-temperature feedback control system described herein can improve the performance of an ultrasonic device especially when the ultrasonic blade is located or immersed, partially or wholly, in a fluid-filled surgical field. The frequency-temperature feedback control system described herein minimizes long activation times and/or potential issues with ultrasonic device performance in fluid-filled surgical field.
As previously described, the temperature of the ultrasonic blade may be inferred by detecting the impedance of the ultrasonic transducer given by the following expression:
or equivalently, detecting the phase angle φ between the voltage Vg(t) and current Ig(t) signals applied to the ultrasonic transducer. The phase angle φ information also may be used to infer the conditions of the ultrasonic blade. As discussed with particularity herein, the phase angle φ changes as a function of the temperature of the ultrasonic blade. Therefore, the phase angle φ information may be employed to control the temperature of the ultrasonic blade. This may be done, for example, by reducing the power delivered to the ultrasonic blade when the ultrasonic blade runs too hot and increasing the power delivered to the ultrasonic blade when the ultrasonic blade runs too cold.
With reference to
As shown in
Initially, the temperature of the ultrasonic blade increases as the blade heats up and eventually exceeds the first target temperature threshold T1. The frequency-temperature feedback control algorithm takes over to control the temperature of the blade to T1 until the vessel transection is completed 133118 at t0 and the ultrasonic blade temperature drops below the second target temperature threshold T2. A processor or control circuit of the generator or instrument or both detects when the ultrasonic blade contacts the clamp arm pad. Once the vessel transection is completed at t0 and detected, the frequency-temperature feedback control algorithm switches to controlling the temperature of the ultrasonic blade to the second target threshold T2 to prolong the life of the clam arm pad. The optimal clamp arm pad life temperature for a TEFLON clamp arm pad is approximately 325° C. In one aspect, the advanced tissue treatment can be announced to the user at a second activation tone.
When the vessel transection in not complete, the processor or control circuit of the generator or instrument or both determines 133130 if the temperature of the ultrasonic blade is set at temperature T1 optimized for vessel sealing and transecting. If the ultrasonic blade temperature is set at T1, the process continues along the YES branch and the processor or control circuit of the generator or instrument or both continues to monitor 133124 the phase angle φ between the voltage Vg(t) and current Ig(t) signals applied to the ultrasonic transducer and based on the phase angle φ. If the ultrasonic blade temperature is not set at T1, the process continues along NO branch and the processor or control circuit of the generator or instrument or both continues to apply 133122 a first power level to the ultrasonic transducer.
When the vessel transection is complete, the processor or control circuit of the generator or instrument or both applies 133132 a second power level to the ultrasonic transducer to set the ultrasonic blade to a second target temperature T2 optimized for preserving or extending the life of the clamp arm pad. The processor or control circuit of the generator or instrument or both determines 133134 if the temperature of the ultrasonic blade is at set temperature T2. If the temperature of the ultrasonic blade is set at T2, the process completes 133136 the vessel transection procedure.
Knowing the temperature of the ultrasonic blade at the beginning of a transection can enable the generator to deliver the proper quantity of power to heat up the blade for a quick cut or if the blade is already hot add only as much power as would be needed. This technique can achieve more consistent transection times and extend the life of the clam arm pad (e.g., a TEFLON clamp arm pad). Knowing the temperature of the ultrasonic blade at the beginning of the transection can enable the generator to deliver the right amount of power to the ultrasonic transducer to generate a desired amount of displacement of the ultrasonic blade.
Once the resonant frequency of the ultrasonic blade is determined, the processor or control circuit of the generator or instrument or both determines 133146 the initial temperature of the ultrasonic blade based on the difference between the measured resonant frequency and the baseline resonant frequency. The generator sets the power level delivered the ultrasonic transducer, e.g., by adjusting the voltage Vg(t) or current Ig(t) drive signals or both, to one of the following values prior to activating the ultrasonic transducer.
The processor or control circuit of the generator or instrument or both determines 133148 if the initial temperature of the ultrasonic blade is low. If the initial temperature of the ultrasonic blade is low, the process continues along YES branch and the processor or control circuit of the generator or instrument or both applies 133152 a high power level to the ultrasonic transducer to increase the temperature of the ultrasonic blade and completes 133156 the vessel transection procedure.
If the initial temperature of the ultrasonic blade is not low, the process continues along NO branch and the processor or control circuit of the generator or instrument or both determines 133150 if the initial temperature of the ultrasonic blade is high. If the initial temperature of the ultrasonic blade is high, the process proceeds along YES branch and the processor or control circuit of the generator or instrument or both applies 133154 a low power level to the ultrasonic transducer to decrease the temperature of the ultrasonic blade and completes 133156 the vessel transection procedure. If the initial temperature of the ultrasonic blade is not high, the process continues along NO branch and the processor or control circuit of the generator or instrument or both completes 133156 the vessel transection.
The temperature of an ultrasonic blade and the contents within the jaws of an ultrasonic end effector can be determined using the frequency-temperature feedback control algorithms described herein. The frequency/temperature relationship of the ultrasonic blade is employed to control ultrasonic blade instability with temperature.
As described herein, there is a well-known relationship between the frequency and temperature in ultrasonic blades. Some ultrasonic blades exhibit displacement instability or modal instability in the presence of increasing temperature. This known relationship may be employed to interpret when an ultrasonic blade is approaching instability and then adjusting the power level driving the ultrasonic transducer (e.g., by adjusting the driving voltage Vg(t) or current Ig(t) signals, or both, applied to the ultrasonic transducer) to modulate the temperature of the ultrasonic blade to prevent instability of the ultrasonic blade.
Advantages include simplification of ultrasonic blade configurations such that the instability characteristics of the ultrasonic blade do not need to be designed out and can be compensated using the present instability control technique. The present instability control technique also enables new ultrasonic blade geometries and can improve stress profile in heated ultrasonic blades. Additionally, ultrasonic blades can be configured to diminish performance of the ultrasonic blade if used with generators that do not employ this technique.
In accordance with the process depicted by the logic flow diagram 133160, the processor or control circuit of the generator or instrument or both monitors 133162 the phase angle φ between the voltage Vg(t) and current Ig(t) signals applied to the ultrasonic transducer. The processor or control circuit of the generator or instrument or both infers 133164 the temperature of the ultrasonic blade based on the phase angle φ between the voltage Vg(t) and current Ig(t) signals applied to the ultrasonic transducer. The processor or control circuit of the generator or instrument or both compares 133166 the inferred temperature of the ultrasonic blade to an ultrasonic blade instability trigger point threshold. The processor or control circuit of the generator or instrument or both determines 133168 whether the ultrasonic blade is approaching instability. If not, the process proceed along the NO branch and monitors 133162 the phase angle φ, infers 133164 the temperature of the ultrasonic blade, and compares 133166 the inferred temperature of the ultrasonic blade to an ultrasonic blade instability trigger point threshold until the ultrasonic blade approaches instability. The process then proceeds along the YES branch and the processor or control circuit of the generator or instrument or both adjusts 133170 the power level applied to the ultrasonic transducer to modulate the temperature of the ultrasonic blade.
Ultrasonic sealing algorithms for ultrasonic blade temperature control can be employed to improve hemostasis utilizing a frequency-temperature feedback control algorithm described herein to exploit the frequency/temperature relationship of ultrasonic blades.
In one aspect, a frequency-temperature feedback control algorithm may be employed to alter the power level applied to the ultrasonic transducer based on measured resonant frequency (using spectroscopy) which relates to temperature, as described in various aspects of the present disclosure. In one aspect, the frequency-temperature feedback control algorithm may be activated by an energy button on the ultrasonic instrument.
It is known that optimal tissue effects may be obtained by increasing the power level driving the ultrasonic transducer (e.g., by increasing the driving voltage Vg(t) or current Ig(t), or both, applied to the ultrasonic transducer) early on in the sealing cycle to rapidly heat and desiccate the tissue, then lowering the power level driving the ultrasonic transducer (e.g., by lowering the driving voltage Vg(t) or current Ig(t), or both, applied to the ultrasonic transducer) to slowly allow the final seal to form. In one aspect, a frequency-temperature feedback control algorithm according to the present disclosure sets a limit on the temperature threshold that the tissue can reach as the tissue heats up during the higher power level stage and then reduces the power level to control the temperature of the ultrasonic blade based on the melting point of the clamp jaw pad (e.g., TEFLON) to complete the seal. The control algorithm can be implemented by activating an energy button on the instrument for a more responsive/adaptive sealing to reduce more the complexity of the hemostasis algorithm.
A first desired resonant frequency fx of the ultrasonic electromechanical system corresponds to a first desired temperature Z° of the ultrasonic blade. In one aspect, the first desired ultrasonic blade temperature Z° is an optimal temperature (e.g., 450° C.) for tissue coagulation. A second desired frequency fY of the ultrasonic electromechanical system corresponds to a second desired temperature ZZ° of the ultrasonic blade. In one aspect, the second desired ultrasonic blade temperature ZZ° is a temperature of 330° C., which is below the melting point of the clamp arm pad, which is approximately 380° C. for TEFLON.
The processor or control circuit of the generator or instrument or both compares 133186 the measured resonant frequency of the ultrasonic electromechanical system to the first desired frequency fx. In other words, the process determines whether the temperature of the ultrasonic blade is less than the temperature for optimal tissue coagulation. If the measured resonant frequency of the ultrasonic electromechanical system is less than the first desired frequency fx, the process continues along the NO branch and the processor or control circuit of the generator or instrument or both increases 133188 the power level applied to the ultrasonic transducer to increase the temperature of the ultrasonic blade until the measured resonant frequency of the ultrasonic electromechanical system exceeds the first desired frequency fx. In which case, the tissue coagulation process is completed and the process controls the temperature of the ultrasonic blade to the second desired temperature corresponding to the second desired frequency fy.
The process continues along the YES branch and the processor or control circuit of the generator or instrument or both decreases 133190 the power level applied to the ultrasonic transducer to decrease the temperature of the ultrasonic blade. The processor or control circuit of the generator or instrument or both measures 133192 the resonant frequency of the ultrasonic electromechanical system and compares 133194 the measured resonant frequency to the second desired frequency fY. If the measured resonant frequency is not less than the second desired frequency fY, the processor or control circuit of the generator or instrument or both decreases 133190 the ultrasonic power level until the measured resonant frequency is less than the second desired frequency fY. The frequency-temperature feedback control algorithm to maintain the measured resonant frequency of the ultrasonic electromechanical system below the second desired frequency fY, e.g., the temperature of the ultrasonic blade is less than the temperature of the melting point of the clamp arm pad then, the generator executes the increases the power level applied to the ultrasonic transducer to increase the temperature of the ultrasonic blade until the tissue transection process is complete 133196.
In various aspects, a surgical instrument (e.g., an ultrasonic surgical instrument) is configured to identify or parameterize the tissue grasped by the end effector and adjust various operational parameters of the surgical instrument accordingly. The identification or parameterization of the tissue can include the tissue type (e.g., the physiological tissue type), physical characteristics or properties of the tissue, the composition of the tissue, the location of the tissue within or relative to the end effector, and so on. In one example discussed in greater detail below, the ultrasonic surgical instrument is configured to tune the displacement amplitude of the distal tip of the ultrasonic blade according to the collagen/elastin ratio of the tissue detected in the jaws of the end effector. As previously discussed, an ultrasonic instrument comprises an ultrasonic transducer acoustically coupled to an ultrasonic blade via an ultrasonic waveguide. The displacement of the ultrasonic blade is a function of the electrical power applied to the ultrasonic transducer and, accordingly, the electrical power supplied to the ultrasonic transducer can be modulated according to the detected collagen/elastin ratio of the tissue. In another example discussed in greater detail below, the force exerted by the clamp arm on the tissue can be modulated according to the location of the tissue relative to the end effector. Various techniques for identifying or parameterizing the tissue are described herein and further details can be found in, for example, U.S. Provisional Patent Application No. 62/692,768, titled SMART ENERGY DEVICES, filed on Jun. 30, 2018, the disclosure of which is herein incorporated by reference in its entirety.
Referring back to
With reference now to
as described herein. Once the conditions at the ultrasonic end effector 1122 are determined using non-therapeutic ultrasonic energy levels, therapeutic ultrasonic energy may be applied based on the determined end effector 1122 conditions to optimize the tissue treatment, effective seal, transection, and duration, among other variables associated with a particular surgical procedure. Therapeutic energy is sufficient to coagulate and cut tissue.
In one aspect, the present disclosure provides a control process, such as an algorithm, to determine the thickness and type of tissue located within the jaws (i.e., between the clamp arm 1140 and the ultrasonic blade 1128) of an ultrasonic end effector 1122 as shown in
When applying power (voltage and current) to the ultrasonic transducer to activate the ultrasonic blade 1128 in the non-therapeutic range (for example, power that is not sufficient for cutting or coagulating tissue), the resulting measured transducer impedance (Ω) is a useful indicator of the position of tissue within the jaw of the end effector 1122, whether at the distal end 130420 or proximal end 130422 of the ultrasonic blade 1128 as shown in
In accordance with one aspect of the process 130100, a processor applies a control signal to close the clamp arm 1140 to capture the tissue between the clamp arm 1140 and the ultrasonic blade 1128. After the clamp arm 1140 closes onto the tissue, the processor waits for a predetermined delay period to allow the tissue to relax and give up some moisture content. After the delay period, the processor sets 130102 the power level applied to ultrasonic transducer to a first non-therapeutic power level. Optionally, one aspect of the process 130100 includes a feedback control can be used to verify that the first power is set below a therapeutic power level. In this aspect, the processor determines 130106 whether the first power level is less than a therapeutic power level. If the first power level is not less than a therapeutic power level, the process 130100 continues along the NO branch and the processor decreases 130108 the applied power and loops until the first power level is less than a therapeutic power level. The process 130100 then continues along the YES branch and the processor measures 130110 a first impedance Zg1(t) of the ultrasonic transducer corresponding to the first power level. The processor then sets 130112 the power level applied to ultrasonic transducer to a second non-therapeutic power level, where the second power is greater than the first power level and is below a therapeutic power level. Again, optionally, a feedback control can be used to verify that the second power level is not only greater than the first power level but also is below a therapeutic power level. In this aspect, the processor determines 130114 whether the second power level is less than a therapeutic power level. If the second power is greater than a therapeutic power level, the process 130100 continues along the NO branch and the processor decreases 130108 the second power level and loops until it is below a therapeutic power level threshold. The process 130100 then continues along the YES branch and the processor measures 130116 a second impedance Zg2(t) of the ultrasonic transducer corresponding to the second power level. The impedance of the ultrasonic transducer can be measured using a variety of techniques as discussed herein. The processor then calculates 130118 the difference in transducer impedance between the applied first and second power levels:
δ=Zg2(t)−Zg1(t).
The processor then provides 130120 an indication of the tissue position to the user. The processor can indicate the tissue position via an output device of a surgical instrument (e.g., visual feedback devices, such as the display depicted in
The processor compares the difference in transducer impedance to a first and second threshold where, as shown in
In various aspects, the reactions of the ultrasonic instrument may be based on whether tissue is present within the end effector, the type of tissue located in the end effector, or the compressibility or composition of the tissue located in the end effector. Accordingly, the generator or the ultrasonic surgical instrument may contain and/or execute instructions to perform algorithms to control the time between clamping the tissue in the jaws of the end effector and the activation of the ultrasonic transducer to treat the tissue. If tissue is not sensed, the ultrasonic generator activation buttons or pedals may be assigned different meanings to execute different functions. In one aspect, an advanced energy device may employ the detection of the presence of tissue within the jaws of the end effector as the queue for activating the ultrasonic transducer, thereby starting the tissue coagulation cycle. In another aspect, the compressive properties and situational awareness may enable automatic activation of the device to also adjust the parameters of the algorithm for the type of tissue sensed. For example, the advanced generator may ignore activations of buttons or foot pedals unless tissue is sensed in contact with the jaws of the end effector. This configuration would eliminate inadvertent activation queues that would allow the device to be operated in a simpler manner.
Accordingly, an advanced generator, such as advanced generators described in connection with
In one aspect, the present disclosure provides an algorithm executed by a processor or control circuit located either in the generator or handheld ultrasonic instrument to determine the presence of tissue and the type of tissue located within the jaws of the end effector. In one aspect, the control algorithm can be configured to determine that tissue is located within the end effector via techniques described herein for determining tissue location as described below under the heading DETERMINING TISSUE LOCATION VIA ELECTRODE CONTINUITY. For example, a control algorithm can be configured to determine whether tissue is located within the end effector according to whether there is any continuity between electrodes (as described below) and, accordingly, activate the surgical instrument (e.g., by causing the generator to which the surgical instrument is coupled to begin applying power to the surgical instrument) automatically upon detecting tissue or permit activation of the surgical instrument. When the surgical instrument and/or generator is being operated in switchless mode, the control algorithm can further be configured to activate the surgical instrument at a particular power level, which may or may not be different that a standard initial activation power level for the surgical instrument. In some aspects, a control algorithm can be configured to activate or permit activation of the surgical instrument according to the particular type or composition of the tissue, which can be detected via, e.g., techniques described below under the heading DETERMINING TISSUE COLLAGEN-TO-ELASTIN RATIO ACCORDING TO IR SURFACE REFLECTANCE AND EMISSIVITY. For example, the control algorithm can be configured to activate the surgical instrument when tissue having a high collagen composition has been grasped, but not necessarily activate the surgical instrument when tissue having a high elastin composition has been grasped. In some aspects, a control algorithm can be configured to activate or permit activation of the surgical instrument according to whether the grasped tissue is located at a particular position within the end effector or whether a particular amount of tissue has been grasped by the end effector via, e.g., techniques described below under the heading DETERMINING TISSUE LOCATION VIA ELECTRODE CONTINUITY. For example, the control algorithm can be configured to activate the surgical instrument when the grasped tissue covers a particular percentage of the end effector. As another example, the control algorithm can be configured to activate the surgical instrument when the grasped tissue is located at the distal end of the end effector.
In other aspects, a control algorithm can be configured to determine whether tissue has been grasped by the end effector, the tissue type or composition, and other characteristics of the end effector or the tissue via a situational awareness system, as described in U.S. Provisional Patent Application Ser. No. 62/659,900, titled METHOD OF HUB COMMUNICATION, filed Apr. 19, 2018, which is hereby incorporated by reference in its entirety, and under the heading SITUATIONAL AWARENESS. In these aspects, a surgical hub 106 (
With the ability to detect whether or not the instrument is contacting tissue, and what type of tissue when in contact, the ultrasonic instrument can be operated in a switchless mode of operation where operation is permitted based on the sensing ability of the ultrasonic instrument. In some aspects, a control algorithm can be configured to ignore actuations of activation buttons, foot pedals, and other input devices coupled to the generator and/or the ultrasonic surgical instrument unless tissue is sensed in contact with the jaws/end effector of the surgical instrument, thereby preventing unintended activations of the instrument. In some aspects, a control algorithm can be configured to assign different meanings to the inputs of activation buttons, foot pedals, and other input devices coupled to the generator and/or the ultrasonic surgical instrument according to whether tissue is sensed in contact with the jaws/end effector of the surgical instrument. For example, when tissue is present in the end effector, a control algorithm can be configured to activate the surgical instrument in response to an activation button being actuated; however, when tissue is not present within the end effector, the control algorithm can be configured to execute some different or secondary action when the activation button is actuated.
The ability to determine the lack of tissue present in the jaws of the end effector acts as a permissive to allow the instrument to change to switchless mode and then initiate an automatic coagulation cycle of operation when tissue is then detected, leading to greater uptime use of the instrument and allowing the user to proceed based on its predictive capability. The ability to further detect tissue type in addition to detecting the presence of tissue allows the algorithm to adjust and calculate the best coagulation opportunity.
In various aspects, an ultrasonic surgical instrument can include a processor or control circuit executing an adaptive ultrasonic blade control algorithm for detecting the composition of the tissue grasped by or at the end effector and controlling operational parameters of the ultrasonic transducer and/or ultrasonic blade accordingly. The tissue composition can include, for example, the ratio of collagen to elastin in the tissue, the stiffness of the tissue, or the thickness of the tissue. The operational parameters controlled or regulated by the adaptive ultrasonic blade control algorithm can include, for example, the amplitude of the ultrasonic blade, the temperature or heat flux of the ultrasonic blade, and so on. The adaptive ultrasonic blade control algorithm can be executed by a control circuit or processor located either in the generator or the surgical instrument.
In one example described in further detail below, the adaptive ultrasonic blade control algorithm can be configured to control the amplitude of the ultrasonic blade according to the collagen-to-elastin ratio of the tissue. The collagen-to-elastin ratio of the tissue can be determined via a variety of techniques, such as those described below. In another example described in further detail below, the adaptive ultrasonic blade control algorithm can be configured to control the ultrasonic transducer/ultrasonic blade to provide a longer warming time and a lower end temperature of the ultrasonic blade the lower the collagen content of the tissue is.
In various aspects, a control algorithm can be configured to determine the collagen-to-elastin ratio of a tissue (e.g., to tune the amplitude of the distal tip of an ultrasonic blade) by detecting the natural frequency of an ultrasonic blade and the shifts in the ultrasonic blade waveform. For example, the techniques described in connection with
The ratio of elastin to collagen may be determined by monitoring the shift in the natural frequency of the ultrasonic blade and comparing the natural frequency to a look-up table. The look-up table can be stored in memory (e.g., memory 3326 of
In various aspects, a control algorithm can be configured to determine the collagen-to-elastin ratio of a tissue (e.g., to tune the amplitude of the distal tip of an ultrasonic blade) by determining the IR reflectivity of the tissue. For example,
With reference to
The IR reflectivity detection sensor circuit 130409 shown in
A comparative method employs an energy dissection device, such as an ultrasonic blade 130404, for example, to determine the exact ratio (as detailed above) and then to predict the collagen ratio for all further actuation using that index as a baseline. In this manner, an endoscope may update the dissection device (e.g., ultrasonic blade 130404) based on collagen ratio. The dissection device can fine-tune the forecasting each time it is actuated to make an actual collagen denaturing firing. An alternative method may employ an absolute index with a look-up table that can differentiate between surface irregularities and sub-surface collagen concentration. Additional information about IR refractive index properties of tissue can be found in Visible To Near-Infrared Refractive Properties Of Freshly-Excised Human-Liver Tissues: Marking Hepatic Malignancies; Panagiotis Giannios, Konstantinos G. Toutouzas, Maria Matiatou, Konstantinos Stasinos, Manousos M. Konstadoulakis, George C. Zografos, and Konstantinos Moutzourisa; Sci. Rep. 2016; 6: 27910, which is hereby incorporated by reference herein.
In other aspects, the ultrasonic dissection device can be configured to change the ideal temperature of the ultrasonic blade control algorithm proportionately with the collagen ratio. For example, the ultrasonic blade temperature control algorithm can be modified based on the collagen ratio received from the control circuit 130420. As one specific example, the ultrasonic blade temperature control algorithm can be configured to lower the set of temperatures at which the ultrasonic blade 130404 is maintained and increase the hold time that the ultrasonic blade 130404 is contacted with the tissue 130410 for higher concentrations of collagen in the grasped tissue 130410. As another example, the wait time for the algorithm to cycle through a full activation could be modified based on the collagen ratio. Various temperature control algorithms for ultrasonic blades are described in connection with
Accordingly, with reference to
The ratio of elastin to collagen may be determined by monitoring the IR reflectance of the tissue and comparing the detected IR reflectance to a look-up table. The look-up table can be stored in memory (e.g., memory 3326 of
Different types of tissues are composed of varying amounts of structural proteins, such as collagen and elastin, which provide the different types of tissue with different properties. As heat is applied to the tissue (e.g., by an ultrasonic blade), the structural proteins denature, which affects the tissue integrity and other tissue properties. However, the structural proteins denature at different known temperatures. For example, collagen denatures prior to elastin. Accordingly, by detecting at what temperature the properties of the tissue change, one can infer the tissue composition (e.g., the ratio of collagen to elastin in the tissue). In various aspects, a control algorithm can be configured to determine the collagen-to-elastin ratio of a tissue by determining the collagen transformation point of the tissue. The control algorithm can, in turn, control various operational parameters of the surgical instrument, such as the amplitude of the ultrasonic blade, according to the determined tissue composition. In one aspect, the control algorithm can determine the collagen transformation point of the tissue by measuring the position of the clamp arm actuation member and the rate of change of its displacement while maintaining the load on the clamp arm constant. In another aspect, the control algorithm can determine the collagen transformation point of the tissue by measuring the temperature of the tissue/blade interface directly to identify the collagen/elastin percentage.
In one aspect, a control algorithm can be configured to detect the collagen transformation point of a grasped tissue and accordingly control the delivery of ultrasonic energy to the tissue by controlling the phase and/or amplitude of the ultrasonic transducer drive signal or rate of closure of the clamp arm. For example, in one aspect, a control algorithm can be configured to control the force applied to the tissue by the clamp arm according to the collagen transformation point. This may be achieved by measuring the position of the clamp arm actuation member and its rate of change while maintaining the load of the clamp arm constant within coaptation pressure within a set operational range (e.g., 130-180 psi) corresponding to the particular instrument type.
In one aspect, once the control algorithm determines that the transition temperature has been reached, the control algorithm can be configured to alter the operation of the ultrasonic instrument accordingly. For example, the control algorithm can switch the surgical instrument from load control (of the clamp arm 1140) to temperature control. In another aspect, the control algorithm can maintain the load control of the clamp arm after the collagen transformation temperature has been reached and monitor for when a clamp arm displacement rate of change threshold has been reached. The second clamp arm displacement rate of change threshold can correspond to, for example, the transition temperature of elastin. The locations of the collagen and/or elastin transitions temperatures in the plot 130258 of the clamp arm displacement over time can be referred to a “knee” in the plot 130258. Accordingly, in this aspect, the control algorithm can be configured to alter the operation of the ultrasonic instrument according to whether the second clamp rate displacement rate of change threshold (or elastin “knee”) has been reached and alter the operation of the ultrasonic instrument accordingly. For example, the control algorithm can switch the surgical instrument from load control (of the clamp arm 1140) to temperature control when the elastin knee in the plot 130258 is detected.
Collagen transformation should be constant for a given heat flux between 45° and 50° C. for collagen, where elastin has a different melt temperature. Further, the temperature should flatten as the collagen absorbs the heat. In some aspects, the control algorithm can be configured to sample the position of the clamp arm and/or clamp arm displacement member at a higher rate around particular temperatures or within temperature ranges (e.g., the ranges for expected temperature for collagen and/or elastin transformation) in order to precisely ascertain when the monitored events occur.
In the aspect depicted in
It will be appreciated that the collagen transformation should be constant for a given heat flux (45° C.-50° C.). It also will be appreciated that load control of the clamp arm 1140 can, in some cases, provide the best sealing for particular types of tissues (e.g., vessels). During the period of time where collagen transformation is occurring, the temperature of the tissue should flatten while the collagen absorbs the heat. The control circuit can be configured to modulate the rate at which data points are collected around a particular temperature or temperatures of interests (e.g., transformation temperatures). Further, the control circuit can tune the amplitude of the ultrasonic transducer drive signal to control the heat flux generated by the ultrasonic blade 1128 at different points in the surgical procedure. For example, the control circuit can decrease the ultrasonic transducer amplitude during the period of collagen transformation. As another example, the control circuit can increase the ultrasonic transducer amplitude to measure the rate at which the temperature increases when the elastin knee occurs. It will be appreciated that as the elastin knee is approached, the rate of temperature change will decrease.
In another aspect, a control algorithm can be configured to detect the collagen transformation temperature to identify the collagen/elastin percentage of the grasped tissue. As discussed above, the control algorithm can then control various operational parameters of the surgical instrument according to the identified composition of the grasped tissue.
The collagen transformation temperature can be used to directly identify the collagen/elastin percentage in the tissue and a control algorithm can be configured to adjust the operation of the ultrasonic device accordingly. As shown in
The ratio of elastin to collagen may be determined by monitoring the collagen transformation point of the tissue and comparing the detected collagen transformation point to a look-up table. The look-up table can be stored in memory (e.g., memory 3326 of
In various aspects, a control algorithm can be configured to determine the location of a tissue within or relative to an end effector and adjust the clamp arm force accordingly. In one aspect, tissue can be identified or parameterized by measuring the compression force load on the clamp arm and the position of the tissue within the jaw, e.g., where the tissue is located along the length of the ultrasonic blade. In one aspect, the time to initial measured load on the clamp arm is measured and then the compression rate on the tissue is measured to determine compressibility of the tissue versus the amount of tissue located across the length of the jaw. The rate of change of position of the clamp arm actuator is monitored while in load control as a way to determine tissue compressibility and therefore tissue type/disease state.
In the graphical representation 130500, the ultrasonic blade 130404 is represented such that the nodes and antinodes are aligned with their corresponding position along the horizontal axis 130504. The graphical representation 130500 includes a first plot 130506 and a second plot 130508. As represented by either of the plots 130506, 130508, the compression force applied to the ultrasonic blade 130404 drops exponentially from a proximal end of the ultrasonic blade 130404 to a distal end of the ultrasonic blade 130404. Thus, tissue 130410 located at the distal end of the ultrasonic blade 130404 is subjected to much lower compression force as compared to tissue 130410 located closer to the proximal end of the ultrasonic blade 130404. The first plot 130506 can represent a default closure of the clamp arm 1140 where the resulting force applied to the distal tissue 130410 is F1. Generally, the amount of force applied by the clamp arm 1140 to tissue 130410 cannot be broadly increased without consideration because then too much force could be applied to tissue 130410 located proximally along the ultrasonic blade 130404. However, by monitoring the location of the tissue 130410 along the ultrasonic blade 130404 (e.g., as discussed above under the heading DETERMINING TISSUE LOCATION VIA IMPEDANCE CHANGE and below under the heading DETERMINING TISSUE LOCATION VIA ELECTRODE CONTINUITY), a control algorithm can amplify the force applied to the tissue 130410 by the clamp arm 1140 in situations where tissue 130410 is located only at the distal end of the ultrasonic blade 130404, as with the situation shown in
In various aspects, a control algorithm can be configured to determine the location of a tissue within or relative to an end effector according to electrical continuity across an array of bipolar (i.e., positive and negative) electrodes positioned along a jaw or jaws of the end effector. The location of the tissue detectable by the bipolar electrode array can correspond to the specific position of the tissue relative to the jaw(s) and/or the percentage of the jaw(s) covered by tissue. In one aspect, the positive and negative electrodes are separated by a physical gap such that electrical continuity is established between the electrodes when tissue bridges the positive and negative electrodes. The positive and negative electrodes are configured in a matrix or array such that a processor or control circuit can be configured to detect where tissue is located between the positive and negative electrodes by monitoring or scanning the electrode array. In one aspect, the bipolar electrode array can be positioned along one jaw of an end effector. Accordingly, a control circuit or processor coupled to the bipolar electrode array can be configured to detect electrical continuity between adjacent electrodes to detect the presence of tissue thereagainst. In another aspect, the bipolar electrode array can be positioned along opposing jaws of an end effector. Accordingly, a control circuit or processor coupled to the bipolar electrode array can be configured to detect electrical continuity between the opposing jaws to detect the presence of tissue therebetween.
Determining what surface area of the jaw(s) is covered with tissue allows a control algorithm to determine the appropriate coaptation pressure for the amount of tissue grasped by the end effector and then calculate the corresponding clamp arm load. The clamp arm load can be expressed in terms of applied pressure (e.g., 130-180 psi) or applied force (e.g., 3.5-5 lbs. or nominally 4.5 lbs.). In some aspects, the bipolar electrode array can be delivered power from a monopolar or bipolar RF electrosurgical generator to the positive and negative electrodes. The generator power output may be a variety of constant, variable, or minimum values (e.g., 45 W, 35 W, or 5 W), a function of various variables associated with the surgical instrument and/or the generator (e.g., amplitude of the ultrasonic blade or clamp arm force), or dictated by an algorithm for controlling the generator according to its power curve (e.g., during ramp up of the generator).
In one aspect, the electrode array 130431 can include electrodes 130429 that are separated by a physical gap and alternate in polarity or are coupled to opposing terminals (i.e., a supply terminal and a return terminal) of an energy source. For example, in the depicted aspect, the evenly numbered electrodes 130429 can be a first polarity (e.g., positive polarity or coupled to a supply terminal of a power source) and the odd numbered electrodes 130429 can be a second polarity (e.g., negative or coupled to a return terminal of a power source). Accordingly, when tissue 130410 contacts adjacent electrodes 130429, the tissue 130410 physically and electrically bridges the bipolar electrodes 130429 and allows current to flow therebetween. The flow of current between bipolar electrodes 130429 can be detected by a control algorithm executed by a control circuit or processor coupled to the electrode array 130431, thereby allowing the control circuit or processor to detect the presence of tissue 130410.
The detection of tissue by the electrode array 130431 can be represented graphically by an activation matrix. For example,
In one aspect, the opposing electrodes 130429 of the electrode arrays 130431, 130433 are separated by a physical gap, and each electrode array 130431, 130433 is of an opposing polarity or is coupled to an opposing terminal (i.e., a supply terminal and a return terminal) of an energy source. For example, in the depicted aspect, the first electrode array 130431 can be a first polarity (e.g., positive polarity or coupled to a supply terminal of a power source) and the second electrode array 130433 can be a second polarity (e.g., negative or coupled to a return terminal of a power source). Accordingly, when tissue 130410 contacts an electrode 130429 of each of the opposing electrode arrays 130431, 130433, the tissue 130410 physically and electrically bridges the bipolar electrodes 130429 and allows current to flow therebetween. The flow of current between bipolar electrodes 130429 can be detected by a control algorithm executed by a control circuit or processor coupled to the electrode arrays 130431, 130433, thereby allowing the control circuit or processor to detect the presence of tissue 130410.
As discussed above, an activation matrix can graphically represent the presence of tissue. For example,
In another aspect, the end effector can be configured to transmit a plurality of signals or pings at varying frequencies and the electrode array can be coupled to a circuit, including corresponding band-pass filters that can each detect a particular frequency signal or signals through a frequency transform. Various portions of the electrode array circuit can include band-pass filters tuned to different frequencies. Therefore, the location of the tissue grasped by the end effector corresponds to the particular detected signals. The signals can be transmitted, for example, at a nontherapeutic frequency (e.g., at frequencies above the therapeutic frequency range for RF electrosurgical instruments). The electrode array circuit can include, for example, a flex circuit.
In one aspect, an adaptive ultrasonic blade control algorithm may be employed to adjust various operational parameters of the ultrasonic system based on the temperature of the ultrasonic blade. The operational parameters controlled or regulated by the adaptive ultrasonic blade control algorithm can include, for example, the amplitude of the ultrasonic blade, the control signal driving the ultrasonic transducer, the pressure applied by the clamp arm, and so on. The adaptive ultrasonic blade control algorithm can be executed by a control circuit or processor located either in the generator or the surgical instrument.
In one example described in further detail below, the adaptive ultrasonic blade control algorithm dynamically monitors the temperature of the ultrasonic blade and adjusts the amplitude of the ultrasonic blade and/or the signal provided to the ultrasonic transducer accordingly. In another example described in further detail below, the adaptive ultrasonic blade control algorithm dynamically monitors the temperature of the ultrasonic blade and adjusts the clamp arm pressure accordingly. The adaptive ultrasonic blade control algorithm can measure the temperature of the ultrasonic blade via various techniques, such as by analyzing the frequency spectrum of the ultrasonic transducer as discussed above under the heading TEMPERATURE INFERENCE. Other techniques for determining the temperature of the ultrasonic blade employ non-contact imaging. These and other techniques are described in detail herein and additional detail may be found in U.S. Provisional Patent Application No. 62/692,768, titled SMART ENERGY DEVICES.
In one aspect, the adaptive ultrasonic blade control algorithm can be configured to adjust operational parameters of the ultrasonic system based on the temperature of the ultrasonic blade. As discussed above under the heading TEMPERATURE INFERENCE, the natural frequency of the ultrasonic blade/transducer moves with temperature, and thus, the temperature of the ultrasonic blade can be inferred from the phase angle between the voltage and current signals applied to drive the ultrasonic transducer. Further, the ultrasonic blade temperature corresponds to the tissue temperature. In some aspects, the adaptive ultrasonic blade control algorithm can be configured to detect the ultrasonic blade temperature and modulate the surgical instrument's operational parameters according to the temperature. The operational parameters can include, for example, the frequency of the ultrasonic transducer drive signal, the amplitude of the ultrasonic blade (which can, for example, correspond to the magnitude or amplitude of the electrical current supplied to the ultrasonic transducer), the pressure applied by the clamp arm, and so on. The adaptive ultrasonic blade control algorithm can be executed by a control circuit or processor located either in the generator or the surgical instrument.
Accordingly, in one aspect, the adaptive ultrasonic blade control algorithm detects the resonant frequency of the ultrasonic blade, as described previously under the heading TEMPERATURE INFERENCE, and then monitors the resonant frequency over time in order to detect a modal shift in the resonant frequency waveform. A shift in the resonant waveform can be correlated to the occurrence of a system change, such as an increase in the temperature of the ultrasonic blade. In some aspects, an adaptive ultrasonic blade control algorithm can be configured to adjust the amplitude of the ultrasonic drive signal, and therefore the amplitude of the ultrasonic blade displacement, in order to measure the temperature of the tissue. In other aspects, an adaptive ultrasonic blade control algorithm can be configured to control the amplitude of the ultrasonic drive signal, and therefore the amplitude of the ultrasonic blade displacement, according to the temperature of the ultrasonic blade and/or tissue in order to hold the temperature of the ultrasonic blade and/or tissue to a predefined temperature or within predefined thresholds (e.g., to allow the ultrasonic blade to cool if its temperature is becoming too high). In still other aspects, an adaptive ultrasonic blade control algorithm can be configured to modulate the RF power and waveform of an electrosurgical instrument in order to, for example, minimize temperature overshoot or change the ultrasonic blade heat flux, according to the tissue impedance, tissue temperature, and/or ultrasonic blade temperature. Further details regarding these and other functions have been described in reference to
Correspondingly, in some aspects, a control circuit coupled to the ultrasonic system can be configured to control the drive signal applied to the ultrasonic system by the generator according to the inferred temperature of the ultrasonic system in order to maintain the ultrasonic system in phase. Maintaining the ultrasonic system in phase can be utilized to, for example, control the temperature of the ultrasonic system. As discussed above, the resonant frequency at which the voltage and current signals are in phase shifts from fe (e.g., 55.5 kHz) at normal temperature to f′e as the temperature of the ultrasonic blade and/or ultrasonic transducer increases. Therefore, as the temperature of the ultrasonic system increases, a control circuit can control the generator to shift the frequency at which the ultrasonic system is driven from fe to f′e to maintain the ultrasonic system in phase with the generator drive signal. For additional description of adaptive ultrasonic blade control algorithms, please refer to the description associated with
The control algorithm can be configured to control the ultrasonic system (e.g., ultrasonic transducer and/or ultrasonic blade) when the temperature of the ultrasonic system approaches a temperature threshold T1. In one aspect, the control algorithm can be configured to determine that the temperature threshold T1 is being approached or has been reached according to whether the resonant frequency of the ultrasonic system has dropped by a threshold ΔfR. As indicated by the first graph 130800, the change in frequency threshold ΔfR corresponding to the threshold temperature T1 can, in turn, be a function of the drive frequency fD of the ultrasonic system (as represented by the plot 130806). As indicated by the second graph 130810 and the fourth graph 130830, as the temperature of the tissue and/or ultrasonic blade increases (represented by the temperature plot 130836), the resonant frequency correspondingly decreases (represented by the frequency plot 130816). As the temperature plot 130836 approaches a temperature threshold T1 (e.g., 130° C.) at time t1, the resonant frequency has dropped from f1 to f2, causing the resonant frequency to reach the control algorithm's change in frequency threshold ΔfR and thereby causing the control algorithm act to stabilize the ultrasonic system temperature. By monitoring the change in resonant frequency of the ultrasonic system, the adaptive ultrasonic blade control algorithm can thus monitor the temperature of the ultrasonic system. Further, the adaptive ultrasonic blade control algorithm can be configured to adjust (e.g., decrease) the electrical current applied to the ultrasonic transducer or otherwise adjust the amplitude of the ultrasonic blade (represented by the current plot 130826) in order to stabilize the tissue and/or ultrasonic blade temperature and/or the resonant frequency when the temperature meets or exceeds the threshold T1.
In another aspect, the adaptive ultrasonic blade control algorithm can be configured to adjust (e.g., decrease) the pressure applied by the clamp arm to the tissue when the temperature meets or exceeds the threshold T1. In various other aspects, the adaptive ultrasonic blade control algorithm can be configured to adjust a variety of other operational parameters associated with the ultrasonic system according to the temperature. In another aspect, the adaptive ultrasonic blade control algorithm can be configured to monitor multiple temperature thresholds. For example, a second temperature threshold T2 can represent, for example, a melt or failure temperature of the clamp arm. Accordingly, the adaptive ultrasonic blade control algorithm can be configured to take the same or different actions according to the particular temperature threshold that has been met or exceeded.
In various aspects, non-contact imaging may be employed to determine the temperature of the ultrasonic blade in addition to or in lieu of the aforementioned techniques. For example, short-wave thermography may be employed to measure blade temperature by imaging the blade from the stationary surrounding ground via a CMOS imaging sensor. Thermographic non-contact monitoring of the ultrasonic waveguide or ultrasonic blade temperature may be employed to control tissue temperature. In other aspects, non-contact imaging may be employed to determine surface conditions and finish of the ultrasonic blade to improve the temperature of tissue and/or ultrasonic blade through near IR detection techniques.
A challenge with ultrasonic energy delivery is that ultrasonic acoustics applied on the wrong materials or the wrong tissue can result in device failure, for example, clamp arm pad burn through or ultrasonic blade breakage. It is also desirable to detect what is located in the jaws of an end effector of an ultrasonic device and the state of the jaws without adding additional sensors in the jaws. Locating sensors in the jaws of an ultrasonic end effector poses reliability, cost, and complexity challenges.
Ultrasonic spectroscopy smart blade algorithm techniques may be employed for estimating the state of the jaw (clamp arm pad burn through, staples, broken blade, bone in jaw, tissue in jaw, back-cutting with jaw closed, etc.) based on the impedance
of an ultrasonic transducer configured to drive an ultrasonic transducer blade, in accordance with at least one aspect of the present disclosure. The impedance Zg(t), magnitude |Z|, and phase φ are plotted as a function of frequency f.
Dynamic mechanical analysis (DMA), also known as dynamic mechanical spectroscopy or simply mechanical spectroscopy, is a technique used to study and characterize materials. A sinusoidal stress is applied to a material, and the strain in the material is measured, allowing the determination of the complex modulus of the material. The spectroscopy as applied to ultrasonic devices includes exciting the tip of the ultrasonic blade with a sweep of frequencies (compound signals or traditional frequency sweeps) and measuring the resulting complex impedance at each frequency. The complex impedance measurements of the ultrasonic transducer across a range of frequencies are used in a classifier or model to infer the characteristics of the ultrasonic end effector. In one aspect, the present disclosure provides a technique for determining the state of an ultrasonic end effector (clamp arm, jaw) to drive automation in the ultrasonic device (such as disabling power to protect the device, executing adaptive algorithms, retrieving information, identifying tissue, etc.).
Spectral analysis of different jaw bites and device states produces different complex impedance characteristic patterns (fingerprints) across a range of frequencies for different conditions and states. Each state or condition has a different characteristic pattern in 3D space when plotted. These characteristic patterns can be used to estimate the condition and state of the end effector.
The spectra 132030 can be evaluated by applying a low-power electrical signal across the ultrasonic transducer to produce a non-therapeutic excitation of the ultrasonic blade. The low-power electrical signal can be applied in the form of a sweep or a compound Fourier series to measure the impedance
across the ultrasonic transducer at a range of frequencies in series (sweep) or in parallel (compound signal) using an FFT.
For each characteristic pattern, a parametric line can be fit to the data used for training using a polynomial, a Fourier series, or any other form of parametric equation as may be dictated by convenience. A new data point is then received and is classified by using the Euclidean perpendicular distance from the new data point to the trajectory that has been fitted to the characteristic pattern training data. The perpendicular distance of the new data point to each of the trajectories (each trajectory representing a different state or condition) is used to assign the point to a state or condition.
The probability distribution of distance of each point in the training data to the fitted curve can be used to estimate the probability of a correctly classified new data point. This essentially constructs a two-dimensional probability distribution in a plane perpendicular to the fitted trajectory at each new data point of the fitted trajectory. The new data point can then be included in the training set based on its probability of correct classification to make an adaptive, learning classifier that readily detects high-frequency changes in states but adapts to slow occurring deviations in system performance, such as a device getting dirty or the pad wearing out.
The parametric Fourier series fit to the 3D training data set (S) is given by:
For a new point {right arrow over (z)}, the perpendicular distance from {right arrow over (p)} to {right arrow over (z)} is found by:
D=∥{right arrow over (p)}−{right arrow over (z)}∥
When:
Then:
D=D⊥
A probability distribution of D can be used to estimate the probability of a data point {right arrow over (z)} belonging to the group S.
Based on the classification of data measured before, during, or after activation of the ultrasonic transducer/ultrasonic blade, a variety of automated tasks and safety measures can be implemented. Similarly, the state of the tissue located in the end effector and temperature of the ultrasonic blade also can be inferred to some degree, and used to better inform the user of the state of the ultrasonic device or protect critical structures, etc. Temperature control of an ultrasonic blade is described in commonly owned U.S. Provisional Patent Application No. 62/640,417, filed Mar. 8, 2018, titled TEMPERATURE CONTROL IN ULTRASONIC DEVICE AND CONTROL SYSTEM THEREFOR, which is incorporated herein by reference in its entirety.
Similarly, power delivery can be reduced when there is a high probability that the ultrasonic blade is contacting the clamp arm pad (e.g., without tissue in between) or if there is a probability that the ultrasonic blade has broken or that the ultrasonic blade is touching metal (e.g., a staple). Furthermore, back-cutting can be disallowed if the jaw is closed and no tissue is detected between the ultrasonic blade and the clamp arm pad.
This system can be used in conjunction with other information provided by sensors, the user, metrics on the patient, environmental factors, etc., by combing the data from this process with the aforementioned data using probability functions and a Kalman filter. The Kalman filter determines the maximum likelihood of a state or condition occurring given a plethora of uncertain measurements of varying confidence. Since this method allows for an assignment of probability to a newly classified data point, this algorithm's information can be implemented with other measures or estimates in a Kalman filter.
Once the reference complex impedance characteristic patterns or a training data sets (S) are generated, the ultrasonic instrument measures new data points, classifies the new points, and determines whether the new data points should be added to the reference complex impedance characteristic patterns or a training data sets (S).
Turning now to the logic flow diagram of
The processor or control circuit receives 132048 a complex impedance measurement data point and compares 132050 the complex impedance measurement data point to a data point in a reference complex impedance characteristic pattern. The processor or control circuit classifies 132052 the complex impedance measurement data point based on a result of the comparison analysis and assigns 132054 a state or condition of the end effector based on the result of the comparison analysis.
In one aspect, the processor or control circuit receives the reference complex impedance characteristic pattern from a database or memory coupled to the processor. In one aspect, the processor or control circuit generates the reference complex impedance characteristic pattern as follows. A drive circuit coupled to the processor or control circuit applies a nontherapeutic drive signal to the ultrasonic transducer starting at an initial frequency, ending at a final frequency, and at a plurality of frequencies therebetween. The processor or control circuit measures the impedance of the ultrasonic transducer at each frequency and stores a data point corresponding to each impedance measurement. The processor or control circuit curve fits a plurality of data points to generate a three-dimensional curve of representative of the reference complex impedance characteristic pattern, wherein the magnitude |Z| and phase φ are plotted as a function of frequency f. The curve fitting includes a polynomial curve fit, a Fourier series, and/or a parametric equation.
In one aspect, the processor or control circuit receives a new impedance measurement data point and classifies the new impedance measurement data point using a Euclidean perpendicular distance from the new impedance measurement data point to a trajectory that has been fitted to the reference complex impedance characteristic pattern. The processor or control circuit estimates a probability that the new impedance measurement data point is correctly classified. The processor or control circuit adds the new impedance measurement data point to the reference complex impedance characteristic pattern based on the probability of the estimated correct classification of the new impedance measurement data point. In one aspect, the processor or control circuit classifies data based on a training data set (S), where the training data set (S) comprises a plurality of complex impedance measurement data, and curve fits the training data set (S) using a parametric Fourier series, wherein S is defined herein and wherein the probability distribution is used to estimate the probability of the new impedance measurement data point belonging to the group S.
Additional details regarding determining or estimating a state of the jaws or the surgical instrument as a whole can be found in U.S. Provisional Patent Application No. 62/692,768, titled SMART ENERGY DEVICES.
Referring now to
The situationally aware surgical hub 106, 206 receives data from the data sources throughout the course of the surgical procedure, including data generated each time medical personnel utilize a modular device that is paired with the surgical hub 106, 206. The surgical hub 106, 206 can receive this data from the paired modular devices and other data sources and continually derive inferences (i.e., contextual information) about the ongoing procedure as new data is received, such as which step of the procedure is being performed at any given time. The situational awareness system of the surgical hub 106, 206 is able to, for example, record data pertaining to the procedure for generating reports, verify the steps being taken by the medical personnel, provide data or prompts (e.g., via a display screen) that may be pertinent for the particular procedural step, adjust modular devices based on the context (e.g., activate monitors, adjust the field of view (FOV) of the medical imaging device, or change the energy level of an ultrasonic surgical instrument or RF electrosurgical instrument), and take any other such action described above.
As the first step 5202 in this illustrative procedure, the hospital staff members retrieve the patient's EMR from the hospital's EMR database. Based on select patient data in the EMR, the surgical hub 106, 206 determines that the procedure to be performed is a thoracic procedure.
Second step 5204, the staff members scan the incoming medical supplies for the procedure. The surgical hub 106, 206 cross-references the scanned supplies with a list of supplies that are utilized in various types of procedures and confirms that the mix of supplies corresponds to a thoracic procedure. Further, the surgical hub 106, 206 is also able to determine that the procedure is not a wedge procedure (because the incoming supplies either lack certain supplies that are necessary for a thoracic wedge procedure or do not otherwise correspond to a thoracic wedge procedure).
Third step 5206, the medical personnel scan the patient band via a scanner that is communicably connected to the surgical hub 106, 206. The surgical hub 106, 206 can then confirm the patient's identity based on the scanned data.
Fourth step 5208, the medical staff turns on the auxiliary equipment. The auxiliary equipment being utilized can vary according to the type of surgical procedure and the techniques to be used by the surgeon, but in this illustrative case they include a smoke evacuator, insufflator, and medical imaging device. When activated, the auxiliary equipment that are modular devices can automatically pair with the surgical hub 106, 206 that is located within a particular vicinity of the modular devices as part of their initialization process. The surgical hub 106, 206 can then derive contextual information about the surgical procedure by detecting the types of modular devices that pair with it during this pre-operative or initialization phase. In this particular example, the surgical hub 106, 206 determines that the surgical procedure is a VATS procedure based on this particular combination of paired modular devices. Based on the combination of the data from the patient's EMR, the list of medical supplies to be used in the procedure, and the type of modular devices that connect to the hub, the surgical hub 106, 206 can generally infer the specific procedure that the surgical team will be performing. Once the surgical hub 106, 206 knows what specific procedure is being performed, the surgical hub 106, 206 can then retrieve the steps of that procedure from a memory or from the cloud and then cross-reference the data it subsequently receives from the connected data sources (e.g., modular devices and patient monitoring devices) to infer what step of the surgical procedure the surgical team is performing.
Fifth step 5210, the staff members attach the EKG electrodes and other patient monitoring devices to the patient. The EKG electrodes and other patient monitoring devices are able to pair with the surgical hub 106, 206. As the surgical hub 106, 206 begins receiving data from the patient monitoring devices, the surgical hub 106, 206 thus confirms that the patient is in the operating theater.
Sixth step 5212, the medical personnel induce anesthesia in the patient. The surgical hub 106, 206 can infer that the patient is under anesthesia based on data from the modular devices and/or patient monitoring devices, including EKG data, blood pressure data, ventilator data, or combinations thereof, for example. Upon completion of the sixth step 5212, the pre-operative portion of the lung segmentectomy procedure is completed and the operative portion begins.
Seventh step 5214, the patient's lung that is being operated on is collapsed (while ventilation is switched to the contralateral lung). The surgical hub 106, 206 can infer from the ventilator data that the patient's lung has been collapsed, for example. The surgical hub 106, 206 can infer that the operative portion of the procedure has commenced as it can compare the detection of the patient's lung collapsing to the expected steps of the procedure (which can be accessed or retrieved previously) and thereby determine that collapsing the lung is the first operative step in this particular procedure.
Eighth step 5216, the medical imaging device (e.g., a scope) is inserted and video from the medical imaging device is initiated. The surgical hub 106, 206 receives the medical imaging device data (i.e., video or image data) through its connection to the medical imaging device. Upon receipt of the medical imaging device data, the surgical hub 106, 206 can determine that the laparoscopic portion of the surgical procedure has commenced. Further, the surgical hub 106, 206 can determine that the particular procedure being performed is a segmentectomy, as opposed to a lobectomy (note that a wedge procedure has already been discounted by the surgical hub 106, 206 based on data received at the second step 5204 of the procedure). The data from the medical imaging device 124 (
Ninth step 5218, the surgical team begins the dissection step of the procedure. The surgical hub 106, 206 can infer that the surgeon is in the process of dissecting to mobilize the patient's lung because it receives data from the RF or ultrasonic generator indicating that an energy instrument is being fired. The surgical hub 106, 206 can cross-reference the received data with the retrieved steps of the surgical procedure to determine that an energy instrument being fired at this point in the process (i.e., after the completion of the previously discussed steps of the procedure) corresponds to the dissection step. In certain instances, the energy instrument can be an energy tool mounted to a robotic arm of a robotic surgical system.
Tenth step 5220, the surgical team proceeds to the ligation step of the procedure. The surgical hub 106, 206 can infer that the surgeon is ligating arteries and veins because it receives data from the surgical stapling and cutting instrument indicating that the instrument is being fired. Similarly to the prior step, the surgical hub 106, 206 can derive this inference by cross-referencing the receipt of data from the surgical stapling and cutting instrument with the retrieved steps in the process. In certain instances, the surgical instrument can be a surgical tool mounted to a robotic arm of a robotic surgical system.
Eleventh step 5222, the segmentectomy portion of the procedure is performed. The surgical hub 106, 206 can infer that the surgeon is transecting the parenchyma based on data from the surgical stapling and cutting instrument, including data from its cartridge. The cartridge data can correspond to the size or type of staple being fired by the instrument, for example. As different types of staples are utilized for different types of tissues, the cartridge data can thus indicate the type of tissue being stapled and/or transected. In this case, the type of staple being fired is utilized for parenchyma (or other similar tissue types), which allows the surgical hub 106, 206 to infer that the segmentectomy portion of the procedure is being performed.
Twelfth step 5224, the node dissection step is then performed. The surgical hub 106, 206 can infer that the surgical team is dissecting the node and performing a leak test based on data received from the generator indicating that an RF or ultrasonic instrument is being fired. For this particular procedure, an RF or ultrasonic instrument being utilized after parenchyma was transected corresponds to the node dissection step, which allows the surgical hub 106, 206 to make this inference. It should be noted that surgeons regularly switch back and forth between surgical stapling/cutting instruments and surgical energy (i.e., RF or ultrasonic) instruments depending upon the particular step in the procedure because different instruments are better adapted for particular tasks. Therefore, the particular sequence in which the stapling/cutting instruments and surgical energy instruments are used can indicate what step of the procedure the surgeon is performing. Moreover, in certain instances, robotic tools can be utilized for one or more steps in a surgical procedure and/or handheld surgical instruments can be utilized for one or more steps in the surgical procedure. The surgeon(s) can alternate between robotic tools and handheld surgical instruments and/or can use the devices concurrently, for example. Upon completion of the twelfth step 5224, the incisions are closed up and the post-operative portion of the procedure begins.
Thirteenth step 5226, the patient's anesthesia is reversed. The surgical hub 106, 206 can infer that the patient is emerging from the anesthesia based on the ventilator data (i.e., the patient's breathing rate begins increasing), for example.
Lastly, the fourteenth step 5228 is that the medical personnel remove the various patient monitoring devices from the patient. The surgical hub 106, 206 can thus infer that the patient is being transferred to a recovery room when the hub loses EKG, BP, and other data from the patient monitoring devices. As can be seen from the description of this illustrative procedure, the surgical hub 106, 206 can determine or infer when each step of a given surgical procedure is taking place according to data received from the various data sources that are communicably coupled to the surgical hub 106, 206.
Situational awareness is further described in U.S. Provisional Patent Application Ser. No. 62/659,900, titled METHOD OF HUB COMMUNICATION, filed Apr. 19, 2018, which is herein incorporated by reference in its entirety. In certain instances, operation of a robotic surgical system, including the various robotic surgical systems disclosed herein, for example, can be controlled by the hub 106, 206 based on its situational awareness and/or feedback from the components thereof and/or based on information from the cloud 102.
While several forms have been illustrated and described, it is not the intention of the applicant to restrict or limit the scope of the appended claims to such detail. Numerous modifications, variations, changes, substitutions, combinations, and equivalents to those forms may be implemented and will occur to those skilled in the art without departing from the scope of the present disclosure. Moreover, the structure of each element associated with the described forms can be alternatively described as a means for providing the function performed by the element. 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, combinations, and variations as falling within the scope of the disclosed forms. The appended claims are intended to cover all such modifications, variations, changes, substitutions, modifications, and equivalents.
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, and/or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. 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 one or more program products 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.
Instructions used to program logic to perform various disclosed aspects can be stored within a memory in the system, such as dynamic random access memory (DRAM), cache, flash memory, or other storage. Furthermore, the instructions can be distributed via a network or by way of other computer readable media. Thus a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), but is not limited to, floppy diskettes, optical disks, compact disc, read-only memory (CD-ROMs), and magneto-optical disks, read-only memory (ROMs), random access memory (RAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic or optical cards, flash memory, or a tangible, machine-readable storage used in the transmission of information over the Internet via electrical, optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.). Accordingly, the non-transitory computer-readable medium includes any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).
As used in any aspect herein, the term “control circuit” may refer to, for example, hardwired circuitry, programmable circuitry (e.g., a computer processor comprising one or more individual instruction processing cores, processing unit, processor, microcontroller, microcontroller unit, controller, digital signal processor (DSP), programmable logic device (PLD), programmable logic array (PLA), or field programmable gate array (FPGA)), state machine circuitry, firmware that stores instructions executed by programmable circuitry, and any combination thereof. The control circuit may, collectively or individually, be embodied as circuitry that forms part of a larger system, for example, an integrated circuit (IC), an application-specific integrated circuit (ASIC), a system on-chip (SoC), desktop computers, laptop computers, tablet computers, servers, smart phones, etc. Accordingly, as used herein “control circuit” 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.
As used in any aspect herein, the term “logic” may refer to an app, software, firmware and/or circuitry configured to perform any of the aforementioned operations. Software may be embodied as a software package, code, instructions, instruction sets and/or data recorded on non-transitory computer readable storage medium. Firmware may be embodied as code, instructions or instruction sets and/or data that are hard-coded (e.g., nonvolatile) in memory devices.
As used in any aspect herein, the terms “component,” “system,” “module” and the like can refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution.
As used in any aspect herein, an “algorithm” refers to a self-consistent sequence of steps leading to a desired result, where a “step” refers to a manipulation of physical quantities and/or logic states 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 and/or states.
A network may include a packet switched network. The communication devices may be capable of communicating with each other using a selected packet switched network communications protocol. One example communications protocol may include an Ethernet communications protocol which may be capable permitting communication using a Transmission Control Protocol/Internet Protocol (TCP/IP). The Ethernet protocol may comply or be compatible with the Ethernet standard published by the Institute of Electrical and Electronics Engineers (IEEE) titled “IEEE 802.3 Standard”, published in December, 2008 and/or later versions of this standard. Alternatively or additionally, the communication devices may be capable of communicating with each other using an X.25 communications protocol. The X.25 communications protocol may comply or be compatible with a standard promulgated by the International Telecommunication Union-Telecommunication Standardization Sector (ITU-T). Alternatively or additionally, the communication devices may be capable of communicating with each other using a frame relay communications protocol. The frame relay communications protocol may comply or be compatible with a standard promulgated by Consultative Committee for International Telegraph and Telephone (CCITT) and/or the American National Standards Institute (ANSI). Alternatively or additionally, the transceivers may be capable of communicating with each other using an Asynchronous Transfer Mode (ATM) communications protocol. The ATM communications protocol may comply or be compatible with an ATM standard published by the ATM Forum titled “ATM-MPLS Network Interworking 2.0” published August 2001, and/or later versions of this standard. Of course, different and/or after-developed connection-oriented network communication protocols are equally contemplated herein.
Unless specifically stated otherwise as apparent from the foregoing disclosure, it is appreciated that, throughout the foregoing disclosure, discussions using terms such as “processing,” “computing,” “calculating,” “determining,” “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.
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.
The terms “proximal” and “distal” are used herein with reference to a clinician manipulating the handle portion of the surgical instrument. The term “proximal” refers to the portion closest to the clinician and the term “distal” refers to the portion located away from the clinician. It will be further appreciated that, for convenience and clarity, spatial terms such as “vertical”, “horizontal”, “up”, and “down” may be used herein with respect to the drawings. However, surgical instruments are used in many orientations and positions, and these terms are not intended to be limiting and/or absolute.
Those skilled in the art will recognize 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.”
With 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 flow diagrams 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.
It is worthy to note that any reference to “one aspect,” “an aspect,” “an exemplification,” “one exemplification,” and the like 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 an exemplification,” and “in one exemplification” 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.
Any patent application, patent, non-patent publication, or other disclosure material referred to in this specification and/or listed in any Application Data Sheet is incorporated by reference herein, to the extent that the incorporated materials is 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.
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.
Various aspects of the subject matter described herein are set out in the following numbered examples:
Example 1. An ultrasonic surgical instrument comprising: an end effector comprising an ultrasonic blade, an ultrasonic transducer acoustically coupled to the ultrasonic blade, and a control circuit coupled to the ultrasonic transducer. The ultrasonic transducer is configured to ultrasonically oscillate the ultrasonic blade in response to a drive signal. The control circuit is configured to: measure a complex impedance of the ultrasonic transducer, compare the complex impedance to a plurality of reference complex impedance patterns, each of the plurality of reference complex impedance patterns corresponding to a state of the end effector, and determine the state of the end effector according to which of the plurality of reference complex impedance patterns the complex impedance corresponds.
Example 2. The ultrasonic surgical instrument of Example 1, wherein the plurality of reference complex impedance patterns correspond to at least one of the ultrasonic blade contacting air, the ultrasonic blade being broken, or the ultrasonic blade contacting metal.
Example 3. The ultrasonic surgical instrument of Example 1 or 2, further comprising a memory coupled to the control circuit. The memory stores the plurality of reference complex impedance patterns. The control circuit is configured to retrieve the plurality of reference complex impedance patterns from the memory.
Example 4. The ultrasonic surgical instrument of any one of Examples 1-3, wherein the reference complex impedance patterns comprise fitted curves plotted from data points of the reference complex impedance patterns.
Example 5. The ultrasonic surgical instrument of Example 4, wherein the control circuit is configured to determine which of the plurality of reference complex impedance patterns the complex impedance corresponds according to a Euclidean perpendicular distance between the complex impedance and the fitted curves.
Example 6. The ultrasonic surgical instrument of Example 5, wherein the complex impedance corresponds to which of the fitted curves the complex impedance has a smallest Euclidean perpendicular distance therebetween.
Example 7. The ultrasonic surgical instrument of any one of Examples 1-6, wherein the complex impedance corresponds to a ratio between a voltage signal and a current signal exciting the ultrasonic transducer.
Example 8. An ultrasonic generator for driving an ultrasonic surgical instrument comprising an end effector, an ultrasonic blade, and an ultrasonic transducer acoustically coupled to the ultrasonic blade. The ultrasonic transducer is configured to ultrasonically oscillate the ultrasonic blade in response to a drive signal. The ultrasonic generator comprises a control circuit coupled to the ultrasonic transducer. The control circuit is configured to: apply the drive signal to the ultrasonic transducer, measure a complex impedance of the ultrasonic transducer, compare the complex impedance to a plurality of reference complex impedance patterns, each of the plurality of reference complex impedance patterns corresponding to a state of the end effector, and determine the state of the end effector according to which of the plurality of reference complex impedance patterns the complex impedance corresponds.
Example 9. The ultrasonic generator of Example 8, wherein the plurality of reference complex impedance patterns correspond to at least one of the ultrasonic blade contacting air, the ultrasonic blade being broken, or the ultrasonic blade contacting metal.
Example 10. The ultrasonic generator of Example 8 or 9, further comprising a memory coupled to the control circuit. The memory stores the plurality of reference complex impedance patterns. The control circuit is configured to retrieve the plurality of reference complex impedance patterns from the memory.
Example 11. The ultrasonic generator of at least one of Examples 8-10, wherein the reference complex impedance patterns comprise fitted curves plotted from data points of the reference complex impedance patterns.
Example 12. The ultrasonic generator of Example 11, wherein the control circuit is configured to determine which of the plurality of reference complex impedance patterns the complex impedance corresponds according to a Euclidean perpendicular distance between the complex impedance and the fitted curves.
Example 13. The ultrasonic generator of Example 12, wherein the complex impedance corresponds to which of the fitted curves the complex impedance has a smallest Euclidean perpendicular distance therebetween.
Example 14. The ultrasonic generator of any one of Examples 8-13, wherein the complex impedance corresponds to a ratio between a voltage signal and a current signal exciting the ultrasonic transducer.
Example 15. A method of controlling an ultrasonic surgical instrument comprising an end effector, an ultrasonic blade, and an ultrasonic transducer acoustically coupled to the ultrasonic blade. The ultrasonic transducer is configured to ultrasonically oscillate the ultrasonic blade in response to a drive signal from a generator. The method comprises: measuring, by a control circuit coupled to the ultrasonic transducer, a complex impedance of the ultrasonic transducer; comparing, by the control circuit, the complex impedance to a plurality of reference complex impedance patterns, each of the plurality of reference complex impedance patterns corresponding to a state of the end effector; and determining, by the control circuit, the state of the end effector according to which of the plurality of reference complex impedance patterns the complex impedance corresponds.
Example 16. The method of Example 15, wherein the plurality of reference complex impedance patterns correspond to at least one of the ultrasonic blade contacting air, the ultrasonic blade being broken, or the ultrasonic blade contacting metal.
Example 17. The method of Example 15 or 16, further comprising retrieving, by the control circuit, the plurality of reference complex impedance patterns from a memory.
Example 18. The method of any one of Examples 15-17, wherein the reference complex impedance patterns comprise fitted curves plotted from data points of the reference complex impedance patterns.
Example 19. The method of Example 18, further comprising determining, by the control circuit, which of the plurality of reference complex impedance patterns the complex impedance corresponds according to a Euclidean perpendicular distance between the complex impedance and the fitted curves.
Example 20. The method of Example 19, wherein the complex impedance corresponds to which of the fitted curves the complex impedance has a smallest Euclidean perpendicular distance therebetween.
Example 21. The method of any one of Examples 15-20, wherein the complex impedance corresponds to a ratio between a voltage signal and a current signal exciting the ultrasonic transducer.
The present application claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 62/721,996, titled RADIO FREQUENCY ENERGY DEVICE FOR DELIVERING COMBINED ELECTRICAL SIGNALS, filed on Aug. 23, 2018, the disclosure of which is herein incorporated by reference in its entirety. The present application also claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 62/692,748, titled SMART ENERGY ARCHITECTURE, filed on Jun. 30, 2018 and to U.S. Provisional Patent Application No. 62/692,768, titled SMART ENERGY DEVICES, filed on Jun. 30, 2018, the disclosure of each of which is herein incorporated by reference in its entirety. This application also claims the benefit of priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application Ser. No. 62/640,417, titled TEMPERATURE CONTROL IN ULTRASONIC DEVICE AND CONTROL SYSTEM THEREFOR, filed Mar. 8, 2018, and to U.S. Provisional Patent Application Ser. No. 62/640,415, titled ESTIMATING STATE OF ULTRASONIC END EFFECTOR AND CONTROL SYSTEM THEREFOR, filed Mar. 8, 2018, the disclosure of each of which is herein incorporated by reference in its entirety. This application also claims the benefit of priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 62/650,898 filed on Mar. 30, 2018, titled CAPACITIVE COUPLED RETURN PATH PAD WITH SEPARABLE ARRAY ELEMENTS, the disclosure of which is herein incorporated by reference in its entirety.
| Number | Name | Date | Kind |
|---|---|---|---|
| 1853416 | Hall | Apr 1932 | A |
| 2222125 | Stehlik | Nov 1940 | A |
| 3082426 | Miles | Mar 1963 | A |
| 3503396 | Pierie et al. | Mar 1970 | A |
| 3584628 | Green | Jun 1971 | A |
| 3626457 | Duerr et al. | Dec 1971 | A |
| 3633584 | Farrell | Jan 1972 | A |
| 3759017 | Young | Sep 1973 | A |
| 3863118 | Lander et al. | Jan 1975 | A |
| 3898545 | Coppa et al. | Aug 1975 | A |
| 3912121 | Steffen | Oct 1975 | A |
| 3915271 | Harper | Oct 1975 | A |
| 3932812 | Milligan | Jan 1976 | A |
| 4041362 | Ichiyanagi | Aug 1977 | A |
| 4052649 | Greenwell et al. | Oct 1977 | A |
| 4087730 | Goles | May 1978 | A |
| 4157859 | Terry | Jun 1979 | A |
| 4171700 | Farin | Oct 1979 | A |
| 4202722 | Paquin | May 1980 | A |
| 4412539 | Jarvik | Nov 1983 | A |
| 4448193 | Ivanov | May 1984 | A |
| 4523695 | Braun et al. | Jun 1985 | A |
| 4608160 | Zoch | Aug 1986 | A |
| 4614366 | North et al. | Sep 1986 | A |
| 4633874 | Chow et al. | Jan 1987 | A |
| 4701193 | Robertson et al. | Oct 1987 | A |
| 4735603 | Goodson et al. | Apr 1988 | A |
| 4788977 | Farin et al. | Dec 1988 | A |
| 4849752 | Bryant | Jul 1989 | A |
| D303787 | Messenger et al. | Oct 1989 | S |
| 4892244 | Fox et al. | Jan 1990 | A |
| 5010341 | Huntley et al. | Apr 1991 | A |
| 5026387 | Thomas | Jun 1991 | A |
| 5035692 | Lyon et al. | Jul 1991 | A |
| 5042460 | Sakurai | Aug 1991 | A |
| 5047043 | Kubota et al. | Sep 1991 | A |
| 5084057 | Green et al. | Jan 1992 | A |
| 5100402 | Fan | Mar 1992 | A |
| D327061 | Soren et al. | Jun 1992 | S |
| 5129570 | Schulze et al. | Jul 1992 | A |
| 5151102 | Kamiyama et al. | Sep 1992 | A |
| 5156315 | Green et al. | Oct 1992 | A |
| 5158585 | Saho et al. | Oct 1992 | A |
| 5171247 | Hughett et al. | Dec 1992 | A |
| 5189277 | Boisvert et al. | Feb 1993 | A |
| 5197962 | Sansom et al. | Mar 1993 | A |
| 5204669 | Dorfe et al. | Apr 1993 | A |
| 5242474 | Herbst et al. | Sep 1993 | A |
| 5253793 | Green et al. | Oct 1993 | A |
| 5271543 | Grant et al. | Dec 1993 | A |
| RE34519 | Fox et al. | Jan 1994 | E |
| 5275323 | Schulze et al. | Jan 1994 | A |
| 5318516 | Cosmescu | Jun 1994 | A |
| 5318563 | Malis et al. | Jun 1994 | A |
| 5322055 | Davison et al. | Jun 1994 | A |
| 5342349 | Kaufman | Aug 1994 | A |
| 5364003 | Williamson, IV | Nov 1994 | A |
| 5383880 | Hooven | Jan 1995 | A |
| 5396900 | Slater et al. | Mar 1995 | A |
| 5397046 | Savage et al. | Mar 1995 | A |
| 5403312 | Yates et al. | Apr 1995 | A |
| 5403327 | Thornton et al. | Apr 1995 | A |
| 5413267 | Solyntjes et al. | May 1995 | A |
| 5415335 | Knodell, Jr. | May 1995 | A |
| 5417699 | Klein et al. | May 1995 | A |
| 5439468 | Schulze et al. | Aug 1995 | A |
| 5445304 | Plyley et al. | Aug 1995 | A |
| 5462545 | Wang et al. | Oct 1995 | A |
| 5465895 | Knodel et al. | Nov 1995 | A |
| 5467911 | Tsuruta et al. | Nov 1995 | A |
| 5474566 | Alesi et al. | Dec 1995 | A |
| 5485947 | Olson et al. | Jan 1996 | A |
| 5496315 | Weaver et al. | Mar 1996 | A |
| 5503320 | Webster et al. | Apr 1996 | A |
| 5529235 | Boiarski et al. | Jun 1996 | A |
| 5531743 | Nettekoven et al. | Jul 1996 | A |
| 5545148 | Wurster | Aug 1996 | A |
| 5552685 | Young et al. | Sep 1996 | A |
| 5560372 | Cory | Oct 1996 | A |
| 5584425 | Savage et al. | Dec 1996 | A |
| 5610379 | Muz et al. | Mar 1997 | A |
| 5610811 | Honda | Mar 1997 | A |
| 5613966 | Makower et al. | Mar 1997 | A |
| 5624452 | Yates | Apr 1997 | A |
| D379346 | Mieki | May 1997 | S |
| 5626587 | Bishop et al. | May 1997 | A |
| 5643291 | Pier et al. | Jul 1997 | A |
| 5654750 | Weil et al. | Aug 1997 | A |
| 5673841 | Schulze et al. | Oct 1997 | A |
| 5673842 | Bittner et al. | Oct 1997 | A |
| 5675227 | Roos et al. | Oct 1997 | A |
| 5693042 | Boiarski et al. | Dec 1997 | A |
| 5693052 | Weaver | Dec 1997 | A |
| 5695502 | Pier et al. | Dec 1997 | A |
| 5697926 | Weaver | Dec 1997 | A |
| 5706998 | Plyley et al. | Jan 1998 | A |
| 5718359 | Palmer et al. | Feb 1998 | A |
| 5724468 | Leone et al. | Mar 1998 | A |
| 5725536 | Oberlin et al. | Mar 1998 | A |
| 5725542 | Yoon | Mar 1998 | A |
| 5735445 | Vidal et al. | Apr 1998 | A |
| 5735848 | Yates et al. | Apr 1998 | A |
| 5746209 | Yost et al. | May 1998 | A |
| 5749362 | Funda et al. | May 1998 | A |
| 5749893 | Vidal et al. | May 1998 | A |
| 5752644 | Bolanos et al. | May 1998 | A |
| 5762255 | Chrisman et al. | Jun 1998 | A |
| 5766186 | Faraz et al. | Jun 1998 | A |
| 5769791 | Benaron et al. | Jun 1998 | A |
| 5775331 | Raymond et al. | Jul 1998 | A |
| 5797537 | Oberlin et al. | Aug 1998 | A |
| 5800350 | Coppleson et al. | Sep 1998 | A |
| D399561 | Ellingson | Oct 1998 | S |
| 5817093 | Williamson, IV et al. | Oct 1998 | A |
| 5820009 | Melling et al. | Oct 1998 | A |
| 5833690 | Yates et al. | Nov 1998 | A |
| 5836849 | Mathiak et al. | Nov 1998 | A |
| 5836869 | Kudo et al. | Nov 1998 | A |
| 5836909 | Cosmescu | Nov 1998 | A |
| 5843080 | Fleenor et al. | Dec 1998 | A |
| 5846237 | Nettekoven | Dec 1998 | A |
| 5849022 | Sakashita et al. | Dec 1998 | A |
| 5873873 | Smith et al. | Feb 1999 | A |
| 5878938 | Bittner et al. | Mar 1999 | A |
| 5893849 | Weaver | Apr 1999 | A |
| 5906625 | Bito et al. | May 1999 | A |
| 5942333 | Arnett et al. | Aug 1999 | A |
| 5947996 | Logeman | Sep 1999 | A |
| 5968032 | Sleister | Oct 1999 | A |
| 5980510 | Tsonton et al. | Nov 1999 | A |
| 5987346 | Benaron et al. | Nov 1999 | A |
| 5997528 | Bisch et al. | Dec 1999 | A |
| 6010054 | Johnson et al. | Jan 2000 | A |
| 6030437 | Gourrier et al. | Feb 2000 | A |
| 6036637 | Kudo | Mar 2000 | A |
| 6039734 | Goble | Mar 2000 | A |
| 6039735 | Greep | Mar 2000 | A |
| 6059799 | Aranyi et al. | May 2000 | A |
| 6066137 | Greep | May 2000 | A |
| 6079606 | Milliman et al. | Jun 2000 | A |
| 6090107 | Borgmeier et al. | Jul 2000 | A |
| 6099537 | Sugai et al. | Aug 2000 | A |
| 6102907 | Smethers et al. | Aug 2000 | A |
| 6109500 | Alli et al. | Aug 2000 | A |
| 6113598 | Baker | Sep 2000 | A |
| 6126592 | Proch et al. | Oct 2000 | A |
| 6126658 | Baker | Oct 2000 | A |
| 6131789 | Schulze et al. | Oct 2000 | A |
| 6155473 | Tompkins et al. | Dec 2000 | A |
| 6214000 | Fleenor et al. | Apr 2001 | B1 |
| 6258105 | Hart et al. | Jul 2001 | B1 |
| 6269411 | Reasoner | Jul 2001 | B1 |
| 6273887 | Yamauchi et al. | Aug 2001 | B1 |
| 6301495 | Gueziec et al. | Oct 2001 | B1 |
| 6302881 | Farin | Oct 2001 | B1 |
| 6308089 | von der Ruhr et al. | Oct 2001 | B1 |
| 6325808 | Bernard et al. | Dec 2001 | B1 |
| 6325811 | Messerly | Dec 2001 | B1 |
| 6331181 | Tierney et al. | Dec 2001 | B1 |
| 6341164 | Dilkie et al. | Jan 2002 | B1 |
| 6391102 | Bodden et al. | May 2002 | B1 |
| 6434416 | Mizoguchi et al. | Aug 2002 | B1 |
| 6443973 | Whitman | Sep 2002 | B1 |
| 6451015 | Rittman, III et al. | Sep 2002 | B1 |
| 6454781 | Witt et al. | Sep 2002 | B1 |
| 6457625 | Tormala et al. | Oct 2002 | B1 |
| 6461352 | Morgan et al. | Oct 2002 | B2 |
| 6466817 | Kaula et al. | Oct 2002 | B1 |
| 6480796 | Wiener | Nov 2002 | B2 |
| 6524307 | Palmerton et al. | Feb 2003 | B1 |
| 6530933 | Yeung et al. | Mar 2003 | B1 |
| 6551243 | Bocionek et al. | Apr 2003 | B2 |
| 6569109 | Sakurai et al. | May 2003 | B2 |
| 6582424 | Fleenor et al. | Jun 2003 | B2 |
| 6584358 | Carter et al. | Jun 2003 | B2 |
| 6585791 | Garito et al. | Jul 2003 | B1 |
| 6611793 | Burnside et al. | Aug 2003 | B1 |
| 6618626 | West, Jr. et al. | Sep 2003 | B2 |
| 6633234 | Wiener | Oct 2003 | B2 |
| 6648223 | Boukhny et al. | Nov 2003 | B2 |
| 6678552 | Pearlman | Jan 2004 | B2 |
| 6679899 | Wiener et al. | Jan 2004 | B2 |
| 6685704 | Greep | Feb 2004 | B2 |
| 6699187 | Webb et al. | Mar 2004 | B2 |
| 6731514 | Evans | May 2004 | B2 |
| 6742895 | Robin | Jun 2004 | B2 |
| 6752816 | Culp et al. | Jun 2004 | B2 |
| 6760616 | Hoey et al. | Jul 2004 | B2 |
| 6770072 | Truckai et al. | Aug 2004 | B1 |
| 6773444 | Messerly | Aug 2004 | B2 |
| 6775575 | Bommannan et al. | Aug 2004 | B2 |
| 6778846 | Martinez et al. | Aug 2004 | B1 |
| 6781683 | Kacyra et al. | Aug 2004 | B2 |
| 6783524 | Anderson et al. | Aug 2004 | B2 |
| 6783525 | Greep et al. | Aug 2004 | B2 |
| 6793663 | Kneifel et al. | Sep 2004 | B2 |
| 6824539 | Novak | Nov 2004 | B2 |
| 6846308 | Whitman et al. | Jan 2005 | B2 |
| 6849074 | Chen et al. | Feb 2005 | B2 |
| 6852219 | Hammond | Feb 2005 | B2 |
| 6863650 | Irion | Mar 2005 | B1 |
| 6869430 | Balbierz et al. | Mar 2005 | B2 |
| 6869435 | Blake, III | Mar 2005 | B2 |
| 6911033 | de Guillebon et al. | Jun 2005 | B2 |
| 6913471 | Smith | Jul 2005 | B2 |
| 6937892 | Leyde et al. | Aug 2005 | B2 |
| 6945981 | Donofrio et al. | Sep 2005 | B2 |
| 6951559 | Greep | Oct 2005 | B1 |
| 6962587 | Johnson et al. | Nov 2005 | B2 |
| 6978921 | Shelton, IV et al. | Dec 2005 | B2 |
| 6988649 | Shelton, IV et al. | Jan 2006 | B2 |
| 7000818 | Shelton, IV et al. | Feb 2006 | B2 |
| 7009511 | Mazar et al. | Mar 2006 | B2 |
| 7030146 | Baynes et al. | Apr 2006 | B2 |
| 7032798 | Whitman et al. | Apr 2006 | B2 |
| 7041941 | Fanes, Jr. et al. | May 2006 | B2 |
| 7044352 | Shelton, IV et al. | May 2006 | B2 |
| 7044911 | Drinan et al. | May 2006 | B2 |
| 7044949 | Orszulak et al. | May 2006 | B2 |
| 7048775 | Jornitz et al. | May 2006 | B2 |
| 7053752 | Wang et al. | May 2006 | B2 |
| 7055730 | Ehrenfels et al. | Jun 2006 | B2 |
| 7073765 | Newkirk | Jul 2006 | B2 |
| 7077853 | Kramer et al. | Jul 2006 | B2 |
| 7077856 | Whitman | Jul 2006 | B2 |
| 7081096 | Brister et al. | Jul 2006 | B2 |
| 7097640 | Wang et al. | Aug 2006 | B2 |
| 7103688 | Strong | Sep 2006 | B2 |
| 7104949 | Anderson et al. | Sep 2006 | B2 |
| 7118564 | Ritchie et al. | Oct 2006 | B2 |
| 7121460 | Parsons et al. | Oct 2006 | B1 |
| 7137980 | Buysse et al. | Nov 2006 | B2 |
| 7140528 | Shelton, IV | Nov 2006 | B2 |
| 7143923 | Shelton, IV et al. | Dec 2006 | B2 |
| 7143925 | Shelton, IV et al. | Dec 2006 | B2 |
| 7147139 | Schwemberger et al. | Dec 2006 | B2 |
| 7155316 | Sutherland et al. | Dec 2006 | B2 |
| 7164940 | Hareyama et al. | Jan 2007 | B2 |
| 7169145 | Isaacson et al. | Jan 2007 | B2 |
| 7177533 | McFarlin et al. | Feb 2007 | B2 |
| 7182775 | de Guillebon et al. | Feb 2007 | B2 |
| 7207472 | Wukusick et al. | Apr 2007 | B2 |
| 7208005 | Frecker et al. | Apr 2007 | B2 |
| 7217269 | El-Galley et al. | May 2007 | B2 |
| 7230529 | Ketcherside, Jr. et al. | Jun 2007 | B2 |
| 7232447 | Gellman et al. | Jun 2007 | B2 |
| 7236817 | Papas et al. | Jun 2007 | B2 |
| 7246734 | Shelton, IV | Jul 2007 | B2 |
| 7252664 | Nasab et al. | Aug 2007 | B2 |
| 7278563 | Green | Oct 2007 | B1 |
| 7294106 | Birkenbach et al. | Nov 2007 | B2 |
| 7294116 | Ellman et al. | Nov 2007 | B1 |
| 7296724 | Green et al. | Nov 2007 | B2 |
| 7317955 | McGreevy | Jan 2008 | B2 |
| 7328828 | Ortiz et al. | Feb 2008 | B2 |
| 7334717 | Rethy et al. | Feb 2008 | B2 |
| 7343565 | Ying et al. | Mar 2008 | B2 |
| 7344532 | Goble et al. | Mar 2008 | B2 |
| 7353068 | Tanaka et al. | Apr 2008 | B2 |
| 7362228 | Nycz et al. | Apr 2008 | B2 |
| 7371227 | Zeiner | May 2008 | B2 |
| 7380695 | Doll et al. | Jun 2008 | B2 |
| 7383088 | Spinelli et al. | Jun 2008 | B2 |
| 7391173 | Schena | Jun 2008 | B2 |
| 7407074 | Ortiz et al. | Aug 2008 | B2 |
| 7408439 | Wang et al. | Aug 2008 | B2 |
| 7422136 | Marczyk | Sep 2008 | B1 |
| 7422139 | Shelton, IV et al. | Sep 2008 | B2 |
| 7423972 | Shaham et al. | Sep 2008 | B2 |
| D579876 | Novotney et al. | Nov 2008 | S |
| 7457804 | Uber, III et al. | Nov 2008 | B2 |
| D583328 | Chiang | Dec 2008 | S |
| 7464847 | Viola et al. | Dec 2008 | B2 |
| 7464849 | Shelton, IV et al. | Dec 2008 | B2 |
| 7496418 | Kim et al. | Feb 2009 | B2 |
| D589447 | Sasada et al. | Mar 2009 | S |
| 7515961 | Germanson et al. | Apr 2009 | B2 |
| 7518502 | Austin et al. | Apr 2009 | B2 |
| 7563259 | Takahashi | Jul 2009 | B2 |
| 7568604 | Ehrenfels et al. | Aug 2009 | B2 |
| 7575144 | Ortiz et al. | Aug 2009 | B2 |
| 7597731 | Palmerton et al. | Oct 2009 | B2 |
| 7617137 | Kreiner et al. | Nov 2009 | B2 |
| 7621192 | Conti et al. | Nov 2009 | B2 |
| 7621898 | Lalomia et al. | Nov 2009 | B2 |
| 7631793 | Rethy et al. | Dec 2009 | B2 |
| 7637410 | Marczyk | Dec 2009 | B2 |
| 7637907 | Blaha | Dec 2009 | B2 |
| 7641092 | Kruszynski et al. | Jan 2010 | B2 |
| 7644848 | Swayze et al. | Jan 2010 | B2 |
| 7667592 | Ohyama et al. | Feb 2010 | B2 |
| 7667839 | Bates | Feb 2010 | B2 |
| 7670334 | Hueil et al. | Mar 2010 | B2 |
| 7694865 | Scirica | Apr 2010 | B2 |
| 7699860 | Huitema et al. | Apr 2010 | B2 |
| 7720306 | Gardiner et al. | May 2010 | B2 |
| 7721934 | Shelton, IV et al. | May 2010 | B2 |
| 7721936 | Shalton, IV et al. | May 2010 | B2 |
| 7736357 | Lee, Jr. et al. | Jun 2010 | B2 |
| 7742176 | Braunecker et al. | Jun 2010 | B2 |
| 7743960 | Whitman et al. | Jun 2010 | B2 |
| 7753245 | Boudreaux et al. | Jul 2010 | B2 |
| 7757028 | Druke et al. | Jul 2010 | B2 |
| 7766207 | Mather et al. | Aug 2010 | B2 |
| 7766905 | Paterson et al. | Aug 2010 | B2 |
| 7770773 | Whitman et al. | Aug 2010 | B2 |
| 7771429 | Ballard et al. | Aug 2010 | B2 |
| 7776037 | Odom | Aug 2010 | B2 |
| 7782789 | Stultz et al. | Aug 2010 | B2 |
| 7784663 | Shelton, IV | Aug 2010 | B2 |
| 7803151 | Whitman | Sep 2010 | B2 |
| 7810692 | Hall et al. | Oct 2010 | B2 |
| 7818041 | Kim et al. | Oct 2010 | B2 |
| 7819298 | Hall et al. | Oct 2010 | B2 |
| 7832612 | Baxter, III et al. | Nov 2010 | B2 |
| 7833219 | Tashiro et al. | Nov 2010 | B2 |
| 7836085 | Petakov et al. | Nov 2010 | B2 |
| 7837079 | Holsten et al. | Nov 2010 | B2 |
| 7837680 | Isaacson et al. | Nov 2010 | B2 |
| 7841980 | Minosawa et al. | Nov 2010 | B2 |
| 7845537 | Shelton, IV et al. | Dec 2010 | B2 |
| 7857185 | Swayze et al. | Dec 2010 | B2 |
| D631252 | Leslie | Jan 2011 | S |
| 7862560 | Marion | Jan 2011 | B2 |
| 7862579 | Ortiz et al. | Jan 2011 | B2 |
| 7865236 | Cory et al. | Jan 2011 | B2 |
| 7884735 | Newkirk | Feb 2011 | B2 |
| 7887530 | Zemlok et al. | Feb 2011 | B2 |
| 7892337 | Palmerton et al. | Feb 2011 | B2 |
| 7907166 | Lamprecht et al. | Mar 2011 | B2 |
| 7913891 | Doll et al. | Mar 2011 | B2 |
| 7918230 | Whitman et al. | Apr 2011 | B2 |
| 7918377 | Measamer et al. | Apr 2011 | B2 |
| 7920706 | Asokan et al. | Apr 2011 | B2 |
| 7927014 | Dehler | Apr 2011 | B2 |
| 7932826 | Fritchie et al. | Apr 2011 | B2 |
| 7942300 | Rethy et al. | May 2011 | B2 |
| 7945065 | Menzl et al. | May 2011 | B2 |
| 7945342 | Tsai et al. | May 2011 | B2 |
| 7951148 | McClurken | May 2011 | B2 |
| 7954682 | Giordano et al. | Jun 2011 | B2 |
| 7955322 | Devengenzo et al. | Jun 2011 | B2 |
| 7956620 | Gilbert | Jun 2011 | B2 |
| 7963433 | Whitman et al. | Jun 2011 | B2 |
| 7966269 | Bauer et al. | Jun 2011 | B2 |
| 7967180 | Scirica | Jun 2011 | B2 |
| 7976553 | Shelton, IV et al. | Jul 2011 | B2 |
| 7979157 | Anvari | Jul 2011 | B2 |
| 7980443 | Scheib et al. | Jul 2011 | B2 |
| 7982776 | Dunki-Jacobs et al. | Jul 2011 | B2 |
| 7988028 | Farascioni et al. | Aug 2011 | B2 |
| 7993140 | Sakezles | Aug 2011 | B2 |
| 7995045 | Dunki-Jacobs | Aug 2011 | B2 |
| 8005947 | Morris et al. | Aug 2011 | B2 |
| 8007494 | Taylor et al. | Aug 2011 | B1 |
| 8007513 | Nalagatla et al. | Aug 2011 | B2 |
| 8010180 | Quaid et al. | Aug 2011 | B2 |
| 8012170 | Whitman et al. | Sep 2011 | B2 |
| 8015976 | Shah | Sep 2011 | B2 |
| 8016855 | Whitman et al. | Sep 2011 | B2 |
| 8019094 | Hsieh et al. | Sep 2011 | B2 |
| 8025199 | Whitman et al. | Sep 2011 | B2 |
| 8027710 | Dannan | Sep 2011 | B1 |
| 8035685 | Jensen | Oct 2011 | B2 |
| 8038686 | Huitema et al. | Oct 2011 | B2 |
| 8038693 | Allen | Oct 2011 | B2 |
| 8043560 | Okumoto et al. | Oct 2011 | B2 |
| 8054184 | Cline et al. | Nov 2011 | B2 |
| 8054752 | Druke et al. | Nov 2011 | B2 |
| 8062306 | Nobis et al. | Nov 2011 | B2 |
| 8062330 | Prommersberger et al. | Nov 2011 | B2 |
| 8066721 | Kortenbach et al. | Nov 2011 | B2 |
| 8074861 | Ehrenfels et al. | Dec 2011 | B2 |
| 8075571 | Vitali et al. | Dec 2011 | B2 |
| 8096459 | Ortiz et al. | Jan 2012 | B2 |
| 8118206 | Zand et al. | Feb 2012 | B2 |
| 8120301 | Goldberg et al. | Feb 2012 | B2 |
| 8123764 | Meade et al. | Feb 2012 | B2 |
| D655678 | Kobayashi et al. | Mar 2012 | S |
| 8128625 | Odom | Mar 2012 | B2 |
| 8131565 | Dicks et al. | Mar 2012 | B2 |
| 8136712 | Zingman | Mar 2012 | B2 |
| D657368 | Magee et al. | Apr 2012 | S |
| 8147486 | Honour et al. | Apr 2012 | B2 |
| 8155479 | Hoffman et al. | Apr 2012 | B2 |
| 8157145 | Shelton, IV et al. | Apr 2012 | B2 |
| 8157150 | Viola et al. | Apr 2012 | B2 |
| 8157151 | Ingmanson et al. | Apr 2012 | B2 |
| 8160098 | Yan et al. | Apr 2012 | B1 |
| 8160690 | Wilfley et al. | Apr 2012 | B2 |
| 8161977 | Shelton, IV et al. | Apr 2012 | B2 |
| 8170396 | Kuspa et al. | May 2012 | B2 |
| 8172836 | Ward | May 2012 | B2 |
| 8181839 | Beetel | May 2012 | B2 |
| 8185409 | Putnam et al. | May 2012 | B2 |
| 8206345 | Abboud et al. | Jun 2012 | B2 |
| 8208707 | Mendonca et al. | Jun 2012 | B2 |
| 8210411 | Yates et al. | Jul 2012 | B2 |
| 8214007 | Baker et al. | Jul 2012 | B2 |
| 8216849 | Petty | Jul 2012 | B2 |
| 8220688 | Laurent et al. | Jul 2012 | B2 |
| 8225643 | Abboud et al. | Jul 2012 | B2 |
| 8225979 | Farascioni et al. | Jul 2012 | B2 |
| 8229549 | Whitman et al. | Jul 2012 | B2 |
| 8231042 | Hessler et al. | Jul 2012 | B2 |
| 8239066 | Jennings et al. | Aug 2012 | B2 |
| 8241322 | Whitman et al. | Aug 2012 | B2 |
| 8255045 | Gharib et al. | Aug 2012 | B2 |
| D667838 | Magee et al. | Sep 2012 | S |
| 8257387 | Cunningham | Sep 2012 | B2 |
| 8260016 | Maeda et al. | Sep 2012 | B2 |
| 8262560 | Whitman | Sep 2012 | B2 |
| 8292639 | Achammer et al. | Oct 2012 | B2 |
| 8292888 | Whitman | Oct 2012 | B2 |
| 8295902 | Salahieh et al. | Oct 2012 | B2 |
| 8308040 | Huang et al. | Nov 2012 | B2 |
| 8321581 | Katis et al. | Nov 2012 | B2 |
| 8322590 | Patel et al. | Dec 2012 | B2 |
| 8328065 | Shah | Dec 2012 | B2 |
| 8335590 | Costa et al. | Dec 2012 | B2 |
| D675164 | Kobayashi et al. | Jan 2013 | S |
| 8343065 | Bartol et al. | Jan 2013 | B2 |
| 8346392 | Walser et al. | Jan 2013 | B2 |
| 8360299 | Zemlok et al. | Jan 2013 | B2 |
| 8364222 | Cook et al. | Jan 2013 | B2 |
| D676392 | Gassauer | Feb 2013 | S |
| 8365975 | Manoux et al. | Feb 2013 | B1 |
| D678196 | Miyauchi et al. | Mar 2013 | S |
| D678304 | Yakoub et al. | Mar 2013 | S |
| 8388652 | Viola | Mar 2013 | B2 |
| 8393514 | Shelton, IV et al. | Mar 2013 | B2 |
| 8397972 | Kostrzewski | Mar 2013 | B2 |
| 8398541 | DiMaio et al. | Mar 2013 | B2 |
| 8403944 | Pain et al. | Mar 2013 | B2 |
| 8403945 | Whitfield et al. | Mar 2013 | B2 |
| 8403946 | Whitfield et al. | Mar 2013 | B2 |
| 8406859 | Zuzak et al. | Mar 2013 | B2 |
| 8411034 | Boillot et al. | Apr 2013 | B2 |
| 8413871 | Racenet et al. | Apr 2013 | B2 |
| 8422035 | Hinderling et al. | Apr 2013 | B2 |
| 8423182 | Robinson et al. | Apr 2013 | B2 |
| 8428722 | Verhoef et al. | Apr 2013 | B2 |
| 8429153 | Birdwell | Apr 2013 | B2 |
| 8439910 | Greep et al. | May 2013 | B2 |
| 8444663 | Houser et al. | May 2013 | B2 |
| 8452615 | Abri | May 2013 | B2 |
| 8454506 | Rothman et al. | Jun 2013 | B2 |
| 8461744 | Wiener et al. | Jun 2013 | B2 |
| 8468030 | Stroup et al. | Jun 2013 | B2 |
| 8469973 | Meade et al. | Jun 2013 | B2 |
| 8472630 | Konrad et al. | Jun 2013 | B2 |
| D687146 | Juzkiw et al. | Jul 2013 | S |
| 8476227 | Kaplan et al. | Jul 2013 | B2 |
| 8489235 | Moll et al. | Jul 2013 | B2 |
| 8499992 | Whitman et al. | Aug 2013 | B2 |
| 8500728 | Newton et al. | Aug 2013 | B2 |
| 8500756 | Papa et al. | Aug 2013 | B2 |
| 8503759 | Greer et al. | Aug 2013 | B2 |
| 8505801 | Ehrenfels et al. | Aug 2013 | B2 |
| 8506478 | Mizuyoshi | Aug 2013 | B2 |
| 8512325 | Mathonnet | Aug 2013 | B2 |
| 8512365 | Wiener et al. | Aug 2013 | B2 |
| 8515520 | Brunnett et al. | Aug 2013 | B2 |
| 8517239 | Scheib et al. | Aug 2013 | B2 |
| 8521331 | Itkowitz | Aug 2013 | B2 |
| 8523043 | Ullrich et al. | Sep 2013 | B2 |
| 8540709 | Allen | Sep 2013 | B2 |
| 8546996 | Messerly et al. | Oct 2013 | B2 |
| 8554697 | Claus et al. | Oct 2013 | B2 |
| 8560047 | Haider et al. | Oct 2013 | B2 |
| 8561870 | Baxter, III et al. | Oct 2013 | B2 |
| 8562598 | Falkenstein et al. | Oct 2013 | B2 |
| 8566115 | Moore | Oct 2013 | B2 |
| 8567393 | Hickle et al. | Oct 2013 | B2 |
| 8571598 | Valavi | Oct 2013 | B2 |
| 8573459 | Smith et al. | Nov 2013 | B2 |
| 8573465 | Shelton, IV | Nov 2013 | B2 |
| 8574229 | Eder et al. | Nov 2013 | B2 |
| 8585694 | Amoah et al. | Nov 2013 | B2 |
| 8590762 | Hess et al. | Nov 2013 | B2 |
| 8591536 | Robertson | Nov 2013 | B2 |
| 8595607 | Nekoomaram et al. | Nov 2013 | B2 |
| 8596513 | Olson et al. | Dec 2013 | B2 |
| 8596515 | Okoniewski | Dec 2013 | B2 |
| 8604709 | Jalbout et al. | Dec 2013 | B2 |
| 8608044 | Hueil et al. | Dec 2013 | B2 |
| 8608045 | Smith et al. | Dec 2013 | B2 |
| 8616431 | Timm et al. | Dec 2013 | B2 |
| 8620055 | Barratt et al. | Dec 2013 | B2 |
| 8620473 | Diolaiti et al. | Dec 2013 | B2 |
| 8623027 | Price et al. | Jan 2014 | B2 |
| 8627483 | Rachlin et al. | Jan 2014 | B2 |
| 8627993 | Smith et al. | Jan 2014 | B2 |
| 8627995 | Smith et al. | Jan 2014 | B2 |
| 8628518 | Blumenkranz et al. | Jan 2014 | B2 |
| 8628545 | Cabrera et al. | Jan 2014 | B2 |
| 8631987 | Shelton, IV et al. | Jan 2014 | B2 |
| 8632525 | Kerr et al. | Jan 2014 | B2 |
| 8636190 | Zemlok et al. | Jan 2014 | B2 |
| 8636736 | Yates et al. | Jan 2014 | B2 |
| 8641621 | Razzaque et al. | Feb 2014 | B2 |
| 8652086 | Gerg et al. | Feb 2014 | B2 |
| 8652121 | Quick et al. | Feb 2014 | B2 |
| 8652128 | Ward | Feb 2014 | B2 |
| 8657176 | Shelton, IV et al. | Feb 2014 | B2 |
| 8657177 | Scirica et al. | Feb 2014 | B2 |
| 8663220 | Wiener et al. | Mar 2014 | B2 |
| 8666544 | Moll et al. | Mar 2014 | B2 |
| 8679114 | Chapman et al. | Mar 2014 | B2 |
| 8682049 | Zhao et al. | Mar 2014 | B2 |
| 8682489 | Itkowitz et al. | Mar 2014 | B2 |
| 8685056 | Evans et al. | Apr 2014 | B2 |
| 8688188 | Heller et al. | Apr 2014 | B2 |
| 8690864 | Hoarau | Apr 2014 | B2 |
| 8701962 | Kostrzewski | Apr 2014 | B2 |
| D704839 | Juzkiw et al. | May 2014 | S |
| 8719061 | Birchall | May 2014 | B2 |
| 8720766 | Hess et al. | May 2014 | B2 |
| 8733613 | Huitema et al. | May 2014 | B2 |
| 8740840 | Foley et al. | Jun 2014 | B2 |
| 8740866 | Reasoner et al. | Jun 2014 | B2 |
| 8747238 | Shelton, IV et al. | Jun 2014 | B2 |
| 8752749 | Moore et al. | Jun 2014 | B2 |
| 8757465 | Woodard, Jr. et al. | Jun 2014 | B2 |
| 8761717 | Buchheit | Jun 2014 | B1 |
| 8763879 | Shelton, IV et al. | Jul 2014 | B2 |
| 8768251 | Claus et al. | Jul 2014 | B2 |
| 8771270 | Burbank | Jul 2014 | B2 |
| 8775196 | Simpson et al. | Jul 2014 | B2 |
| 8779648 | Giordano et al. | Jul 2014 | B2 |
| 8790253 | Sunagawa et al. | Jul 2014 | B2 |
| 8794497 | Zingman | Aug 2014 | B2 |
| 8795001 | Lam et al. | Aug 2014 | B1 |
| 8799008 | Johnson et al. | Aug 2014 | B2 |
| 8799009 | Mellin et al. | Aug 2014 | B2 |
| 8800838 | Shelton, IV | Aug 2014 | B2 |
| 8801703 | Gregg et al. | Aug 2014 | B2 |
| 8814996 | Giurgiutiu et al. | Aug 2014 | B2 |
| 8818556 | Sanchez et al. | Aug 2014 | B2 |
| 8819581 | Nakamura et al. | Aug 2014 | B2 |
| 8820603 | Shelton, IV et al. | Sep 2014 | B2 |
| 8820608 | Miyamoto | Sep 2014 | B2 |
| 8827134 | Viola et al. | Sep 2014 | B2 |
| 8840003 | Morgan et al. | Sep 2014 | B2 |
| D716333 | Chotin et al. | Oct 2014 | S |
| 8851354 | Swensgard et al. | Oct 2014 | B2 |
| 8852174 | Burbank | Oct 2014 | B2 |
| 8875973 | Whitman | Nov 2014 | B2 |
| 8882662 | Charles | Nov 2014 | B2 |
| 8886790 | Harrang et al. | Nov 2014 | B2 |
| 8893949 | Shelton, IV et al. | Nov 2014 | B2 |
| 8899479 | Cappuzzo et al. | Dec 2014 | B2 |
| 8905977 | Shelton et al. | Dec 2014 | B2 |
| 8912746 | Reid et al. | Dec 2014 | B2 |
| 8914098 | Brennan et al. | Dec 2014 | B2 |
| 8917513 | Hazzard | Dec 2014 | B1 |
| 8918207 | Prisco | Dec 2014 | B2 |
| 8920186 | Shishikura | Dec 2014 | B2 |
| 8920414 | Stone et al. | Dec 2014 | B2 |
| 8920433 | Barrier et al. | Dec 2014 | B2 |
| 8930203 | Kiaie et al. | Jan 2015 | B2 |
| 8930214 | Woolford | Jan 2015 | B2 |
| 8931679 | Kostrzewski | Jan 2015 | B2 |
| 8936614 | Allen, IV | Jan 2015 | B2 |
| 8945095 | Blumenkranz et al. | Feb 2015 | B2 |
| 8945163 | Voegele et al. | Feb 2015 | B2 |
| 8955732 | Zemlok et al. | Feb 2015 | B2 |
| 8956581 | Rosenbaum et al. | Feb 2015 | B2 |
| 8960519 | Whitman et al. | Feb 2015 | B2 |
| 8960520 | McCuen | Feb 2015 | B2 |
| 8962062 | Podhajsky et al. | Feb 2015 | B2 |
| 8967443 | McCuen | Mar 2015 | B2 |
| 8967455 | Zhou | Mar 2015 | B2 |
| 8968276 | Zemlok et al. | Mar 2015 | B2 |
| 8968296 | McPherson | Mar 2015 | B2 |
| 8968309 | Roy et al. | Mar 2015 | B2 |
| 8968312 | Marczyk et al. | Mar 2015 | B2 |
| 8968337 | Whitfield et al. | Mar 2015 | B2 |
| 8968358 | Reschke | Mar 2015 | B2 |
| 8974429 | Gordon et al. | Mar 2015 | B2 |
| 8979890 | Boudreaux | Mar 2015 | B2 |
| 8986288 | Konishi | Mar 2015 | B2 |
| 8986302 | Aldridge et al. | Mar 2015 | B2 |
| 8989903 | Weir et al. | Mar 2015 | B2 |
| 8991678 | Wellman et al. | Mar 2015 | B2 |
| 8992565 | Brisson et al. | Mar 2015 | B2 |
| 8998797 | Omori | Apr 2015 | B2 |
| 9002518 | Manzo et al. | Apr 2015 | B2 |
| 9010611 | Ross et al. | Apr 2015 | B2 |
| 9011366 | Dean et al. | Apr 2015 | B2 |
| 9011427 | Price et al. | Apr 2015 | B2 |
| 9016539 | Kostrzewski et al. | Apr 2015 | B2 |
| 9017326 | DiNardo et al. | Apr 2015 | B2 |
| 9020240 | Pettersson et al. | Apr 2015 | B2 |
| D729267 | Yoo et al. | May 2015 | S |
| 9023032 | Robinson | May 2015 | B2 |
| 9023071 | Miller et al. | May 2015 | B2 |
| 9027431 | Tang et al. | May 2015 | B2 |
| 9028494 | Shelton, IV et al. | May 2015 | B2 |
| 9035568 | Ganton et al. | May 2015 | B2 |
| 9038882 | Racenet et al. | May 2015 | B2 |
| 9043027 | Durant et al. | May 2015 | B2 |
| 9044227 | Shelton, IV et al. | Jun 2015 | B2 |
| 9044244 | Ludwin et al. | Jun 2015 | B2 |
| 9044261 | Houser | Jun 2015 | B2 |
| 9050063 | Roe et al. | Jun 2015 | B2 |
| 9050083 | Yates et al. | Jun 2015 | B2 |
| 9050120 | Swarup et al. | Jun 2015 | B2 |
| 9052809 | Vesto | Jun 2015 | B2 |
| 9055035 | Porsch et al. | Jun 2015 | B2 |
| 9055870 | Meador et al. | Jun 2015 | B2 |
| 9060770 | Shelton, IV et al. | Jun 2015 | B2 |
| 9060775 | Wiener et al. | Jun 2015 | B2 |
| 9066650 | Sekiguchi | 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 |
| 9078653 | Leimbach et al. | Jul 2015 | B2 |
| 9078727 | Miller | Jul 2015 | B2 |
| 9084606 | Greep | 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 |
| 9101359 | Smith et al. | Aug 2015 | B2 |
| 9101374 | Hoch et al. | Aug 2015 | B1 |
| 9106270 | Puterbaugh et al. | Aug 2015 | B2 |
| 9107573 | Birnkrant | Aug 2015 | B2 |
| 9107662 | Kostrzewski | Aug 2015 | B2 |
| 9107684 | Ma | Aug 2015 | B2 |
| 9107688 | Kimball et al. | Aug 2015 | B2 |
| 9107689 | Robertson et al. | Aug 2015 | B2 |
| 9107694 | Hendriks et al. | Aug 2015 | B2 |
| 9111548 | Nandy et al. | Aug 2015 | B2 |
| 9113880 | Zemlok et al. | Aug 2015 | B2 |
| 9114494 | Mah | Aug 2015 | B1 |
| 9116597 | Gulasky | Aug 2015 | B1 |
| 9119617 | Souls et al. | Sep 2015 | B2 |
| 9119655 | Bowling et al. | Sep 2015 | B2 |
| 9119657 | Shelton, IV et al. | Sep 2015 | B2 |
| 9123155 | Cunningham et al. | Sep 2015 | B2 |
| 9125644 | Lane et al. | Sep 2015 | B2 |
| 9129054 | Nawana et al. | Sep 2015 | B2 |
| 9137254 | Bilbrey et al. | Sep 2015 | B2 |
| 9138129 | Diolaiti | Sep 2015 | B2 |
| 9138225 | Huang et al. | Sep 2015 | B2 |
| 9149322 | Knowlton | Oct 2015 | B2 |
| 9155503 | Cadwell | Oct 2015 | B2 |
| 9160853 | Daddi et al. | Oct 2015 | B1 |
| 9161803 | Yates et al. | Oct 2015 | B2 |
| 9168054 | Turner et al. | Oct 2015 | B2 |
| 9168091 | Janssen et al. | Oct 2015 | B2 |
| 9168104 | Dein | Oct 2015 | B2 |
| 9179912 | Yates et al. | Nov 2015 | B2 |
| 9183723 | Sherman et al. | Nov 2015 | B2 |
| 9186143 | Timm et al. | Nov 2015 | B2 |
| 9192375 | Skinlo et al. | Nov 2015 | B2 |
| 9192447 | Choi et al. | Nov 2015 | B2 |
| 9192707 | Gerber et al. | Nov 2015 | B2 |
| 9198711 | Joseph | Dec 2015 | B2 |
| 9202078 | Abuelsaad et al. | Dec 2015 | B2 |
| 9204830 | Zand et al. | Dec 2015 | B2 |
| 9204879 | Shelton, IV | Dec 2015 | B2 |
| 9204995 | Scheller et al. | Dec 2015 | B2 |
| 9211120 | Scheib et al. | Dec 2015 | B2 |
| 9216062 | Duque et al. | Dec 2015 | B2 |
| 9218053 | Komuro et al. | Dec 2015 | B2 |
| 9220502 | Zemlok et al. | Dec 2015 | B2 |
| 9226689 | Jacobsen 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 |
| 9226791 | McCarthy et al. | Jan 2016 | B2 |
| 9232883 | Ozawa et al. | Jan 2016 | B2 |
| 9237891 | Shelton, IV | Jan 2016 | B2 |
| 9237921 | Messerly et al. | Jan 2016 | B2 |
| 9241728 | Price et al. | Jan 2016 | B2 |
| 9241730 | Babaev | Jan 2016 | B2 |
| 9241731 | Boudreaux et al. | Jan 2016 | B2 |
| 9247996 | Merana et al. | Feb 2016 | B1 |
| 9250172 | Harris et al. | Feb 2016 | B2 |
| 9255907 | Heanue et al. | Feb 2016 | B2 |
| 9265429 | St. Pierre et al. | Feb 2016 | B2 |
| 9265585 | Wingardner et al. | Feb 2016 | B2 |
| 9272406 | Aronhalt et al. | Mar 2016 | B2 |
| 9277956 | Zhang | Mar 2016 | B2 |
| 9277961 | Panescu et al. | Mar 2016 | B2 |
| 9277969 | Brannan et al. | Mar 2016 | B2 |
| 9280884 | Schultz et al. | Mar 2016 | B1 |
| 9282962 | Schmid et al. | Mar 2016 | B2 |
| 9282974 | Shelton, IV | Mar 2016 | B2 |
| 9283045 | Rhee et al. | Mar 2016 | B2 |
| 9283054 | Morgan et al. | Mar 2016 | B2 |
| 9289211 | Williams et al. | Mar 2016 | B2 |
| 9289212 | Shelton, IV et al. | Mar 2016 | B2 |
| 9295514 | Shelton, IV et al. | Mar 2016 | B2 |
| 9301691 | Hufnagel et al. | Apr 2016 | B2 |
| 9301753 | Aldridge et al. | Apr 2016 | B2 |
| 9301759 | Spivey et al. | Apr 2016 | B2 |
| 9301810 | Amiri et al. | Apr 2016 | B2 |
| 9302213 | Manahan et al. | Apr 2016 | B2 |
| 9307894 | von Grunberg et al. | Apr 2016 | B2 |
| 9307914 | Fahey | Apr 2016 | B2 |
| 9307986 | Hall et al. | Apr 2016 | B2 |
| 9314246 | Shelton, IV et al. | Apr 2016 | B2 |
| 9314308 | Parihar et al. | Apr 2016 | B2 |
| 9320563 | Brustad et al. | Apr 2016 | B2 |
| 9325732 | Stickle et al. | Apr 2016 | B1 |
| 9326767 | Koch et al. | May 2016 | B2 |
| 9326770 | Shelton, IV et al. | May 2016 | B2 |
| 9331422 | Nazzaro et al. | May 2016 | B2 |
| 9332987 | Leimbach et al. | May 2016 | B2 |
| 9333042 | Diolaiti et al. | May 2016 | B2 |
| 9336385 | Spencer et al. | May 2016 | B1 |
| 9341704 | Picard et al. | May 2016 | B2 |
| 9345481 | Hall et al. | May 2016 | B2 |
| 9345490 | Ippisch | May 2016 | B2 |
| 9345546 | Toth et al. | May 2016 | B2 |
| 9345900 | Wu et al. | May 2016 | B2 |
| 9351726 | Leimbach et al. | May 2016 | B2 |
| 9351727 | Leimbach et al. | May 2016 | B2 |
| 9358003 | Hall et al. | Jun 2016 | B2 |
| 9358685 | Meier et al. | Jun 2016 | B2 |
| 9360449 | Durie | Jun 2016 | B2 |
| 9364231 | Wenchell | Jun 2016 | B2 |
| 9364249 | Kimball et al. | Jun 2016 | B2 |
| 9364294 | Razzaque et al. | Jun 2016 | B2 |
| 9370400 | Parihar | Jun 2016 | B2 |
| 9375282 | Nau, Jr. et al. | Jun 2016 | B2 |
| 9375539 | Stearns et al. | Jun 2016 | B2 |
| 9381003 | Todor et al. | Jul 2016 | B2 |
| 9381058 | Houser et al. | Jul 2016 | B2 |
| 9386984 | Aronhalt et al. | Jul 2016 | B2 |
| 9386988 | Baxter, III et al. | Jul 2016 | B2 |
| 9387295 | Mastri et al. | Jul 2016 | B1 |
| 9393017 | Flanagan et al. | Jul 2016 | B2 |
| 9393037 | Olson et al. | Jul 2016 | B2 |
| 9398905 | Martin | Jul 2016 | B2 |
| 9398911 | Auld | Jul 2016 | B2 |
| 9402629 | Ehrenfels et al. | Aug 2016 | B2 |
| 9414776 | Sillay et al. | Aug 2016 | B2 |
| 9414940 | Stein et al. | Aug 2016 | B2 |
| 9419018 | Sasagawa et al. | Aug 2016 | B2 |
| 9421014 | Ingmanson et al. | Aug 2016 | B2 |
| 9433470 | Choi | Sep 2016 | B2 |
| 9439622 | Case et al. | Sep 2016 | B2 |
| 9439668 | Timm et al. | Sep 2016 | B2 |
| 9439736 | Olson | Sep 2016 | B2 |
| 9445764 | Gross et al. | Sep 2016 | B2 |
| 9445813 | Shelton, IV et al. | Sep 2016 | B2 |
| 9450701 | Do et al. | Sep 2016 | B2 |
| 9451949 | Gorek et al. | Sep 2016 | B2 |
| 9451958 | Shelton, IV et al. | Sep 2016 | B2 |
| 9463022 | Swayze et al. | Oct 2016 | B2 |
| 9463646 | Payne et al. | Oct 2016 | B2 |
| 9468438 | Baber et al. | Oct 2016 | B2 |
| 9474565 | Shikhman et al. | Oct 2016 | B2 |
| D772252 | Myers et al. | Nov 2016 | S |
| 9480492 | Aranyi et al. | Nov 2016 | B2 |
| 9485475 | Speier et al. | Nov 2016 | B2 |
| 9486271 | Dunning | Nov 2016 | B2 |
| 9492146 | Kostrzewski et al. | Nov 2016 | B2 |
| 9492237 | Kang et al. | Nov 2016 | B2 |
| 9493807 | Little et al. | Nov 2016 | B2 |
| 9498182 | Case et al. | Nov 2016 | B2 |
| 9498215 | Duque et al. | Nov 2016 | B2 |
| 9498231 | Haider et al. | Nov 2016 | B2 |
| 9516239 | Blanquart et al. | Dec 2016 | B2 |
| 9519753 | Gerdeman et al. | Dec 2016 | B1 |
| 9522003 | Weir et al. | Dec 2016 | B2 |
| 9526407 | Hoeg et al. | Dec 2016 | B2 |
| 9526499 | Kostrzewski et al. | Dec 2016 | B2 |
| 9526587 | Zhao et al. | Dec 2016 | B2 |
| 9532827 | Morgan et al. | Jan 2017 | B2 |
| 9532845 | Dossett et al. | Jan 2017 | B1 |
| 9539007 | Dhakad et al. | Jan 2017 | B2 |
| 9539020 | Conlon et al. | Jan 2017 | B2 |
| 9542481 | Halter et al. | Jan 2017 | B2 |
| 9546662 | Shener-Irmakoglu et al. | Jan 2017 | B2 |
| 9549781 | He et al. | Jan 2017 | B2 |
| 9554692 | Levy | Jan 2017 | B2 |
| 9554794 | Baber et al. | Jan 2017 | B2 |
| 9554854 | Yates et al. | Jan 2017 | B2 |
| 9561038 | Shelton, IV et al. | Feb 2017 | B2 |
| 9561045 | Hinman et al. | Feb 2017 | B2 |
| 9561982 | Enicks et al. | Feb 2017 | B2 |
| 9566708 | Kurnianto | Feb 2017 | B2 |
| 9572592 | Price et al. | Feb 2017 | B2 |
| 9579503 | McKinney et al. | Feb 2017 | B2 |
| 9585657 | Shelton, IV et al. | Mar 2017 | B2 |
| 9592095 | Panescu et al. | Mar 2017 | B2 |
| 9597081 | Swayze et al. | Mar 2017 | B2 |
| 9600031 | Kaneko et al. | Mar 2017 | B2 |
| 9600138 | Thomas et al. | Mar 2017 | B2 |
| 9603024 | Wang et al. | Mar 2017 | B2 |
| 9603277 | Morgan et al. | Mar 2017 | B2 |
| D783675 | Yagisawa et al. | Apr 2017 | S |
| D784270 | Bhattacharya | Apr 2017 | S |
| 9610114 | Baxter, III et al. | Apr 2017 | B2 |
| 9622684 | Wybo | Apr 2017 | B2 |
| 9622808 | Beller et al. | Apr 2017 | B2 |
| 9628501 | Datta Ray et al. | Apr 2017 | B2 |
| 9629560 | Joseph | Apr 2017 | B2 |
| 9629623 | Lytle, IV et al. | Apr 2017 | B2 |
| 9629628 | Aranyi | Apr 2017 | B2 |
| 9629629 | Leimbach et al. | Apr 2017 | B2 |
| 9630318 | Ibarz Gabardos et al. | Apr 2017 | B2 |
| 9636188 | Gattani et al. | May 2017 | B2 |
| 9636239 | Durand et al. | May 2017 | B2 |
| 9636825 | Penn et al. | May 2017 | B2 |
| 9641596 | Unagami et al. | May 2017 | B2 |
| 9641815 | Richardson et al. | May 2017 | B2 |
| 9642620 | Baxter, III et al. | May 2017 | B2 |
| 9643022 | Mashiach et al. | May 2017 | B2 |
| 9649110 | Parihar et al. | May 2017 | B2 |
| 9649111 | Shelton, IV et al. | May 2017 | B2 |
| 9649126 | Robertson et al. | May 2017 | B2 |
| 9649169 | Cinquin et al. | May 2017 | B2 |
| 9652655 | Satish et al. | May 2017 | B2 |
| 9655616 | Aranyi | May 2017 | B2 |
| 9656092 | Golden | May 2017 | B2 |
| 9662116 | Smith et al. | May 2017 | B2 |
| 9662177 | Weir et al. | May 2017 | B2 |
| 9668729 | Williams et al. | Jun 2017 | B2 |
| 9668732 | Patel et al. | Jun 2017 | B2 |
| 9668765 | Grace et al. | Jun 2017 | B2 |
| 9671860 | Ogawa et al. | Jun 2017 | B2 |
| 9675264 | Acquista et al. | Jun 2017 | B2 |
| 9675354 | Weir et al. | Jun 2017 | B2 |
| 9681870 | Baxter, III et al. | Jun 2017 | B2 |
| 9686306 | Chizeck et al. | Jun 2017 | B2 |
| 9687230 | Leimbach et al. | Jun 2017 | B2 |
| 9690362 | Leimbach et al. | Jun 2017 | B2 |
| 9700292 | Nawana et al. | Jul 2017 | B2 |
| 9700309 | Jaworek et al. | Jul 2017 | B2 |
| 9700312 | Kostrzewski et al. | Jul 2017 | B2 |
| 9700320 | Dinardo et al. | Jul 2017 | B2 |
| 9706993 | Hessler et al. | Jul 2017 | B2 |
| 9710214 | Lin et al. | Jul 2017 | B2 |
| 9710644 | Reybok et al. | Jul 2017 | B2 |
| 9713424 | Spaide | Jul 2017 | B2 |
| 9713503 | Goldschmidt | Jul 2017 | B2 |
| 9717141 | Tegg | Jul 2017 | B1 |
| 9717498 | Aranyi et al. | Aug 2017 | B2 |
| 9717525 | Ahluwalia et al. | Aug 2017 | B2 |
| 9717548 | Couture | Aug 2017 | B2 |
| 9724094 | Baber et al. | Aug 2017 | B2 |
| 9724100 | Scheib et al. | Aug 2017 | B2 |
| 9724118 | Schulte et al. | Aug 2017 | B2 |
| 9733663 | Leimbach et al. | Aug 2017 | B2 |
| 9737301 | Baber et al. | Aug 2017 | B2 |
| 9737310 | Whitfield et al. | Aug 2017 | B2 |
| 9737335 | Butler et al. | Aug 2017 | B2 |
| 9737355 | Yates et al. | Aug 2017 | B2 |
| 9740826 | Raghavan et al. | Aug 2017 | B2 |
| 9743016 | Res 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 |
| 9750499 | Leimbach et al. | Sep 2017 | B2 |
| 9750500 | Malkowski | Sep 2017 | B2 |
| 9750522 | Scheib et al. | Sep 2017 | B2 |
| 9750523 | Tsubuku | Sep 2017 | B2 |
| 9750563 | Shikhman et al. | Sep 2017 | B2 |
| 9753135 | Bosch | Sep 2017 | B2 |
| 9753568 | McMillen | Sep 2017 | B2 |
| 9757126 | Cappola | Sep 2017 | B2 |
| 9757128 | Baber et al. | Sep 2017 | B2 |
| 9757142 | Shimizu | Sep 2017 | B2 |
| 9757152 | Ogilvie et al. | Sep 2017 | B2 |
| 9763741 | Alvarez et al. | Sep 2017 | B2 |
| 9764164 | Wiener et al. | Sep 2017 | B2 |
| 9770541 | Carr et al. | Sep 2017 | B2 |
| 9775611 | Kostrzewski | Oct 2017 | B2 |
| 9777913 | Talbert et al. | Oct 2017 | B2 |
| 9782164 | Mumaw et al. | Oct 2017 | B2 |
| 9782169 | Kimsey et al. | Oct 2017 | B2 |
| 9782212 | Wham et al. | Oct 2017 | B2 |
| 9782214 | Houser et al. | Oct 2017 | B2 |
| 9788835 | Morgan et al. | Oct 2017 | B2 |
| 9788836 | Overmyer et al. | Oct 2017 | B2 |
| 9788851 | Dannaher et al. | Oct 2017 | B2 |
| 9788902 | Inoue et al. | Oct 2017 | B2 |
| 9788907 | Alvi et al. | Oct 2017 | B1 |
| 9795436 | Yates et al. | Oct 2017 | B2 |
| 9797486 | Zergiebel et al. | Oct 2017 | B2 |
| 9801531 | Morita et al. | Oct 2017 | B2 |
| 9801626 | Parihar et al. | Oct 2017 | B2 |
| 9801627 | Harris et al. | Oct 2017 | B2 |
| 9801679 | Trees et al. | Oct 2017 | B2 |
| 9802033 | Hibner et al. | Oct 2017 | B2 |
| 9804618 | Leimbach et al. | Oct 2017 | B2 |
| 9805472 | Chou et al. | Oct 2017 | B2 |
| 9808244 | Leimbach et al. | Nov 2017 | B2 |
| 9808245 | Richard et al. | Nov 2017 | B2 |
| 9808246 | Shelton, IV et al. | Nov 2017 | B2 |
| 9808248 | Hoffman | Nov 2017 | B2 |
| 9808249 | Shelton, IV | Nov 2017 | B2 |
| 9814457 | Martin et al. | Nov 2017 | B2 |
| 9814460 | Kimsey et al. | Nov 2017 | B2 |
| 9814462 | Woodard, Jr. et al. | Nov 2017 | B2 |
| 9814463 | Williams et al. | Nov 2017 | B2 |
| 9820699 | Bingley et al. | Nov 2017 | B2 |
| 9820738 | Lytle, IV et al. | Nov 2017 | B2 |
| 9820741 | Kostrzewski | Nov 2017 | B2 |
| 9826976 | Parihar et al. | Nov 2017 | B2 |
| 9826977 | Leimbach et al. | Nov 2017 | B2 |
| 9827054 | Richmond et al. | Nov 2017 | B2 |
| 9827059 | Robinson et al. | Nov 2017 | B2 |
| 9830424 | Dixon et al. | Nov 2017 | B2 |
| 9833241 | Huitema et al. | Dec 2017 | B2 |
| 9833254 | Barral et al. | Dec 2017 | B1 |
| 9839419 | Deck et al. | Dec 2017 | B2 |
| 9839424 | Zergiebel et al. | Dec 2017 | B2 |
| 9839428 | Baxter, III et al. | Dec 2017 | B2 |
| 9839470 | Gilbert et al. | Dec 2017 | B2 |
| 9839487 | Dachs, II | Dec 2017 | B2 |
| 9844321 | Ekvall et al. | Dec 2017 | B1 |
| 9844368 | Boudreaux et al. | Dec 2017 | B2 |
| 9844369 | Huitema et al. | Dec 2017 | B2 |
| 9844374 | Lytle, IV et al. | Dec 2017 | B2 |
| 9844375 | Overmyer et al. | Dec 2017 | B2 |
| 9844376 | Baxter, III et al. | Dec 2017 | B2 |
| 9844379 | Shelton, IV et al. | Dec 2017 | B2 |
| 9848058 | Johnson et al. | Dec 2017 | B2 |
| 9848877 | Shelton, IV et al. | Dec 2017 | B2 |
| 9861354 | Saliman et al. | Jan 2018 | B2 |
| 9861363 | Chen et al. | Jan 2018 | B2 |
| 9861428 | Trees et al. | Jan 2018 | B2 |
| 9864839 | Baym et al. | Jan 2018 | B2 |
| 9867612 | Parihar et al. | Jan 2018 | B2 |
| 9867651 | Wham | Jan 2018 | B2 |
| 9867670 | Brannan et al. | Jan 2018 | B2 |
| 9867914 | Bonano et al. | Jan 2018 | B2 |
| 9872609 | Levy | Jan 2018 | B2 |
| 9872683 | Hopkins et al. | Jan 2018 | B2 |
| 9877718 | Weir et al. | Jan 2018 | B2 |
| 9877721 | Schellin et al. | Jan 2018 | B2 |
| 9883860 | Leimbach | Feb 2018 | B2 |
| 9888864 | Rondon et al. | Feb 2018 | B2 |
| 9888914 | Martin et al. | Feb 2018 | B2 |
| 9888919 | Leimbach et al. | Feb 2018 | B2 |
| 9888921 | Williams et al. | Feb 2018 | B2 |
| 9888975 | Auld | Feb 2018 | B2 |
| 9895148 | Shelton, IV et al. | Feb 2018 | B2 |
| 9900787 | Ou | Feb 2018 | B2 |
| 9901342 | Shelton, IV et al. | Feb 2018 | B2 |
| 9901406 | State et al. | Feb 2018 | B2 |
| 9905000 | Chou et al. | Feb 2018 | B2 |
| 9907196 | Susini et al. | Feb 2018 | B2 |
| 9907550 | Sniffin et al. | Mar 2018 | B2 |
| 9913642 | Leimbach et al. | Mar 2018 | B2 |
| 9913645 | Zerkle et al. | Mar 2018 | B2 |
| 9918730 | Trees et al. | Mar 2018 | B2 |
| 9918778 | Walberg et al. | Mar 2018 | B2 |
| 9918788 | Paul et al. | Mar 2018 | B2 |
| 9922304 | DeBusk et al. | Mar 2018 | B2 |
| 9924941 | Burbank | Mar 2018 | B2 |
| 9924944 | Shelton, IV et al. | Mar 2018 | B2 |
| 9924961 | Shelton, IV et al. | Mar 2018 | B2 |
| 9931040 | Homyk et al. | Apr 2018 | B2 |
| 9931118 | Shelton, IV et al. | Apr 2018 | B2 |
| 9931124 | Gokharu | Apr 2018 | B2 |
| 9936863 | Tesar | Apr 2018 | B2 |
| 9936942 | Chin et al. | Apr 2018 | B2 |
| 9936955 | Miller et al. | Apr 2018 | B2 |
| 9936961 | Chien et al. | Apr 2018 | B2 |
| 9937012 | Hares et al. | Apr 2018 | B2 |
| 9937014 | Bowling et al. | Apr 2018 | B2 |
| 9937626 | Rockrohr | Apr 2018 | B2 |
| 9938972 | Walley | Apr 2018 | B2 |
| 9943230 | Kaku et al. | Apr 2018 | B2 |
| 9943309 | Shelton, IV et al. | Apr 2018 | B2 |
| 9943312 | Posada et al. | Apr 2018 | B2 |
| 9943377 | Yates et al. | Apr 2018 | B2 |
| 9943379 | Gregg, II et al. | Apr 2018 | B2 |
| 9943918 | Grogan et al. | Apr 2018 | B2 |
| 9949785 | Price et al. | Apr 2018 | B2 |
| 9962157 | Sapre | May 2018 | B2 |
| 9968355 | Shelton, IV et al. | May 2018 | B2 |
| 9974595 | Anderson et al. | May 2018 | B2 |
| 9980140 | Spencer et al. | May 2018 | B1 |
| 9980769 | Trees et al. | May 2018 | B2 |
| 9980778 | Ohline et al. | May 2018 | B2 |
| 9987000 | Shelton, IV et al. | Jun 2018 | B2 |
| 9987068 | Anderson et al. | Jun 2018 | B2 |
| 9987072 | McPherson | Jun 2018 | B2 |
| 9990856 | Kuchenbecker et al. | Jun 2018 | B2 |
| 9993248 | Shelton, IV et al. | Jun 2018 | B2 |
| 9993258 | Shelton, IV et al. | Jun 2018 | B2 |
| 9993305 | Andersson | Jun 2018 | B2 |
| 10004491 | Martin et al. | Jun 2018 | B2 |
| 10004497 | Overmyer et al. | Jun 2018 | B2 |
| 10004500 | Shelton, IV et al. | Jun 2018 | B2 |
| 10004501 | Shelton, IV et al. | Jun 2018 | B2 |
| 10004527 | Gee et al. | Jun 2018 | B2 |
| 10004557 | Gross | Jun 2018 | B2 |
| D822206 | Shelton, IV et al. | Jul 2018 | S |
| 10010322 | Shelton, IV et al. | Jul 2018 | B2 |
| 10010324 | Huitema et al. | Jul 2018 | B2 |
| 10013049 | Leimbach et al. | Jul 2018 | B2 |
| 10016199 | Baber et al. | Jul 2018 | B2 |
| 10021318 | Hugosson et al. | Jul 2018 | B2 |
| 10022090 | Whitman | Jul 2018 | B2 |
| 10022120 | Martin et al. | Jul 2018 | B2 |
| 10022391 | Ruderman Chen et al. | Jul 2018 | B2 |
| 10022568 | Messerly et al. | Jul 2018 | B2 |
| 10028402 | Walker | Jul 2018 | B1 |
| 10028744 | Shelton, IV et al. | Jul 2018 | B2 |
| 10028761 | Leimbach et al. | Jul 2018 | B2 |
| 10028788 | Kang | Jul 2018 | B2 |
| 10034704 | Asher et al. | Jul 2018 | B2 |
| 10037641 | Hyde et al. | Jul 2018 | B2 |
| 10037715 | Toly et al. | Jul 2018 | B2 |
| D826405 | Shelton, IV et al. | Aug 2018 | S |
| 10039546 | Williams et al. | Aug 2018 | B2 |
| 10039564 | Hibner et al. | Aug 2018 | B2 |
| 10039565 | Vezzu | Aug 2018 | B2 |
| 10039589 | Virshek et al. | Aug 2018 | B2 |
| 10041822 | Zemlok | Aug 2018 | B2 |
| 10044791 | Kamen et al. | Aug 2018 | B2 |
| 10045704 | Fagin et al. | Aug 2018 | B2 |
| 10045776 | Shelton, IV et al. | Aug 2018 | B2 |
| 10045779 | Savage et al. | Aug 2018 | B2 |
| 10045781 | Cropper et al. | Aug 2018 | B2 |
| 10045782 | Murthy Aravalli | Aug 2018 | B2 |
| 10045813 | Mueller | Aug 2018 | B2 |
| 10048379 | Markendorf et al. | Aug 2018 | B2 |
| 10052044 | Shelton, IV et al. | Aug 2018 | B2 |
| 10052102 | Baxter, III et al. | Aug 2018 | B2 |
| 10052104 | Shelton, IV et al. | Aug 2018 | B2 |
| 10054441 | Schorr et al. | Aug 2018 | B2 |
| 10058393 | Bonutti et al. | Aug 2018 | B2 |
| 10069633 | Gulati et al. | Sep 2018 | B2 |
| 10076326 | Yates et al. | Sep 2018 | B2 |
| 10080618 | Marshall et al. | Sep 2018 | B2 |
| 10084833 | McDonnell et al. | Sep 2018 | B2 |
| D831209 | Huitema et al. | Oct 2018 | S |
| 10085748 | Morgan et al. | Oct 2018 | B2 |
| 10085749 | Cappola et al. | Oct 2018 | B2 |
| 10092355 | Hannaford et al. | Oct 2018 | B1 |
| 10095942 | Mentese et al. | Oct 2018 | B2 |
| 10097578 | Baldonado et al. | Oct 2018 | B2 |
| 10098527 | Weisenburgh, II et al. | Oct 2018 | B2 |
| 10098635 | Burbank | Oct 2018 | B2 |
| 10098642 | Baxter, III et al. | Oct 2018 | B2 |
| 10098705 | Brisson et al. | Oct 2018 | B2 |
| 10102926 | Leonardi | Oct 2018 | B1 |
| 10105140 | Malinouskas et al. | Oct 2018 | B2 |
| 10105142 | Baxter, III et al. | Oct 2018 | B2 |
| 10105470 | Reasoner et al. | Oct 2018 | B2 |
| 10111658 | Chowaniec et al. | Oct 2018 | B2 |
| 10111665 | Aranyi et al. | Oct 2018 | B2 |
| 10111679 | Baber et al. | Oct 2018 | B2 |
| D834541 | You et al. | Nov 2018 | S |
| 10117649 | Baxter et al. | Nov 2018 | B2 |
| 10117651 | Whitman et al. | Nov 2018 | B2 |
| 10117702 | Danziger et al. | Nov 2018 | B2 |
| 10118119 | Sappok et al. | Nov 2018 | B2 |
| 10130359 | Hess et al. | Nov 2018 | B2 |
| 10130360 | Olson et al. | Nov 2018 | B2 |
| 10130361 | Yates et al. | Nov 2018 | B2 |
| 10130367 | Cappola et al. | Nov 2018 | B2 |
| 10133248 | Fitzsimmons et al. | Nov 2018 | B2 |
| 10135242 | Baber et al. | Nov 2018 | B2 |
| 10136887 | Shelton, IV et al. | Nov 2018 | B2 |
| 10136891 | Shelton, IV et al. | Nov 2018 | B2 |
| 10136949 | Felder et al. | Nov 2018 | B2 |
| 10136954 | Johnson et al. | Nov 2018 | B2 |
| 10137245 | Melker et al. | Nov 2018 | B2 |
| 10143526 | Walker et al. | Dec 2018 | B2 |
| 10143948 | Bonitas et al. | Dec 2018 | B2 |
| 10147148 | Wu et al. | Dec 2018 | B2 |
| 10149680 | Parihar et al. | Dec 2018 | B2 |
| 10152789 | Carnes et al. | Dec 2018 | B2 |
| 10154841 | Weaner et al. | Dec 2018 | B2 |
| 10159044 | Hrabak | Dec 2018 | B2 |
| 10159481 | Whitman et al. | Dec 2018 | B2 |
| 10159483 | Beckman et al. | Dec 2018 | B2 |
| 10164466 | Calderoni | Dec 2018 | B2 |
| 10166025 | Leimbach et al. | Jan 2019 | B2 |
| 10166061 | Berry et al. | Jan 2019 | B2 |
| 10169862 | Andre et al. | Jan 2019 | B2 |
| 10172618 | Shelton, IV et al. | Jan 2019 | B2 |
| 10172687 | Garbus et al. | Jan 2019 | B2 |
| 10175096 | Dickerson | Jan 2019 | B2 |
| 10175127 | Collins et al. | Jan 2019 | B2 |
| 10178992 | Wise et al. | Jan 2019 | B2 |
| 10179413 | Rockrohr | Jan 2019 | B2 |
| 10180463 | Beckman et al. | Jan 2019 | B2 |
| 10182814 | Okoniewski | Jan 2019 | B2 |
| 10182816 | Shelton, IV et al. | Jan 2019 | B2 |
| 10182818 | Hensel et al. | Jan 2019 | B2 |
| 10188385 | Kerr et al. | Jan 2019 | B2 |
| 10189157 | Schlegel et al. | Jan 2019 | B2 |
| 10190888 | Hryb et al. | Jan 2019 | B2 |
| 10194891 | Jeong et al. | Feb 2019 | B2 |
| 10194907 | Marczyk et al. | Feb 2019 | B2 |
| 10194913 | Nalagatla et al. | Feb 2019 | B2 |
| 10194972 | Yates et al. | Feb 2019 | B2 |
| 10197803 | Badiali et al. | Feb 2019 | B2 |
| 10198965 | Hart | Feb 2019 | B2 |
| 10201311 | Chou et al. | Feb 2019 | B2 |
| 10201349 | Leimbach et al. | Feb 2019 | B2 |
| 10201364 | Leimbach et al. | Feb 2019 | B2 |
| 10201365 | Boudreaux et al. | Feb 2019 | B2 |
| 10205708 | Fletcher et al. | Feb 2019 | B1 |
| 10206605 | Shelton, IV et al. | Feb 2019 | B2 |
| 10206752 | Hares et al. | Feb 2019 | B2 |
| 10213201 | Shelton, IV et al. | Feb 2019 | B2 |
| 10213203 | Swayze et al. | Feb 2019 | B2 |
| 10213266 | Zemlok et al. | Feb 2019 | B2 |
| 10213268 | Dachs, II | Feb 2019 | B2 |
| 10219491 | Stiles, Jr. et al. | Mar 2019 | B2 |
| 10220522 | Rockrohr | Mar 2019 | B2 |
| 10222750 | Bang et al. | Mar 2019 | B2 |
| 10226249 | Jaworek et al. | Mar 2019 | B2 |
| 10226250 | Beckman et al. | Mar 2019 | B2 |
| 10226302 | Lacal et al. | Mar 2019 | B2 |
| 10231634 | Zand et al. | Mar 2019 | B2 |
| 10231733 | Ehrenfels et al. | Mar 2019 | B2 |
| 10231775 | Shelton, IV et al. | Mar 2019 | B2 |
| 10238413 | Hibner et al. | Mar 2019 | B2 |
| 10245027 | Shelton, IV et al. | Apr 2019 | B2 |
| 10245028 | Shelton, IV et al. | Apr 2019 | B2 |
| 10245029 | Hunter et al. | Apr 2019 | B2 |
| 10245030 | Hunter et al. | Apr 2019 | B2 |
| 10245033 | Overmyer et al. | Apr 2019 | B2 |
| 10245037 | Conklin et al. | Apr 2019 | B2 |
| 10245038 | Hopkins et al. | Apr 2019 | B2 |
| 10251661 | Collings et al. | Apr 2019 | B2 |
| 10251725 | Valentine et al. | Apr 2019 | B2 |
| 10258331 | Shelton, IV et al. | Apr 2019 | B2 |
| 10258359 | Kapadia | Apr 2019 | B2 |
| 10258362 | Conlon | Apr 2019 | B2 |
| 10258363 | Worrell et al. | Apr 2019 | B2 |
| 10258415 | Harrah et al. | Apr 2019 | B2 |
| 10258418 | Shelton, IV et al. | Apr 2019 | B2 |
| 10258425 | Mustufa et al. | Apr 2019 | B2 |
| 10263171 | Wiener et al. | Apr 2019 | B2 |
| 10265035 | Fehre et al. | Apr 2019 | B2 |
| 10265068 | Harris et al. | Apr 2019 | B2 |
| 10265072 | Shelton, IV et al. | Apr 2019 | B2 |
| 10265090 | Ingmanson et al. | Apr 2019 | B2 |
| 10265130 | Hess et al. | Apr 2019 | B2 |
| 10271840 | Sapre | Apr 2019 | B2 |
| 10271844 | Valentine et al. | Apr 2019 | B2 |
| 10271850 | Williams | Apr 2019 | B2 |
| 10271851 | Shelton, IV et al. | Apr 2019 | B2 |
| D847989 | Shelton, IV et al. | May 2019 | S |
| 10278698 | Racenet | May 2019 | B2 |
| 10278778 | State et al. | May 2019 | B2 |
| 10283220 | Azizian et al. | May 2019 | B2 |
| 10285694 | Viola et al. | May 2019 | B2 |
| 10285698 | Cappola et al. | May 2019 | B2 |
| 10285700 | Scheib | May 2019 | B2 |
| 10285705 | Shelton, IV et al. | May 2019 | B2 |
| 10292704 | Harris et al. | May 2019 | B2 |
| 10292707 | Shelton, IV et al. | May 2019 | B2 |
| 10292758 | Boudreaux et al. | May 2019 | B2 |
| 10292771 | Wood et al. | May 2019 | B2 |
| 10293129 | Fox et al. | May 2019 | B2 |
| 10299792 | Huitema et al. | May 2019 | B2 |
| 10299870 | Connolly et al. | May 2019 | B2 |
| 10305926 | Mihan et al. | May 2019 | B2 |
| D850617 | Shelton, IV et al. | Jun 2019 | S |
| 10307159 | Harris et al. | Jun 2019 | B2 |
| 10307170 | Parfett et al. | Jun 2019 | B2 |
| 10307199 | Farritor et al. | Jun 2019 | B2 |
| 10311036 | Hussam et al. | Jun 2019 | B1 |
| 10313137 | Aarnio et al. | Jun 2019 | B2 |
| 10314577 | Laurent et al. | Jun 2019 | B2 |
| 10314582 | Shelton, IV et al. | Jun 2019 | B2 |
| 10321907 | Shelton, IV et al. | Jun 2019 | B2 |
| 10321964 | Grover et al. | Jun 2019 | B2 |
| 10327764 | Harris et al. | Jun 2019 | B2 |
| 10335147 | Rector et al. | Jul 2019 | B2 |
| 10335149 | Baxter, III et al. | Jul 2019 | B2 |
| 10335180 | Johnson et al. | Jul 2019 | B2 |
| 10335227 | Heard | Jul 2019 | B2 |
| 10339496 | Matson et al. | Jul 2019 | B2 |
| 10342543 | Shelton, IV et al. | Jul 2019 | B2 |
| 10342602 | Strobl et al. | Jul 2019 | B2 |
| 10342623 | Huelman et al. | Jul 2019 | B2 |
| 10343102 | Reasoner et al. | Jul 2019 | B2 |
| 10349824 | Claude et al. | Jul 2019 | B2 |
| 10349939 | Shelton, IV et al. | Jul 2019 | B2 |
| 10349941 | Marczyk et al. | Jul 2019 | B2 |
| 10350016 | Burbank et al. | Jul 2019 | B2 |
| 10357184 | Crawford et al. | Jul 2019 | B2 |
| 10357246 | Shelton, IV et al. | Jul 2019 | B2 |
| 10357247 | Shelton, IV et al. | Jul 2019 | B2 |
| 10362179 | Harris | Jul 2019 | B2 |
| 10363032 | Scheib et al. | Jul 2019 | B2 |
| 10363037 | Aronhalt et al. | Jul 2019 | B2 |
| 10368861 | Baxter, III et al. | Aug 2019 | B2 |
| 10368865 | Harris et al. | Aug 2019 | B2 |
| 10368867 | Harris et al. | Aug 2019 | B2 |
| 10368876 | Bhatnagar et al. | Aug 2019 | B2 |
| 10368894 | Madan et al. | Aug 2019 | B2 |
| 10368903 | Morales et al. | Aug 2019 | B2 |
| 10376263 | Morgan et al. | Aug 2019 | B2 |
| 10376305 | Yates et al. | Aug 2019 | B2 |
| 10376337 | Kilroy et al. | Aug 2019 | B2 |
| 10376338 | Taylor et al. | Aug 2019 | B2 |
| 10378893 | Mankovskii | Aug 2019 | B2 |
| 10383518 | Abu-Tarif et al. | Aug 2019 | B2 |
| 10383699 | Kilroy et al. | Aug 2019 | B2 |
| 10384021 | Koeth et al. | Aug 2019 | B2 |
| 10386990 | Shikhman et al. | Aug 2019 | B2 |
| 10390718 | Chen et al. | Aug 2019 | B2 |
| 10390794 | Kuroiwa et al. | Aug 2019 | B2 |
| 10390825 | Shelton, IV et al. | Aug 2019 | B2 |
| 10390831 | Holsten et al. | Aug 2019 | B2 |
| 10390895 | Henderson et al. | Aug 2019 | B2 |
| 10398348 | Osadchy et al. | Sep 2019 | B2 |
| 10398434 | Shelton, IV et al. | Sep 2019 | B2 |
| 10398517 | Eckert et al. | Sep 2019 | B2 |
| 10398521 | Itkowitz et al. | Sep 2019 | B2 |
| 10404521 | McChord et al. | Sep 2019 | B2 |
| 10404801 | Martch | Sep 2019 | B2 |
| 10405857 | Shelton, IV et al. | Sep 2019 | B2 |
| 10405863 | Wise et al. | Sep 2019 | B2 |
| 10413291 | Worthington et al. | Sep 2019 | B2 |
| 10413293 | Shelton, IV et al. | Sep 2019 | B2 |
| 10413297 | Harris et al. | Sep 2019 | B2 |
| 10417446 | Takeyama | Sep 2019 | B2 |
| 10420552 | Shelton, IV et al. | Sep 2019 | B2 |
| 10420558 | Nalagatla et al. | Sep 2019 | B2 |
| 10420559 | Marczyk et al. | Sep 2019 | B2 |
| 10420620 | Rockrohr | Sep 2019 | B2 |
| 10420865 | Reasoner et al. | Sep 2019 | B2 |
| 10422727 | Pliskin | Sep 2019 | B2 |
| 10426466 | Contini et al. | Oct 2019 | B2 |
| 10426467 | Miller et al. | Oct 2019 | B2 |
| 10426468 | Contini et al. | Oct 2019 | B2 |
| 10426471 | Shelton, IV et al. | Oct 2019 | B2 |
| 10426481 | Aronhalt et al. | Oct 2019 | B2 |
| 10433837 | Worthington et al. | Oct 2019 | B2 |
| 10433844 | Shelton, IV et al. | Oct 2019 | B2 |
| 10433849 | Shelton, IV et al. | Oct 2019 | B2 |
| 10433918 | Shelton, IV et al. | Oct 2019 | B2 |
| 10441279 | Shelton, IV et al. | Oct 2019 | B2 |
| 10441345 | Aldridge et al. | Oct 2019 | B2 |
| 10448948 | Shelton, IV et al. | Oct 2019 | B2 |
| 10448950 | Shelton, IV et al. | Oct 2019 | B2 |
| 10456137 | Vendely et al. | Oct 2019 | B2 |
| 10456140 | Shelton, IV et al. | Oct 2019 | B2 |
| 10456193 | Yates et al. | Oct 2019 | B2 |
| 10463365 | Williams | Nov 2019 | B2 |
| 10463367 | Kostrzewski et al. | Nov 2019 | B2 |
| 10463371 | Kostrzewski | Nov 2019 | B2 |
| 10463436 | Jackson et al. | Nov 2019 | B2 |
| 10470762 | Leimbach et al. | Nov 2019 | B2 |
| 10470764 | Baxter, III et al. | Nov 2019 | B2 |
| 10470768 | Harris et al. | Nov 2019 | B2 |
| 10470791 | Houser | Nov 2019 | B2 |
| 10471254 | Sano et al. | Nov 2019 | B2 |
| 10478181 | Shelton, IV et al. | Nov 2019 | B2 |
| 10478185 | Nicholas | Nov 2019 | B2 |
| 10478189 | Bear et al. | Nov 2019 | B2 |
| 10478190 | Miller et al. | Nov 2019 | B2 |
| 10478544 | Friederichs et al. | Nov 2019 | B2 |
| 10485450 | Gupta et al. | Nov 2019 | B2 |
| 10485542 | Shelton, IV et al. | Nov 2019 | B2 |
| 10485543 | Shelton, IV et al. | Nov 2019 | B2 |
| 10492783 | Shelton, IV et al. | Dec 2019 | B2 |
| 10492784 | Beardsley et al. | Dec 2019 | B2 |
| 10492785 | Overmyer et al. | Dec 2019 | B2 |
| 10496788 | Amarasingham et al. | Dec 2019 | B2 |
| 10498269 | Zemlok et al. | Dec 2019 | B2 |
| 10499847 | Latimer et al. | Dec 2019 | B2 |
| 10499891 | Chaplin et al. | Dec 2019 | B2 |
| 10499914 | Huang et al. | Dec 2019 | B2 |
| 10499915 | Aranyi | Dec 2019 | B2 |
| 10499994 | Luks et al. | Dec 2019 | B2 |
| 10507068 | Kopp et al. | Dec 2019 | B2 |
| 10512461 | Gupta et al. | Dec 2019 | B2 |
| 10512499 | McHenry et al. | Dec 2019 | B2 |
| 10512514 | Nowlin et al. | Dec 2019 | B2 |
| 10517588 | Gupta et al. | Dec 2019 | B2 |
| 10517595 | Hunter et al. | Dec 2019 | B2 |
| 10517596 | Hunter et al. | Dec 2019 | B2 |
| 10517686 | Vokrot et al. | Dec 2019 | B2 |
| 10524789 | Swayze et al. | Jan 2020 | B2 |
| 10531579 | Hsiao et al. | Jan 2020 | B2 |
| 10531874 | Morgan et al. | Jan 2020 | B2 |
| 10531929 | Widenhouse et al. | Jan 2020 | B2 |
| 10532330 | Diallo et al. | Jan 2020 | B2 |
| 10536617 | Liang et al. | Jan 2020 | B2 |
| 10537324 | Shelton, IV et al. | Jan 2020 | B2 |
| 10537325 | Bakos et al. | Jan 2020 | B2 |
| 10537351 | Shelton, IV et al. | Jan 2020 | B2 |
| 10542978 | Chowaniec et al. | Jan 2020 | B2 |
| 10542979 | Shelton, IV et al. | Jan 2020 | B2 |
| 10542982 | Beckman et al. | Jan 2020 | B2 |
| 10542991 | Shelton, IV et al. | Jan 2020 | B2 |
| D876466 | Kobayashi et al. | Feb 2020 | S |
| 10548504 | Shelton, IV et al. | Feb 2020 | B2 |
| 10548612 | Martinez et al. | Feb 2020 | B2 |
| 10548673 | Harris et al. | Feb 2020 | B2 |
| 10552574 | Sweeney | Feb 2020 | B2 |
| 10555675 | Satish et al. | Feb 2020 | B2 |
| 10555748 | Yates et al. | Feb 2020 | B2 |
| 10555750 | Conlon et al. | Feb 2020 | B2 |
| 10555769 | Worrell et al. | Feb 2020 | B2 |
| 10561422 | Schellin et al. | Feb 2020 | B2 |
| 10561471 | Nichogi | Feb 2020 | B2 |
| 10561753 | Thompson et al. | Feb 2020 | B2 |
| 10568625 | Harris et al. | Feb 2020 | B2 |
| 10568626 | Shelton, IV et al. | Feb 2020 | B2 |
| 10568632 | Miller et al. | Feb 2020 | B2 |
| 10568704 | Savall et al. | Feb 2020 | B2 |
| 10575868 | Hall et al. | Mar 2020 | B2 |
| 10582928 | Hunter et al. | Mar 2020 | B2 |
| 10582931 | Mujawar | Mar 2020 | B2 |
| 10582964 | Weinberg et al. | Mar 2020 | B2 |
| 10586074 | Rose et al. | Mar 2020 | B2 |
| 10588625 | Weaner et al. | Mar 2020 | B2 |
| 10588629 | Malinouskas et al. | Mar 2020 | B2 |
| 10588630 | Shelton, IV et al. | Mar 2020 | B2 |
| 10588631 | Shelton, IV et al. | Mar 2020 | B2 |
| 10588632 | Shelton, IV et al. | Mar 2020 | B2 |
| 10588711 | DiCarlo et al. | Mar 2020 | B2 |
| 10592067 | Merdan et al. | Mar 2020 | B2 |
| 10595844 | Nawana et al. | Mar 2020 | B2 |
| 10595882 | Parfett et al. | Mar 2020 | B2 |
| 10595887 | Shelton, IV et al. | Mar 2020 | B2 |
| 10595930 | Scheib et al. | Mar 2020 | B2 |
| 10595952 | Forrest et al. | Mar 2020 | B2 |
| 10602007 | Takano | Mar 2020 | B2 |
| 10602848 | Magana | Mar 2020 | B2 |
| 10603036 | Hunter et al. | Mar 2020 | B2 |
| 10603128 | Zergiebel et al. | Mar 2020 | B2 |
| 10610223 | Wellman et al. | Apr 2020 | B2 |
| 10610224 | Shelton, IV et al. | Apr 2020 | B2 |
| 10610286 | Wiener et al. | Apr 2020 | B2 |
| 10610313 | Bailey et al. | Apr 2020 | B2 |
| 10617412 | Shelton, IV et al. | Apr 2020 | B2 |
| 10617414 | Shelton, IV et al. | Apr 2020 | B2 |
| 10617482 | Houser et al. | Apr 2020 | B2 |
| 10617484 | Kilroy et al. | Apr 2020 | B2 |
| 10624635 | Harris et al. | Apr 2020 | B2 |
| 10624667 | Faller et al. | Apr 2020 | B2 |
| 10624691 | Wiener et al. | Apr 2020 | B2 |
| 10631423 | Collins et al. | Apr 2020 | B2 |
| 10631858 | Burbank | Apr 2020 | B2 |
| 10631912 | McFarlin et al. | Apr 2020 | B2 |
| 10631916 | Horner et al. | Apr 2020 | B2 |
| 10631917 | Ineson | Apr 2020 | B2 |
| 10631939 | Dachs, II et al. | Apr 2020 | B2 |
| 10639027 | Shelton, IV et al. | May 2020 | B2 |
| 10639034 | Harris et al. | May 2020 | B2 |
| 10639035 | Shelton, IV et al. | May 2020 | B2 |
| 10639036 | Yates et al. | May 2020 | B2 |
| 10639037 | Shelton, IV et al. | May 2020 | B2 |
| 10639039 | Vendely et al. | May 2020 | B2 |
| 10639098 | Cosman et al. | May 2020 | B2 |
| 10639111 | Kopp | May 2020 | B2 |
| 10639185 | Agrawal et al. | May 2020 | B2 |
| 10653413 | Worthington et al. | May 2020 | B2 |
| 10653476 | Ross | May 2020 | B2 |
| 10653489 | Kopp | May 2020 | B2 |
| 10656720 | Holz | May 2020 | B1 |
| 10660705 | Piron et al. | May 2020 | B2 |
| 10667809 | Bakos et al. | Jun 2020 | B2 |
| 10667810 | Shelton, IV et al. | Jun 2020 | B2 |
| 10667811 | Harris et al. | Jun 2020 | B2 |
| 10667877 | Kapadia | Jun 2020 | B2 |
| 10674897 | Levy | Jun 2020 | B2 |
| 10675021 | Harris et al. | Jun 2020 | B2 |
| 10675023 | Cappola | Jun 2020 | B2 |
| 10675024 | Shelton, IV et al. | Jun 2020 | B2 |
| 10675025 | Swayze et al. | Jun 2020 | B2 |
| 10675026 | Harris et al. | Jun 2020 | B2 |
| 10675035 | Zingman | Jun 2020 | B2 |
| 10675100 | Frushour | Jun 2020 | B2 |
| 10675104 | Kapadia | Jun 2020 | B2 |
| 10677764 | Ross et al. | Jun 2020 | B2 |
| 10679758 | Fox et al. | Jun 2020 | B2 |
| 10682136 | Harris et al. | Jun 2020 | B2 |
| 10682138 | Shelton, IV et al. | Jun 2020 | B2 |
| 10686805 | Reybok, Jr. et al. | Jun 2020 | B2 |
| 10687806 | Shelton, IV et al. | Jun 2020 | B2 |
| 10687809 | Shelton, IV et al. | Jun 2020 | B2 |
| 10687810 | Shelton, IV et al. | Jun 2020 | B2 |
| 10687884 | Wiener et al. | Jun 2020 | B2 |
| 10687905 | Kostrzewski | Jun 2020 | B2 |
| 10695055 | Shelton, IV et al. | Jun 2020 | B2 |
| 10695081 | Shelton, IV et al. | Jun 2020 | B2 |
| 10695134 | Barral et al. | Jun 2020 | B2 |
| 10702270 | Shelton, IV et al. | Jul 2020 | B2 |
| 10702271 | Aranyi et al. | Jul 2020 | B2 |
| 10709446 | Harris et al. | Jul 2020 | B2 |
| 10716489 | Kalvoy et al. | Jul 2020 | B2 |
| 10716615 | Shelton, IV et al. | Jul 2020 | B2 |
| 10716639 | Kapadia et al. | Jul 2020 | B2 |
| 10717194 | Griffiths et al. | Jul 2020 | B2 |
| 10722222 | Aranyi | Jul 2020 | B2 |
| 10722233 | Wellman | Jul 2020 | B2 |
| 10722292 | Arya et al. | Jul 2020 | B2 |
| D893717 | Messerly et al. | Aug 2020 | S |
| 10729458 | Stoddard et al. | Aug 2020 | B2 |
| 10729509 | Shelton, IV et al. | Aug 2020 | B2 |
| 10733267 | Pedersen | Aug 2020 | B2 |
| 10736219 | Seow et al. | Aug 2020 | B2 |
| 10736616 | Scheib et al. | Aug 2020 | B2 |
| 10736628 | Yates et al. | Aug 2020 | B2 |
| 10736629 | Shelton, IV et al. | Aug 2020 | B2 |
| 10736636 | Baxter, III et al. | Aug 2020 | B2 |
| 10736705 | Scheib et al. | Aug 2020 | B2 |
| 10743872 | Leimbach et al. | Aug 2020 | B2 |
| 10748115 | Laster et al. | Aug 2020 | B2 |
| 10751052 | Stokes et al. | Aug 2020 | B2 |
| 10751136 | Farritor et al. | Aug 2020 | B2 |
| 10751768 | Hersey et al. | Aug 2020 | B2 |
| 10755813 | Shelton, IV et al. | Aug 2020 | B2 |
| D896379 | Shelton, IV et al. | Sep 2020 | S |
| 10758229 | Shelton, IV et al. | Sep 2020 | B2 |
| 10758230 | Shelton, IV et al. | Sep 2020 | B2 |
| 10758294 | Jones | Sep 2020 | B2 |
| 10758310 | Shelton, IV et al. | Sep 2020 | B2 |
| 10765376 | Brown, III et al. | Sep 2020 | B2 |
| 10765424 | Baxter, III et al. | Sep 2020 | B2 |
| 10765427 | Shelton, IV et al. | Sep 2020 | B2 |
| 10765470 | Yates et al. | Sep 2020 | B2 |
| 10772630 | Wixey | Sep 2020 | B2 |
| 10772651 | Shelton, IV et al. | Sep 2020 | B2 |
| 10772673 | Allen, IV et al. | Sep 2020 | B2 |
| 10772688 | Peine et al. | Sep 2020 | B2 |
| 10779818 | Zemlok et al. | Sep 2020 | B2 |
| 10779821 | Harris et al. | Sep 2020 | B2 |
| 10779823 | Shelton, IV et al. | Sep 2020 | B2 |
| 10779897 | Rockrohr | Sep 2020 | B2 |
| 10779900 | Pedros et al. | Sep 2020 | B2 |
| 10783634 | Nye et al. | Sep 2020 | B2 |
| 10786298 | Johnson | Sep 2020 | B2 |
| 10786317 | Zhou et al. | Sep 2020 | B2 |
| 10786327 | Anderson et al. | Sep 2020 | B2 |
| 10792038 | Becerra et al. | Oct 2020 | B2 |
| 10792118 | Prpa et al. | Oct 2020 | B2 |
| 10792422 | Douglas et al. | Oct 2020 | B2 |
| 10799304 | Kapadia et al. | Oct 2020 | B2 |
| 10803977 | Sanmugalingham | Oct 2020 | B2 |
| 10806445 | Penna et al. | Oct 2020 | B2 |
| 10806453 | Chen et al. | Oct 2020 | B2 |
| 10806454 | Kopp | Oct 2020 | B2 |
| 10806506 | Gaspredes et al. | Oct 2020 | B2 |
| 10806532 | Grubbs et al. | Oct 2020 | B2 |
| 10813638 | Shelton, IV et al. | Oct 2020 | B2 |
| 10813703 | Swayze et al. | Oct 2020 | B2 |
| 10818383 | Sharifi Sedeh et al. | Oct 2020 | B2 |
| 10828028 | Harris et al. | Nov 2020 | B2 |
| 10828030 | Weir et al. | Nov 2020 | B2 |
| 10835245 | Swayze et al. | Nov 2020 | B2 |
| 10835246 | Shelton, IV et al. | Nov 2020 | B2 |
| 10835247 | Shelton, IV et al. | Nov 2020 | B2 |
| 10842473 | Scheib et al. | Nov 2020 | B2 |
| 10842490 | DiNardo et al. | Nov 2020 | B2 |
| 10842492 | Shelton, IV et al. | Nov 2020 | B2 |
| 10842522 | Messerly et al. | Nov 2020 | B2 |
| 10842523 | Shelton, IV et al. | Nov 2020 | B2 |
| 10842575 | Panescu et al. | Nov 2020 | B2 |
| 10842897 | Schwartz et al. | Nov 2020 | B2 |
| D904612 | Wynn et al. | Dec 2020 | S |
| 10849697 | Yates et al. | Dec 2020 | B2 |
| 10849700 | Kopp et al. | Dec 2020 | B2 |
| 10856768 | Osadchy et al. | Dec 2020 | B2 |
| 10856867 | Shelton, IV et al. | Dec 2020 | B2 |
| 10856868 | Shelton, IV et al. | Dec 2020 | B2 |
| 10856870 | Harris et al. | Dec 2020 | B2 |
| 10863984 | Shelton, IV et al. | Dec 2020 | B2 |
| 10864037 | Mun et al. | Dec 2020 | B2 |
| 10864050 | Tabandeh et al. | Dec 2020 | B2 |
| 10872684 | McNutt et al. | Dec 2020 | B2 |
| 10881399 | Shelton, IV et al. | Jan 2021 | B2 |
| 10881401 | Baber et al. | Jan 2021 | B2 |
| 10881446 | Strobl | Jan 2021 | B2 |
| 10881464 | Odermatt et al. | Jan 2021 | B2 |
| 10888321 | Shelton, IV et al. | Jan 2021 | B2 |
| 10888322 | Morgan et al. | Jan 2021 | B2 |
| 10892899 | Shelton, IV et al. | Jan 2021 | B2 |
| 10892995 | Shelton, IV et al. | Jan 2021 | B2 |
| 10893863 | Shelton, IV et al. | Jan 2021 | B2 |
| 10893864 | Harris et al. | Jan 2021 | B2 |
| 10893884 | Stoddard et al. | Jan 2021 | B2 |
| 10898183 | Shelton, IV et al. | Jan 2021 | B2 |
| 10898186 | Bakos et al. | Jan 2021 | B2 |
| 10898189 | McDonald, II | Jan 2021 | B2 |
| 10898256 | Yates et al. | Jan 2021 | B2 |
| 10898280 | Kopp | Jan 2021 | B2 |
| 10898622 | Shelton, IV et al. | Jan 2021 | B2 |
| 10902944 | Casey et al. | Jan 2021 | B1 |
| 10903685 | Yates et al. | Jan 2021 | B2 |
| 10905415 | DiNardo et al. | Feb 2021 | B2 |
| 10905418 | Shelton, IV et al. | Feb 2021 | B2 |
| 10905420 | Jasemian et al. | Feb 2021 | B2 |
| 10912559 | Harris et al. | Feb 2021 | B2 |
| 10912580 | Green et al. | Feb 2021 | B2 |
| 10912619 | Jarc et al. | Feb 2021 | B2 |
| D914878 | Shelton, IV et al. | Mar 2021 | S |
| 10932784 | Mozdzierz et al. | Mar 2021 | B2 |
| 10950982 | Regnier et al. | Mar 2021 | B2 |
| 11000276 | Shelton, IV et al. | May 2021 | B2 |
| 11051817 | Shelton, IV et al. | Jul 2021 | B2 |
| 11058501 | Tokarchuk et al. | Jul 2021 | B2 |
| 20020049551 | Friedman | Apr 2002 | A1 |
| 20020052616 | Wiener et al. | May 2002 | A1 |
| 20020072746 | Lingenfelder et al. | Jun 2002 | A1 |
| 20020138642 | Miyazawa et al. | Sep 2002 | A1 |
| 20030009111 | Cory et al. | Jan 2003 | A1 |
| 20030018329 | Hooven | Jan 2003 | A1 |
| 20030069573 | Kadhiresan et al. | Apr 2003 | A1 |
| 20030093503 | Yamaki et al. | May 2003 | A1 |
| 20030114851 | Truckai et al. | Jun 2003 | A1 |
| 20030130711 | Pearson et al. | Jul 2003 | A1 |
| 20030210812 | Khamene et al. | Nov 2003 | A1 |
| 20030223877 | Anstine et al. | Dec 2003 | A1 |
| 20040078236 | Stoodley et al. | Apr 2004 | A1 |
| 20040199180 | Knodel et al. | Oct 2004 | A1 |
| 20040199659 | Ishikawa et al. | Oct 2004 | A1 |
| 20040206365 | Knowlton | Oct 2004 | A1 |
| 20040243148 | Wasielewski | Dec 2004 | A1 |
| 20040243435 | Williams | Dec 2004 | A1 |
| 20050020909 | Moctezuma de la Barrera et al. | Jan 2005 | A1 |
| 20050023324 | Doll et al. | Feb 2005 | A1 |
| 20050063575 | Ma et al. | Mar 2005 | A1 |
| 20050065438 | Miller | Mar 2005 | A1 |
| 20050131390 | Heinrich et al. | Jun 2005 | A1 |
| 20050143759 | Kelly | Jun 2005 | A1 |
| 20050149001 | Uchikubo et al. | Jul 2005 | A1 |
| 20050149356 | Cyr et al. | Jul 2005 | A1 |
| 20050165390 | Mauti et al. | Jul 2005 | A1 |
| 20050192633 | Montpetit | Sep 2005 | A1 |
| 20050203384 | Sati et al. | Sep 2005 | A1 |
| 20050203504 | Wham et al. | Sep 2005 | A1 |
| 20050222631 | Dalal et al. | Oct 2005 | A1 |
| 20050228425 | Boukhny et al. | Oct 2005 | A1 |
| 20050236474 | Onuma et al. | Oct 2005 | A1 |
| 20050251233 | Kanzius | Nov 2005 | A1 |
| 20050277913 | McCary | Dec 2005 | A1 |
| 20060020272 | Gildenberg | Jan 2006 | A1 |
| 20060025816 | Shelton | Feb 2006 | A1 |
| 20060059018 | Shiobara et al. | Mar 2006 | A1 |
| 20060079874 | Faller et al. | Apr 2006 | A1 |
| 20060116908 | Dew et al. | Jun 2006 | A1 |
| 20060136622 | Rouvelin et al. | Jun 2006 | A1 |
| 20060184160 | Ozaki et al. | Aug 2006 | A1 |
| 20060241399 | Fabian | Oct 2006 | A1 |
| 20070010838 | Shelton et al. | Jan 2007 | A1 |
| 20070016235 | Tanaka et al. | Jan 2007 | A1 |
| 20070027459 | Horvath et al. | Feb 2007 | A1 |
| 20070049947 | Menn et al. | Mar 2007 | A1 |
| 20070078678 | DiSilvestro et al. | Apr 2007 | A1 |
| 20070084896 | Doll et al. | Apr 2007 | A1 |
| 20070167702 | Hasser et al. | Jul 2007 | A1 |
| 20070168461 | Moore | Jul 2007 | A1 |
| 20070173803 | Wham et al. | Jul 2007 | A1 |
| 20070175955 | Shelton et al. | Aug 2007 | A1 |
| 20070179482 | Anderson | Aug 2007 | A1 |
| 20070191713 | Eichmann et al. | Aug 2007 | A1 |
| 20070203744 | Scholl | Aug 2007 | A1 |
| 20070225556 | Ortiz et al. | Sep 2007 | A1 |
| 20070225690 | Sekiguchi et al. | Sep 2007 | A1 |
| 20070244478 | Bahney | Oct 2007 | A1 |
| 20070249990 | Cosmescu | Oct 2007 | A1 |
| 20070270660 | Caylor et al. | Nov 2007 | A1 |
| 20070282195 | Masini et al. | Dec 2007 | A1 |
| 20070282321 | Shah et al. | Dec 2007 | A1 |
| 20070282333 | Fortson et al. | Dec 2007 | A1 |
| 20070293218 | Meylan et al. | Dec 2007 | A1 |
| 20080013460 | Allen et al. | Jan 2008 | A1 |
| 20080015664 | Podhajsky | Jan 2008 | A1 |
| 20080015912 | Rosenthal et al. | Jan 2008 | A1 |
| 20080033404 | Romoda et al. | Feb 2008 | A1 |
| 20080040151 | Moore | Feb 2008 | A1 |
| 20080059658 | Williams | Mar 2008 | A1 |
| 20080077158 | Haider et al. | Mar 2008 | A1 |
| 20080083414 | Messerges | Apr 2008 | A1 |
| 20080114350 | Park et al. | May 2008 | A1 |
| 20080129465 | Rao | Jun 2008 | A1 |
| 20080140090 | Aranyi et al. | Jun 2008 | A1 |
| 20080177258 | Govari et al. | Jul 2008 | A1 |
| 20080177362 | Phillips et al. | Jul 2008 | A1 |
| 20080200940 | Eichmann et al. | Aug 2008 | A1 |
| 20080255413 | Zemlok et al. | Oct 2008 | A1 |
| 20080262654 | Omori et al. | Oct 2008 | A1 |
| 20080272172 | Zemlok et al. | Nov 2008 | A1 |
| 20080281301 | DeBoer et al. | Nov 2008 | A1 |
| 20080281678 | Keuls et al. | Nov 2008 | A1 |
| 20080296346 | Shelton, IV et al. | Dec 2008 | A1 |
| 20080306759 | Ilkin et al. | Dec 2008 | A1 |
| 20080312953 | Claus | Dec 2008 | A1 |
| 20090030437 | Houser et al. | Jan 2009 | A1 |
| 20090036750 | Weinstein et al. | Feb 2009 | A1 |
| 20090036794 | Stubhaug et al. | Feb 2009 | A1 |
| 20090043253 | Podaima | Feb 2009 | A1 |
| 20090046146 | Hoyt | Feb 2009 | A1 |
| 20090048589 | Takashino et al. | Feb 2009 | A1 |
| 20090076409 | Wu et al. | Mar 2009 | A1 |
| 20090090763 | Zemlok et al. | Apr 2009 | A1 |
| 20090099866 | Newman | Apr 2009 | A1 |
| 20090182577 | Squilla et al. | Jul 2009 | A1 |
| 20090206131 | Weisenburgh, II et al. | Aug 2009 | A1 |
| 20090217932 | Voegele | Sep 2009 | A1 |
| 20090234352 | Behnke et al. | Sep 2009 | A1 |
| 20090259149 | Tahara et al. | Oct 2009 | A1 |
| 20090259221 | Tahara et al. | Oct 2009 | A1 |
| 20090299214 | Wu et al. | Dec 2009 | A1 |
| 20090307681 | Armado et al. | Dec 2009 | A1 |
| 20090326321 | Jacobsen et al. | Dec 2009 | A1 |
| 20090326336 | Lemke et al. | Dec 2009 | A1 |
| 20100057106 | Sorrentino et al. | Mar 2010 | A1 |
| 20100065604 | Weng | Mar 2010 | A1 |
| 20100069939 | Konishi | Mar 2010 | A1 |
| 20100069942 | Shelton, IV | Mar 2010 | A1 |
| 20100070417 | Flynn et al. | Mar 2010 | A1 |
| 20100120266 | Rimborg | May 2010 | A1 |
| 20100132334 | Duclos et al. | Jun 2010 | A1 |
| 20100137845 | Ramstein et al. | Jun 2010 | A1 |
| 20100137886 | Zergiebel et al. | Jun 2010 | A1 |
| 20100168561 | Anderson | Jul 2010 | A1 |
| 20100179831 | Brown et al. | Jul 2010 | A1 |
| 20100191100 | Anderson et al. | Jul 2010 | A1 |
| 20100198200 | Horvath | Aug 2010 | A1 |
| 20100198248 | Vakharia | Aug 2010 | A1 |
| 20100217991 | Choi | Aug 2010 | A1 |
| 20100234996 | Schreiber et al. | Sep 2010 | A1 |
| 20100235689 | Tian et al. | Sep 2010 | A1 |
| 20100250571 | Pierce et al. | Sep 2010 | A1 |
| 20100292535 | Paskar | Nov 2010 | A1 |
| 20100292684 | Cybulski et al. | Nov 2010 | A1 |
| 20110022032 | Zemlok et al. | Jan 2011 | A1 |
| 20110071530 | Carson | Mar 2011 | A1 |
| 20110077512 | Boswell | Mar 2011 | A1 |
| 20110087238 | Wang et al. | Apr 2011 | A1 |
| 20110105895 | Kornblau et al. | May 2011 | A1 |
| 20110118708 | Burbank et al. | May 2011 | A1 |
| 20110119075 | Dhoble | May 2011 | A1 |
| 20110125149 | El-Galley et al. | May 2011 | A1 |
| 20110152712 | Cao et al. | Jun 2011 | A1 |
| 20110163147 | Laurent et al. | Jul 2011 | A1 |
| 20110166883 | Palmer et al. | Jul 2011 | A1 |
| 20110196398 | Robertson et al. | Aug 2011 | A1 |
| 20110237883 | Chun | Sep 2011 | A1 |
| 20110264000 | Paul et al. | Oct 2011 | A1 |
| 20110273465 | Konishi et al. | Nov 2011 | A1 |
| 20110278343 | Knodel et al. | Nov 2011 | A1 |
| 20110290024 | Lefler | Dec 2011 | A1 |
| 20110295270 | Giordano et al. | Dec 2011 | A1 |
| 20110306840 | Allen et al. | Dec 2011 | A1 |
| 20120022519 | Huang et al. | Jan 2012 | A1 |
| 20120029354 | Mark et al. | Feb 2012 | A1 |
| 20120046662 | Gilbert | Feb 2012 | A1 |
| 20120059684 | Hampapur et al. | Mar 2012 | A1 |
| 20120078247 | Worrell et al. | Mar 2012 | A1 |
| 20120080336 | Shelton, IV et al. | Apr 2012 | A1 |
| 20120083786 | Artale et al. | Apr 2012 | A1 |
| 20120116265 | Houser et al. | May 2012 | A1 |
| 20120116381 | Houser et al. | May 2012 | A1 |
| 20120116394 | Timm et al. | May 2012 | A1 |
| 20120130217 | Kauphusman et al. | May 2012 | A1 |
| 20120145714 | Farascioni et al. | Jun 2012 | A1 |
| 20120172696 | Kallback et al. | Jul 2012 | A1 |
| 20120190981 | Harris et al. | Jul 2012 | A1 |
| 20120191091 | Allen | Jul 2012 | A1 |
| 20120191162 | Villa | Jul 2012 | A1 |
| 20120197619 | Namer Yelin et al. | Aug 2012 | A1 |
| 20120203785 | Awada | Aug 2012 | A1 |
| 20120211542 | Racenet | Aug 2012 | A1 |
| 20120245958 | Lawrence et al. | Sep 2012 | A1 |
| 20120253329 | Zemlok et al. | Oct 2012 | A1 |
| 20120265555 | Cappuzzo et al. | Oct 2012 | A1 |
| 20120292367 | Morgan et al. | Nov 2012 | A1 |
| 20120319859 | Taub et al. | Dec 2012 | A1 |
| 20130024213 | Poon | Jan 2013 | A1 |
| 20130046182 | Hegg et al. | Feb 2013 | A1 |
| 20130046279 | Niklewski et al. | Feb 2013 | A1 |
| 20130066647 | Andrie et al. | Mar 2013 | A1 |
| 20130090526 | Suzuki et al. | Apr 2013 | A1 |
| 20130093829 | Rosenblatt et al. | Apr 2013 | A1 |
| 20130096597 | Anand et al. | Apr 2013 | A1 |
| 20130116218 | Kaplan et al. | May 2013 | A1 |
| 20130144284 | Behnke, II et al. | Jun 2013 | A1 |
| 20130165776 | Blomqvist | Jun 2013 | A1 |
| 20130178853 | Hyink et al. | Jul 2013 | A1 |
| 20130206813 | Nalagatla | Aug 2013 | A1 |
| 20130214025 | Zemlok et al. | Aug 2013 | A1 |
| 20130253480 | Kimball et al. | Sep 2013 | A1 |
| 20130256373 | Schmid et al. | Oct 2013 | A1 |
| 20130267874 | Marcotte et al. | Oct 2013 | A1 |
| 20130268283 | Vann et al. | Oct 2013 | A1 |
| 20130277410 | Fernandez et al. | Oct 2013 | A1 |
| 20130317837 | Ballantyne et al. | Nov 2013 | A1 |
| 20130321425 | Greene et al. | Dec 2013 | A1 |
| 20130325809 | Kim et al. | Dec 2013 | A1 |
| 20130331873 | Ross et al. | Dec 2013 | A1 |
| 20130331875 | Ross 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 |
| 20140006132 | Barker | Jan 2014 | A1 |
| 20140006943 | Robbins et al. | Jan 2014 | A1 |
| 20140009894 | Yu | Jan 2014 | A1 |
| 20140013565 | MacDonald et al. | Jan 2014 | A1 |
| 20140029411 | Nayak et al. | Jan 2014 | A1 |
| 20140033926 | Fassel et al. | Feb 2014 | A1 |
| 20140035762 | Shelton, IV et al. | Feb 2014 | A1 |
| 20140066700 | Wilson et al. | Mar 2014 | A1 |
| 20140073893 | Bencini | Mar 2014 | A1 |
| 20140074076 | Gertner | Mar 2014 | A1 |
| 20140081255 | Johnson et al. | Mar 2014 | A1 |
| 20140081659 | Nawana et al. | Mar 2014 | A1 |
| 20140084949 | Smith et al. | Mar 2014 | A1 |
| 20140087999 | Kaplan et al. | Mar 2014 | A1 |
| 20140092089 | Kasuya et al. | Apr 2014 | A1 |
| 20140107697 | Patani et al. | Apr 2014 | A1 |
| 20140108035 | Akbay et al. | Apr 2014 | A1 |
| 20140108983 | William R et al. | Apr 2014 | A1 |
| 20140148729 | Schmitz et al. | May 2014 | A1 |
| 20140166724 | Schellin et al. | Jun 2014 | A1 |
| 20140187856 | Holoien et al. | Jul 2014 | A1 |
| 20140188440 | Donhowe et al. | Jul 2014 | A1 |
| 20140194864 | Martin et al. | Jul 2014 | A1 |
| 20140204190 | Rosenblatt, III et al. | Jul 2014 | A1 |
| 20140226572 | Thota et al. | Aug 2014 | A1 |
| 20140243799 | Parihar | Aug 2014 | A1 |
| 20140243809 | Gelfand et al. | Aug 2014 | A1 |
| 20140246475 | Hall et al. | Sep 2014 | A1 |
| 20140249557 | Koch et al. | Sep 2014 | A1 |
| 20140252064 | Mozdzierz et al. | Sep 2014 | A1 |
| 20140263541 | Leimbach et al. | Sep 2014 | A1 |
| 20140263552 | Hall et al. | Sep 2014 | A1 |
| 20140276749 | Johnson | Sep 2014 | A1 |
| 20140303660 | Boyden et al. | Oct 2014 | A1 |
| 20140303990 | Schoenefeld et al. | Oct 2014 | A1 |
| 20140364691 | Krivopisk et al. | Dec 2014 | A1 |
| 20150006201 | Pait et al. | Jan 2015 | A1 |
| 20150025549 | Kilroy et al. | Jan 2015 | A1 |
| 20150032150 | Ishida et al. | Jan 2015 | A1 |
| 20150051452 | Ciaccio | Feb 2015 | A1 |
| 20150051617 | Takemura et al. | Feb 2015 | A1 |
| 20150053737 | Leimbach et al. | Feb 2015 | A1 |
| 20150057675 | Akeel et al. | Feb 2015 | A1 |
| 20150066000 | An et al. | Mar 2015 | A1 |
| 20150070187 | Wiesner et al. | Mar 2015 | A1 |
| 20150108198 | Estrella | Apr 2015 | A1 |
| 20150133945 | Dushyant et al. | May 2015 | A1 |
| 20150140982 | Postrel | May 2015 | A1 |
| 20150145682 | Harris | May 2015 | A1 |
| 20150148830 | Stulen et al. | May 2015 | A1 |
| 20150173673 | Toth et al. | Jun 2015 | A1 |
| 20150173756 | Baxter, III et al. | Jun 2015 | A1 |
| 20150196295 | Shelton, IV et al. | Jul 2015 | A1 |
| 20150199109 | Lee | Jul 2015 | A1 |
| 20150208934 | Sztrubel et al. | Jul 2015 | A1 |
| 20150237502 | Schmidt et al. | Aug 2015 | A1 |
| 20150238355 | Vezzu et al. | Aug 2015 | A1 |
| 20150272557 | Overmyer et al. | Oct 2015 | A1 |
| 20150272571 | Leimbach et al. | Oct 2015 | A1 |
| 20150272580 | Leimbach et al. | Oct 2015 | A1 |
| 20150272582 | Leimbach et al. | Oct 2015 | A1 |
| 20150272694 | Charles | Oct 2015 | A1 |
| 20150297200 | Fitzsimmons et al. | Oct 2015 | A1 |
| 20150297222 | Huitema et al. | Oct 2015 | A1 |
| 20150297228 | Huitema et al. | Oct 2015 | A1 |
| 20150297233 | Huitema et al. | Oct 2015 | A1 |
| 20150297311 | Tesar | Oct 2015 | A1 |
| 20150302157 | Collar et al. | Oct 2015 | A1 |
| 20150310174 | Coudert et al. | Oct 2015 | A1 |
| 20150313538 | Bechtel et al. | Nov 2015 | A1 |
| 20150317899 | Dumbauld et al. | Nov 2015 | A1 |
| 20150324114 | Hurley et al. | Nov 2015 | A1 |
| 20150328474 | Flyash et al. | Nov 2015 | A1 |
| 20150332003 | Stamm et al. | Nov 2015 | A1 |
| 20150332196 | Stiller et al. | Nov 2015 | A1 |
| 20150335344 | Aljuri et al. | Nov 2015 | A1 |
| 20160000437 | Giordano et al. | Jan 2016 | A1 |
| 20160001411 | Alberti | Jan 2016 | A1 |
| 20160015471 | Piron et al. | Jan 2016 | A1 |
| 20160034648 | Mohlenbrock et al. | Feb 2016 | A1 |
| 20160038253 | Piron et al. | Feb 2016 | A1 |
| 20160066913 | Swayze et al. | Mar 2016 | A1 |
| 20160078190 | Greene et al. | Mar 2016 | A1 |
| 20160106516 | Mesallum | Apr 2016 | A1 |
| 20160106934 | Hiraga et al. | Apr 2016 | A1 |
| 20160121143 | Mumaw et al. | May 2016 | A1 |
| 20160158468 | Tang et al. | Jun 2016 | A1 |
| 20160174998 | Lal et al. | Jun 2016 | A1 |
| 20160180045 | Syed | Jun 2016 | A1 |
| 20160184054 | Lowe | Jun 2016 | A1 |
| 20160192960 | Bueno et al. | Jul 2016 | A1 |
| 20160206202 | Frangioni | Jul 2016 | A1 |
| 20160224760 | Petak et al. | Aug 2016 | A1 |
| 20160225551 | Shedletsky | Aug 2016 | A1 |
| 20160228204 | Quaid et al. | Aug 2016 | A1 |
| 20160235303 | Fleming et al. | Aug 2016 | A1 |
| 20160249910 | Shelton, IV et al. | Sep 2016 | A1 |
| 20160278841 | Panescu et al. | Sep 2016 | A1 |
| 20160287312 | Tegg et al. | Oct 2016 | A1 |
| 20160287912 | Warnking | Oct 2016 | A1 |
| 20160296246 | Schaller | Oct 2016 | A1 |
| 20160302210 | Thornton et al. | Oct 2016 | A1 |
| 20160310055 | Zand et al. | Oct 2016 | A1 |
| 20160314716 | Grubbs | Oct 2016 | A1 |
| 20160314717 | Grubbs | Oct 2016 | A1 |
| 20160321400 | Durrant et al. | Nov 2016 | A1 |
| 20160323283 | Kang et al. | Nov 2016 | A1 |
| 20160331460 | Cheatham, III et al. | Nov 2016 | A1 |
| 20160342753 | Feazell | Nov 2016 | A1 |
| 20160342916 | Arceneaux et al. | Nov 2016 | A1 |
| 20160345857 | Jensrud et al. | Dec 2016 | A1 |
| 20160345976 | Gonzalez et al. | Dec 2016 | A1 |
| 20160350490 | Martinez et al. | Dec 2016 | A1 |
| 20160361070 | Ardel et al. | Dec 2016 | A1 |
| 20160367305 | Hareland | Dec 2016 | A1 |
| 20160374723 | Frankhouser et al. | Dec 2016 | A1 |
| 20160374762 | Case et al. | Dec 2016 | A1 |
| 20160379504 | Bailey et al. | Dec 2016 | A1 |
| 20170000516 | Stulen et al. | Jan 2017 | A1 |
| 20170000553 | Wiener et al. | Jan 2017 | A1 |
| 20170027603 | Pandey | Feb 2017 | A1 |
| 20170042604 | McFarland et al. | Feb 2017 | A1 |
| 20170068792 | Reiner | Mar 2017 | A1 |
| 20170079730 | Azizian et al. | Mar 2017 | A1 |
| 20170086829 | Vendely et al. | Mar 2017 | A1 |
| 20170086930 | Thompson et al. | Mar 2017 | A1 |
| 20170105754 | Boudreaux et al. | Apr 2017 | A1 |
| 20170116873 | Lendvay et al. | Apr 2017 | A1 |
| 20170127499 | Unoson et al. | May 2017 | A1 |
| 20170132374 | Lee et al. | May 2017 | A1 |
| 20170132785 | Wshah et al. | May 2017 | A1 |
| 20170143284 | Sehnert et al. | May 2017 | A1 |
| 20170143442 | Tesar et al. | May 2017 | A1 |
| 20170156076 | Eom et al. | Jun 2017 | A1 |
| 20170164997 | Johnson et al. | Jun 2017 | A1 |
| 20170165012 | Chaplin et al. | Jun 2017 | A1 |
| 20170172565 | Heneveld | Jun 2017 | A1 |
| 20170172614 | Scheib et al. | Jun 2017 | A1 |
| 20170177807 | Fabian | Jun 2017 | A1 |
| 20170196583 | Sugiyama | Jul 2017 | A1 |
| 20170196637 | Shelton, IV et al. | Jul 2017 | A1 |
| 20170202591 | Shelton, IV et al. | Jul 2017 | A1 |
| 20170202595 | Shelton, IV | Jul 2017 | A1 |
| 20170202607 | Shelton, IV et al. | Jul 2017 | A1 |
| 20170202608 | Shelton, IV et al. | Jul 2017 | A1 |
| 20170224332 | Hunter et al. | Aug 2017 | A1 |
| 20170224334 | Worthington et al. | Aug 2017 | A1 |
| 20170224428 | Kopp | Aug 2017 | A1 |
| 20170231627 | Shelton, IV et al. | Aug 2017 | A1 |
| 20170231628 | Shelton, IV et al. | Aug 2017 | A1 |
| 20170245809 | Ma et al. | Aug 2017 | A1 |
| 20170249432 | Grantcharov | Aug 2017 | A1 |
| 20170262604 | Francois | Sep 2017 | A1 |
| 20170265864 | Hessler et al. | Sep 2017 | A1 |
| 20170265943 | Sela et al. | Sep 2017 | A1 |
| 20170273715 | Piron et al. | Sep 2017 | A1 |
| 20170281171 | Shelton, IV et al. | Oct 2017 | A1 |
| 20170281173 | Shelton, IV et al. | Oct 2017 | A1 |
| 20170281186 | Shelton, IV et al. | Oct 2017 | A1 |
| 20170281189 | Nalagatla et al. | Oct 2017 | A1 |
| 20170290585 | Shelton, IV et al. | Oct 2017 | A1 |
| 20170296169 | Yates et al. | Oct 2017 | A1 |
| 20170296173 | Shelton, IV et al. | Oct 2017 | A1 |
| 20170296185 | Swensgard et al. | Oct 2017 | A1 |
| 20170296213 | Swensgard et al. | Oct 2017 | A1 |
| 20170303984 | Malackowski | Oct 2017 | A1 |
| 20170304020 | Ng et al. | Oct 2017 | A1 |
| 20170312456 | Phillips | Nov 2017 | A1 |
| 20170325876 | Nakadate et al. | Nov 2017 | A1 |
| 20170325878 | Messerly et al. | Nov 2017 | A1 |
| 20170360499 | Greep et al. | Dec 2017 | A1 |
| 20170367583 | Black et al. | Dec 2017 | A1 |
| 20170367695 | Shelton, IV et al. | Dec 2017 | A1 |
| 20170367754 | Narisawa | Dec 2017 | A1 |
| 20170367771 | Tako et al. | Dec 2017 | A1 |
| 20170367772 | Gunn et al. | Dec 2017 | A1 |
| 20170370710 | Chen et al. | Dec 2017 | A1 |
| 20180008359 | Randle | Jan 2018 | A1 |
| 20180011983 | Zuhars et al. | Jan 2018 | A1 |
| 20180042659 | Rupp et al. | Feb 2018 | A1 |
| 20180050196 | Pawsey et al. | Feb 2018 | A1 |
| 20180055529 | Messerly et al. | Mar 2018 | A1 |
| 20180065248 | Barral et al. | Mar 2018 | A1 |
| 20180078170 | Panescu et al. | Mar 2018 | A1 |
| 20180098816 | Govari et al. | Apr 2018 | A1 |
| 20180110523 | Shelton, IV | Apr 2018 | A1 |
| 20180116662 | Shelton, IV et al. | May 2018 | A1 |
| 20180116735 | Tierney et al. | May 2018 | A1 |
| 20180122506 | Grantcharov et al. | May 2018 | A1 |
| 20180125590 | Giordano et al. | May 2018 | A1 |
| 20180132895 | Silver | May 2018 | A1 |
| 20180144243 | Hsieh et al. | May 2018 | A1 |
| 20180153574 | Faller et al. | Jun 2018 | A1 |
| 20180153628 | Grover et al. | Jun 2018 | A1 |
| 20180153632 | Tokarchuk et al. | Jun 2018 | A1 |
| 20180154297 | Maletich et al. | Jun 2018 | A1 |
| 20180161716 | Li et al. | Jun 2018 | A1 |
| 20180168575 | Simms et al. | Jun 2018 | A1 |
| 20180168577 | Aronhalt et al. | Jun 2018 | A1 |
| 20180168578 | Aronhalt et al. | Jun 2018 | A1 |
| 20180168579 | Aronhalt et al. | Jun 2018 | A1 |
| 20180168584 | Harris et al. | Jun 2018 | A1 |
| 20180168586 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168590 | Overmyer et al. | Jun 2018 | A1 |
| 20180168592 | Overmyer et al. | Jun 2018 | A1 |
| 20180168593 | Overmyer et al. | Jun 2018 | A1 |
| 20180168597 | Fanelli et al. | Jun 2018 | A1 |
| 20180168598 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168608 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168609 | Fanelli et al. | Jun 2018 | A1 |
| 20180168610 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168614 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168615 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168617 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168618 | Scott et al. | Jun 2018 | A1 |
| 20180168619 | Scott et al. | Jun 2018 | A1 |
| 20180168623 | Simms et al. | Jun 2018 | A1 |
| 20180168625 | Posada et al. | Jun 2018 | A1 |
| 20180168627 | Weaner et al. | Jun 2018 | A1 |
| 20180168628 | Hunter et al. | Jun 2018 | A1 |
| 20180168633 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168647 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168648 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168649 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168650 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168651 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180177383 | Noonan et al. | Jun 2018 | A1 |
| 20180206884 | Beaupre | Jul 2018 | A1 |
| 20180206905 | Batchelor et al. | Jul 2018 | A1 |
| 20180214025 | Homyk et al. | Aug 2018 | A1 |
| 20180221005 | Hamel et al. | Aug 2018 | A1 |
| 20180221598 | Silver | Aug 2018 | A1 |
| 20180228557 | Darisse et al. | Aug 2018 | A1 |
| 20180233222 | Daley et al. | Aug 2018 | A1 |
| 20180235719 | Jarc | Aug 2018 | A1 |
| 20180235722 | Baghdadi et al. | Aug 2018 | A1 |
| 20180242967 | Meade | Aug 2018 | A1 |
| 20180263710 | Sakaguchi et al. | Sep 2018 | A1 |
| 20180268320 | Shekhar | Sep 2018 | A1 |
| 20180271520 | Shelton, IV et al. | Sep 2018 | A1 |
| 20180271603 | Nir et al. | Sep 2018 | A1 |
| 20180296286 | Peine et al. | Oct 2018 | A1 |
| 20180303552 | Ryan et al. | Oct 2018 | A1 |
| 20180304471 | Tokuchi | Oct 2018 | A1 |
| 20180310935 | Wixey | Nov 2018 | A1 |
| 20180310986 | Batchelor et al. | Nov 2018 | A1 |
| 20180315492 | Bishop et al. | Nov 2018 | A1 |
| 20180317826 | Muhsin et al. | Nov 2018 | A1 |
| 20180333207 | Moctezuma De La Barrera | Nov 2018 | A1 |
| 20180351987 | Patel et al. | Dec 2018 | A1 |
| 20180360454 | Shelton, IV et al. | Dec 2018 | A1 |
| 20180360456 | Shelton, IV et al. | Dec 2018 | A1 |
| 20180368930 | Esterberg et al. | Dec 2018 | A1 |
| 20180369511 | Zergiebel et al. | Dec 2018 | A1 |
| 20190000446 | Shelton, IV et al. | Jan 2019 | A1 |
| 20190000478 | Messerly et al. | Jan 2019 | A1 |
| 20190000565 | Shelton, IV et al. | Jan 2019 | A1 |
| 20190000569 | Crawford et al. | Jan 2019 | A1 |
| 20190001079 | Zergiebel et al. | Jan 2019 | A1 |
| 20190005641 | Yamamoto | Jan 2019 | A1 |
| 20190006047 | Gorek et al. | Jan 2019 | A1 |
| 20190025040 | Andreason et al. | Jan 2019 | A1 |
| 20190036688 | Wasily et al. | Jan 2019 | A1 |
| 20190038335 | Mohr et al. | Feb 2019 | A1 |
| 20190038364 | Enoki | Feb 2019 | A1 |
| 20190046198 | Stokes et al. | Feb 2019 | A1 |
| 20190053801 | Wixey et al. | Feb 2019 | A1 |
| 20190053866 | Seow et al. | Feb 2019 | A1 |
| 20190069949 | Vrba et al. | Mar 2019 | A1 |
| 20190069964 | Hagn | Mar 2019 | A1 |
| 20190069966 | Petersen et al. | Mar 2019 | A1 |
| 20190070550 | Lalomia et al. | Mar 2019 | A1 |
| 20190070731 | Bowling et al. | Mar 2019 | A1 |
| 20190083190 | Graves et al. | Mar 2019 | A1 |
| 20190087544 | Peterson | Mar 2019 | A1 |
| 20190104919 | Shelton, IV et al. | Apr 2019 | A1 |
| 20190110828 | Despatie | Apr 2019 | A1 |
| 20190110855 | Barral et al. | Apr 2019 | A1 |
| 20190115108 | Hegedus et al. | Apr 2019 | A1 |
| 20190125320 | Shelton, IV et al. | May 2019 | A1 |
| 20190125321 | Shelton, IV et al. | May 2019 | A1 |
| 20190125324 | Scheib et al. | May 2019 | A1 |
| 20190125335 | Shelton, IV et al. | May 2019 | A1 |
| 20190125336 | Deck et al. | May 2019 | A1 |
| 20190125337 | Shelton, IV et al. | May 2019 | A1 |
| 20190125338 | Shelton, IV et al. | May 2019 | A1 |
| 20190125339 | Shelton, IV et al. | May 2019 | A1 |
| 20190125347 | Stokes et al. | May 2019 | A1 |
| 20190125348 | Shelton, IV et al. | May 2019 | A1 |
| 20190125352 | Shelton, IV et al. | May 2019 | A1 |
| 20190125353 | Shelton, IV et al. | May 2019 | A1 |
| 20190125354 | Deck et al. | May 2019 | A1 |
| 20190125355 | Shelton, IV et al. | May 2019 | A1 |
| 20190125356 | Shelton, IV et al. | May 2019 | A1 |
| 20190125357 | Shelton, IV et al. | May 2019 | A1 |
| 20190125358 | Shelton, IV et al. | May 2019 | A1 |
| 20190125359 | Shelton, IV et al. | May 2019 | A1 |
| 20190125360 | Shelton, IV et al. | May 2019 | A1 |
| 20190125361 | Shelton, IV et al. | May 2019 | A1 |
| 20190125377 | Shelton, IV | May 2019 | A1 |
| 20190125378 | Shelton, IV et al. | May 2019 | A1 |
| 20190125379 | Shelton, IV et al. | May 2019 | A1 |
| 20190125380 | Hunter et al. | May 2019 | A1 |
| 20190125383 | Scheib et al. | May 2019 | A1 |
| 20190125384 | Scheib et al. | May 2019 | A1 |
| 20190125385 | Scheib et al. | May 2019 | A1 |
| 20190125386 | Shelton, IV et al. | May 2019 | A1 |
| 20190125387 | Parihar et al. | May 2019 | A1 |
| 20190125388 | Shelton, IV et al. | May 2019 | A1 |
| 20190125389 | Shelton, IV et al. | May 2019 | A1 |
| 20190125430 | Shelton, IV et al. | May 2019 | A1 |
| 20190125431 | Shelton, IV et al. | May 2019 | A1 |
| 20190125432 | Shelton, IV et al. | May 2019 | A1 |
| 20190125454 | Stokes et al. | May 2019 | A1 |
| 20190125455 | Shelton, IV et al. | May 2019 | A1 |
| 20190125456 | Shelton, IV et al. | May 2019 | A1 |
| 20190125457 | Parihar et al. | May 2019 | A1 |
| 20190125458 | Shelton, IV et al. | May 2019 | A1 |
| 20190125459 | Shelton, IV et al. | May 2019 | A1 |
| 20190125476 | Shelton, IV et al. | May 2019 | A1 |
| 20190133703 | Seow et al. | May 2019 | A1 |
| 20190142449 | Shelton, IV et al. | May 2019 | A1 |
| 20190142535 | Seow et al. | May 2019 | A1 |
| 20190145942 | Dutriez et al. | May 2019 | A1 |
| 20190150975 | Kawasaki et al. | May 2019 | A1 |
| 20190159777 | Ehrenfels et al. | May 2019 | A1 |
| 20190159778 | Shelton, IV et al. | May 2019 | A1 |
| 20190162179 | O'Shea et al. | May 2019 | A1 |
| 20190167296 | Tsubuku et al. | Jun 2019 | A1 |
| 20190192157 | Scott et al. | Jun 2019 | A1 |
| 20190192236 | Shelton, IV et al. | Jun 2019 | A1 |
| 20190200844 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200863 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200905 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200906 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200977 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200980 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200981 | Harris et al. | Jul 2019 | A1 |
| 20190200984 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200985 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200986 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200987 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200988 | Shelton, IV | Jul 2019 | A1 |
| 20190200996 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200997 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200998 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201020 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201021 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201023 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201024 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201025 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201026 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201027 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201028 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201029 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201030 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201033 | Yates et al. | Jul 2019 | A1 |
| 20190201034 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201036 | Nott et al. | Jul 2019 | A1 |
| 20190201037 | Houser et al. | Jul 2019 | A1 |
| 20190201038 | Yates et al. | Jul 2019 | A1 |
| 20190201039 | Widenhouse et al. | Jul 2019 | A1 |
| 20190201040 | Messerly et al. | Jul 2019 | A1 |
| 20190201041 | Kimball et al. | Jul 2019 | A1 |
| 20190201042 | Nott et al. | Jul 2019 | A1 |
| 20190201043 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201044 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201045 | Yates et al. | Jul 2019 | A1 |
| 20190201046 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201047 | Yates et al. | Jul 2019 | A1 |
| 20190201073 | Nott et al. | Jul 2019 | A1 |
| 20190201074 | Yates et al. | Jul 2019 | A1 |
| 20190201075 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201077 | Yates et al. | Jul 2019 | A1 |
| 20190201079 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201080 | Messerly et al. | Jul 2019 | A1 |
| 20190201081 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201082 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201083 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201084 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201085 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201086 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201087 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201090 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201091 | Yates et al. | Jul 2019 | A1 |
| 20190201092 | Yates et al. | Jul 2019 | A1 |
| 20190201102 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201104 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201105 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201111 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201112 | Wiener et al. | Jul 2019 | A1 |
| 20190201113 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201114 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201115 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201116 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201118 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201119 | Harris et al. | Jul 2019 | A1 |
| 20190201120 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201123 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201124 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201125 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201126 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201127 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201128 | Yates et al. | Jul 2019 | A1 |
| 20190201129 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201130 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201135 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201136 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201137 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201138 | Yates et al. | Jul 2019 | A1 |
| 20190201139 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201140 | Yates et al. | Jul 2019 | A1 |
| 20190201141 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201142 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201143 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201144 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201145 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201146 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201158 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201159 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201594 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201597 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190204201 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190205001 | Messerly et al. | Jul 2019 | A1 |
| 20190205441 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190205566 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190205567 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206003 | Harris et al. | Jul 2019 | A1 |
| 20190206004 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206050 | Yates et al. | Jul 2019 | A1 |
| 20190206216 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206542 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206551 | Yates et al. | Jul 2019 | A1 |
| 20190206555 | Morgan et al. | Jul 2019 | A1 |
| 20190206556 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206561 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206562 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206563 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206564 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206565 | Shelton, IV | Jul 2019 | A1 |
| 20190206569 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206576 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190207911 | Wiener et al. | Jul 2019 | A1 |
| 20190208641 | Yates et al. | Jul 2019 | A1 |
| 20190224434 | Silver et al. | Jul 2019 | A1 |
| 20190254759 | Azizian | Aug 2019 | A1 |
| 20190261984 | Nelson et al. | Aug 2019 | A1 |
| 20190269476 | Bowling et al. | Sep 2019 | A1 |
| 20190272917 | Couture et al. | Sep 2019 | A1 |
| 20190274662 | Rockman et al. | Sep 2019 | A1 |
| 20190274705 | Sawhney et al. | Sep 2019 | A1 |
| 20190274706 | Nott et al. | Sep 2019 | A1 |
| 20190274707 | Sawhney et al. | Sep 2019 | A1 |
| 20190274708 | Boudreaux | Sep 2019 | A1 |
| 20190274709 | Scoggins | Sep 2019 | A1 |
| 20190274710 | Black | Sep 2019 | A1 |
| 20190274711 | Scoggins et al. | Sep 2019 | A1 |
| 20190274712 | Faller et al. | Sep 2019 | A1 |
| 20190274713 | Scoggins et al. | Sep 2019 | A1 |
| 20190274714 | Cut et al. | Sep 2019 | A1 |
| 20190274717 | Nott et al. | Sep 2019 | A1 |
| 20190274718 | Denzinger et al. | Sep 2019 | A1 |
| 20190274719 | Stulen | Sep 2019 | A1 |
| 20190274720 | Gee et al. | Sep 2019 | A1 |
| 20190274749 | Brady et al. | Sep 2019 | A1 |
| 20190274750 | Jayme et al. | Sep 2019 | A1 |
| 20190274752 | Denzinger et al. | Sep 2019 | A1 |
| 20190278262 | Taylor et al. | Sep 2019 | A1 |
| 20190282311 | Nowlin et al. | Sep 2019 | A1 |
| 20190290389 | Kopp | Sep 2019 | A1 |
| 20190298340 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298341 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298342 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298343 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298346 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298347 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298350 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298351 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298352 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298353 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298354 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298355 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298356 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298357 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298464 | Abbott | Oct 2019 | A1 |
| 20190298481 | Rosenberg et al. | Oct 2019 | A1 |
| 20190307520 | Peine et al. | Oct 2019 | A1 |
| 20190311802 | Kokubo et al. | Oct 2019 | A1 |
| 20190314015 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190314016 | Huitema et al. | Oct 2019 | A1 |
| 20190314081 | Brogna | Oct 2019 | A1 |
| 20190321117 | Itkowitz et al. | Oct 2019 | A1 |
| 20190333626 | Mansi et al. | Oct 2019 | A1 |
| 20190343594 | Garcia Kilroy et al. | Nov 2019 | A1 |
| 20190374140 | Tucker et al. | Dec 2019 | A1 |
| 20200000470 | Du et al. | Jan 2020 | A1 |
| 20200000509 | Hayashida et al. | Jan 2020 | A1 |
| 20200038120 | Ziraknejad et al. | Feb 2020 | A1 |
| 20200046353 | Deck et al. | Feb 2020 | A1 |
| 20200054317 | Pisarnwongs et al. | Feb 2020 | A1 |
| 20200054320 | Harris et al. | Feb 2020 | A1 |
| 20200054321 | Harris et al. | Feb 2020 | A1 |
| 20200054322 | Harris et al. | Feb 2020 | A1 |
| 20200054323 | Harris et al. | Feb 2020 | A1 |
| 20200054326 | Harris et al. | Feb 2020 | A1 |
| 20200054328 | Harris et al. | Feb 2020 | A1 |
| 20200054330 | Harris et al. | Feb 2020 | A1 |
| 20200078070 | Henderson et al. | Mar 2020 | A1 |
| 20200078071 | Asher | Mar 2020 | A1 |
| 20200078076 | Henderson et al. | Mar 2020 | A1 |
| 20200078077 | Henderson et al. | Mar 2020 | A1 |
| 20200078078 | Henderson et al. | Mar 2020 | A1 |
| 20200078079 | Morgan et al. | Mar 2020 | A1 |
| 20200078080 | Henderson et al. | Mar 2020 | A1 |
| 20200078081 | Jayme et al. | Mar 2020 | A1 |
| 20200078082 | Henderson et al. | Mar 2020 | A1 |
| 20200078089 | Henderson et al. | Mar 2020 | A1 |
| 20200078096 | Barbagli et al. | Mar 2020 | A1 |
| 20200078106 | Henderson et al. | Mar 2020 | A1 |
| 20200078110 | Henderson et al. | Mar 2020 | A1 |
| 20200078111 | Oberkircher et al. | Mar 2020 | A1 |
| 20200078112 | Henderson et al. | Mar 2020 | A1 |
| 20200078113 | Sawhney et al. | Mar 2020 | A1 |
| 20200078114 | Asher et al. | Mar 2020 | A1 |
| 20200078115 | Asher et al. | Mar 2020 | A1 |
| 20200078116 | Oberkircher et al. | Mar 2020 | A1 |
| 20200078117 | Henderson et al. | Mar 2020 | A1 |
| 20200078118 | Henderson et al. | Mar 2020 | A1 |
| 20200078119 | Henderson et al. | Mar 2020 | A1 |
| 20200078120 | Aldridge et al. | Mar 2020 | A1 |
| 20200081585 | Petre et al. | Mar 2020 | A1 |
| 20200090808 | Carroll et al. | Mar 2020 | A1 |
| 20200100825 | Henderson et al. | Apr 2020 | A1 |
| 20200100830 | Henderson et al. | Apr 2020 | A1 |
| 20200106220 | Henderson et al. | Apr 2020 | A1 |
| 20200162896 | Su et al. | May 2020 | A1 |
| 20200168323 | Bullington et al. | May 2020 | A1 |
| 20200178760 | Kashima et al. | Jun 2020 | A1 |
| 20200178971 | Harris et al. | Jun 2020 | A1 |
| 20200214699 | Shelton, IV et al. | Jul 2020 | A1 |
| 20200237372 | Park | Jul 2020 | A1 |
| 20200261075 | Boudreaux et al. | Aug 2020 | A1 |
| 20200261076 | Boudreaux et al. | Aug 2020 | A1 |
| 20200261077 | Shelton, IV et al. | Aug 2020 | A1 |
| 20200261078 | Bakos et al. | Aug 2020 | A1 |
| 20200261080 | Bakos et al. | Aug 2020 | A1 |
| 20200261081 | Boudreaux et al. | Aug 2020 | A1 |
| 20200261082 | Boudreaux et al. | Aug 2020 | A1 |
| 20200261083 | Bakos et al. | Aug 2020 | A1 |
| 20200261084 | Bakos et al. | Aug 2020 | A1 |
| 20200261085 | Boudreaux et al. | Aug 2020 | A1 |
| 20200261086 | Zeiner et al. | Aug 2020 | A1 |
| 20200261087 | Timm et al. | Aug 2020 | A1 |
| 20200261088 | Harris et al. | Aug 2020 | A1 |
| 20200261089 | Shelton, IV et al. | Aug 2020 | A1 |
| 20200275928 | Shelton, IV et al. | Sep 2020 | A1 |
| 20200275930 | Harris et al. | Sep 2020 | A1 |
| 20200281665 | Kopp | Sep 2020 | A1 |
| 20200305924 | Carroll | Oct 2020 | A1 |
| 20200305945 | Morgan et al. | Oct 2020 | A1 |
| 20200314569 | Morgan et al. | Oct 2020 | A1 |
| 20200405375 | Shelton, IV et al. | Dec 2020 | A1 |
| 20210000555 | Shelton, IV et al. | Jan 2021 | A1 |
| 20210007760 | Reisin | Jan 2021 | A1 |
| 20210015568 | Liao et al. | Jan 2021 | A1 |
| 20210022731 | Eisinger | Jan 2021 | A1 |
| 20210022738 | Weir et al. | Jan 2021 | A1 |
| 20210022809 | Crawford et al. | Jan 2021 | A1 |
| 20210059674 | Shelton, IV et al. | Mar 2021 | A1 |
| 20210068834 | Shelton, IV et al. | Mar 2021 | A1 |
| 20210128149 | Whitfield et al. | May 2021 | A1 |
| 20210153889 | Nott et al. | May 2021 | A1 |
| 20210169516 | Houser et al. | Jun 2021 | A1 |
| 20210176179 | Shelton, IV | Jun 2021 | A1 |
| 20210177452 | Nott et al. | Jun 2021 | A1 |
| 20210177489 | Yates et al. | Jun 2021 | A1 |
| 20210192914 | Shelton, IV et al. | Jun 2021 | A1 |
| 20210201646 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205020 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205021 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205028 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205029 | Wiener et al. | Jul 2021 | A1 |
| 20210205030 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205031 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212602 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212694 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212717 | Yates et al. | Jul 2021 | A1 |
| 20210212719 | Houser et al. | Jul 2021 | A1 |
| 20210212770 | Messerly et al. | Jul 2021 | A1 |
| 20210212771 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212774 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212775 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212782 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210219976 | DiNardo et al. | Jul 2021 | A1 |
| 20210220058 | Messerly et al. | Jul 2021 | A1 |
| 20210240852 | Shelton, IV et al. | Aug 2021 | A1 |
| 20210241898 | Shelton, IV et al. | Aug 2021 | A1 |
| 20210249125 | Morgan et al. | Aug 2021 | A1 |
| 20210251487 | Shelton, IV et al. | Aug 2021 | A1 |
| 20210259697 | Shelton, IV et al. | Aug 2021 | A1 |
| 20210259698 | Shelton, IV et al. | Aug 2021 | A1 |
| 20210282780 | Shelton, IV et al. | Sep 2021 | A1 |
| 20210282781 | Shelton, IV et al. | Sep 2021 | A1 |
| 20210315579 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210315580 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210315581 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210315582 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322014 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322015 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322017 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322018 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322019 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322020 | Shelton, IV et al. | Oct 2021 | A1 |
| Number | Date | Country |
|---|---|---|
| 2015201140 | Mar 2015 | AU |
| 2795323 | May 2014 | CA |
| 101617950 | Jan 2010 | CN |
| 104490448 | Mar 2017 | CN |
| 206097107 | Apr 2017 | CN |
| 108652695 | Oct 2018 | CN |
| 2037167 | Jul 1980 | DE |
| 3016131 | Oct 1981 | DE |
| 3824913 | Feb 1990 | DE |
| 4002843 | Apr 1991 | DE |
| 102005051367 | Apr 2007 | DE |
| 102016207666 | Nov 2017 | DE |
| 0000756 | Oct 1981 | EP |
| 0408160 | Jan 1991 | EP |
| 0473987 | Mar 1992 | EP |
| 0929263 | Jul 1999 | EP |
| 1214913 | Jun 2002 | EP |
| 2732772 | May 2014 | EP |
| 2942023 | Nov 2015 | EP |
| 3047806 | Jul 2016 | EP |
| 3056923 | Aug 2016 | EP |
| 3095399 | Nov 2016 | EP |
| 3120781 | Jan 2017 | EP |
| 3135225 | Mar 2017 | EP |
| 3141181 | Mar 2017 | EP |
| 2838234 | Oct 2003 | FR |
| 2509523 | Jul 2014 | GB |
| S5373315 | Jun 1978 | JP |
| 2001029353 | Feb 2001 | JP |
| 2007123394 | May 2007 | JP |
| 2017513561 | Jun 2017 | JP |
| 20140104587 | Aug 2014 | KR |
| 101587721 | Jan 2016 | KR |
| WO-9734533 | Sep 1997 | WO |
| WO-0024322 | May 2000 | WO |
| WO-0108578 | Feb 2001 | WO |
| WO-0112089 | Feb 2001 | WO |
| WO-0120892 | Mar 2001 | WO |
| WO-03079909 | Oct 2003 | WO |
| WO-2007137304 | Nov 2007 | WO |
| WO-2008053485 | May 2008 | WO |
| WO-2008056618 | May 2008 | WO |
| WO-2008069816 | Jun 2008 | WO |
| WO-2008147555 | Dec 2008 | WO |
| WO-2011112931 | Sep 2011 | WO |
| WO-2013143573 | Oct 2013 | WO |
| WO-2014031800 | Feb 2014 | WO |
| WO-2014071184 | May 2014 | WO |
| WO-2014134196 | Sep 2014 | WO |
| WO-2015129395 | Sep 2015 | WO |
| WO-2016100719 | Jun 2016 | WO |
| WO-2016206015 | Dec 2016 | WO |
| WO-2017011382 | Jan 2017 | WO |
| WO-2017011646 | Jan 2017 | WO |
| WO-2017058617 | Apr 2017 | WO |
| WO-2017058695 | Apr 2017 | WO |
| WO-2017151996 | Sep 2017 | WO |
| WO-2017189317 | Nov 2017 | WO |
| WO-2017205308 | Nov 2017 | WO |
| WO-2017210499 | Dec 2017 | WO |
| WO-2017210501 | Dec 2017 | WO |
| WO-2018116247 | Jun 2018 | WO |
| WO-2018152141 | Aug 2018 | WO |
| WO-2018176414 | Oct 2018 | WO |
| Entry |
|---|
| US 10,504,709, 08/2018, Karancsi et al. (withdrawn). |
| Flores et al., “Large-scale Offloading in the Internet of Things,” 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), IEEE, pp. 479-484, Mar. 13, 2017. |
| Kalantarian et al., “Computation Offloading for Real-Time Health-Monitoring Devices,” 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EBMC), IEEE, pp. 4971-4974, Aug. 16, 2016. |
| Yuyi Mao et al., “A Survey on Mobile Edge Computing: The Communication Perspective,” IEEE Communications Surveys & Tutorials, pp. 2322-2358, Jun. 13, 2017. |
| Khazaei et al., “Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective,” IEEE Journal of Translational Engineering in Health and Medicine, vol. 3, pp. 1-9, Oct. 21, 2015. |
| Benkmann et al., “Concept of iterative optimization of minimally invasive surgery,” 2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR), IEEE pp. 443-446, Aug. 28, 2017. |
| Trautman, Peter, “Breaking the Human-Robot Deadlock: Surpassing Shared Control Performance Limits with Sparse Human-Robot Interaction,” Robotics: Science and Systems XIIII, pp. 1-10, Jul. 12, 2017. |
| Yang et al., “A dynamic stategy for packet scheduling and bandwidth allocation based on channel quality in IEEE 802.16e OFDMA system,” Journal of Network and Computer Applications, vol. 39, pp. 52-60, May 2, 2013. |
| Takahashi et al., “Automatic smoke evacuation in laparoscopic surgery: a simplified method for objective evaluation,” Surgical Endoscopy, vol. 27, No. 8, pp. 2980-2987, Feb. 23, 2013. |
| Miksch et al., “Utilizing temporal data abstraction for data validation and therapy planning for artificially ventilated newborn infants,” Artificial Intelligence in Medicine, vol. 8, No. 6, pp. 543-576 (1996). |
| Horn et al., “Effective data validation of high-frequency data: Time-point-time-interval-, and trend-based methods,” Computers in Biology and Medic, New York, NY, vol. 27, No. 5, pp. 389-409 (1997). |
| Stacey et al., “Temporal abstraction in intelligent clinical data analysis: A survey,” Artificial Intelligence in Medicine, vol. 39, No. 1, pp. 1-24 (2006). |
| Zoccali, Bruno, “A Method for Approximating Component Temperatures at Altitude Conditions Based on CFD Analysis at Sea Level Conditions,” (white paper), www.tdmginc.com, Dec. 6, 2018 (9 pages). |
| Engel et al. “A safe robot system for craniofacial surgery”, 2013 IEEE International Conference on Robotics and Automation (ICRA); May 6-10, 2013; Karlsruhe, Germany, vol. 2, Jan. 1, 2001, pp. 2020-2024. |
| Bonaci et al., “To Make a Robot Secure: An Experimental Analysis of Cyber Security Threats Against Teleoperated Surgical Robots,” May 13, 2015. Retrieved from the Internet: URL:https://arxiv.org/pdf/1504.04339v2.pdf [retrieved on Aug. 24, 2019]. |
| Homa Alemzadeh et al., “Targeted Attacks on Teleoperated Surgical Robots: Dynamic Model-Based Detection and Mitigation,” 2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), IEEE, Jun. 28, 2016, pp. 395-406. |
| Phumzile Malindi, “5. QoS in Telemedicine,” “Telemedicine,” Jun. 20, 2011, IntechOpen, pp. 119-138. |
| Staub et al., “Contour-based Surgical Instrument Tracking Supported by Kinematic Prediction,” Proceedings of the 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, Sep. 1, 2010, pp. 746-752. |
| Allan et al., “3-D Pose Estimation of Articulated Instruments in Robotic Minimally Invasive Surgery,” IEEE Transactions on Medical Imaging, vol. 37, No. 5, May 1, 2018, pp. 1204-1213. |
| Kassahun et al., “Surgical Robotics Beyond Enhanced Dexterity Instrumentation: A Survey of the Machine Learning Techniques and their Role in Intelligent and Autonomous Surgical Actions.” International Journal of Computer Assisted Radiology and Surgery, vol. 11, No. 4, Oct. 8, 2015, pp. 553-568. |
| Weede et al. “An Intelligent and Autonomous Endoscopic Guidance System for Minimally Invasive Surgery,” 2013 IEEE International Conference on Robotics ad Automation (ICRA), May 6-10, 2013. Karlsruhe, Germany, May 1, 2011, pp. 5762-5768. |
| Altenberg et al., “Genes of Glycolysis are Ubiquitously Overexpressed in 24 Cancer Classes,” Genomics, vol. 84, pp. 1014-1020 (2004). |
| Harold I. Brandon and V. Leroy Young, Mar. 1997, Surgical Services Management vol. 3 No. 3. retrieved from the internet <https://www.surgimedics.com/Research%20Articles/Electrosurgical%20Plume/Characterization%20And%20Removal%20Of%20Electrosurgical%20Smoke.pdf> (Year: 1997). |
| Marshall Brain, How Microcontrollers Work, 2006, retrieved from the internet <https://web.archive.org/web/20060221235221/http://electronics.howstuffworks.com/microcontroller.htm/printable> (Year: 2006). |
| CRC Press, “The Measurement, Instrumentation and Sensors Handbook,” 1999, Section VII, Chapter 41, Peter O'Shea, “Phase Measurement,” pp. 1303-1321, ISBN 0-8493-2145-X. |
| Jiang, “‘Sound of Silence’: a secure indoor wireless ultrasonic communication system,” Article, 2014, pp. 46-50, Snapshots of Doctoral Research at University College Cork, School of Engineering—Electrical & Electronic Engineering, UCC, Cork, Ireland. |
| Li, et al., “Short-range ultrasonic communications in air using quadrature modulation,” Journal, Oct. 30, 2009, pp. 2060-2072, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 56, No. 10, IEEE. |
| Salamon, “AI Detects Polyps Better Than Colonoscopists” Online Article, Jun. 3, 2018, Medscape Medical News, Digestive Disease Week (DDW) 2018: Presentation 133. |
| Misawa, et al. “Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience,” Article, Jun. 2018, pp. 2027-2029, vol. 154, Issue 8, American Gastroenterolgy Association. |
| Dottorato, “Analysis and Design of the Rectangular Microstrip Patch Antennas for TM0n0 operating mode,”Article, Oct. 8, 2010, pp. 1-9, Microwave Journal. |
| Miller, et al., “Impact of Powered and Tissue-Specific Endoscopic Stapling Technology on Clinical and Economic Outcomes of Video-Assisted Thoracic Surgery Lobectomy Procedures: A Retrospective, Observational Study,” Article, Apr. 2018, pp. 707-723, vol. 35 (Issue 5), Advances in Therapy. |
| Hsiao-Wei Tang, “ARCM”, Video, Sep. 2012, YouTube, 5 screenshots, Retrieved from. Internet: <https://www.youtube.com/watch?v=UldQaxb3fRw&feature=youtu.be>. |
| Giannios, et al., “Visible to near-infrared refractive properties of freshly-excised human-liver tissues: marking hepatic malignancies,” Article, Jun. 14, 2016, pp. 1-10, Scientific Reports 6, Article No. 27910, Nature. |
| Vander Heiden, et al., “Understanding the Warburg effect: the metabolic requirements of cell proliferation,” Article, May 22, 2009, pp. 1-12, vol. 324, Issue 5930, Science. |
| Hirayama et al., “Quantitative Metabolome Profiling of Colon and Stomach Cancer Microenvironment by Capillary Electrophoresis Time-of-Flight Mass Spectrometry,” Article, Jun. 2009, pp. 4918-4925, vol. 69, Issue 11, Cancer Research. |
| Cengiz, et al., “A Tale of Two Compartments: Interstitial Versus Blood Glucose Monitoring,” Article, Jun. 2009, pp. S11-S16, vol. 11, Supplement 1, Diabetes Technology & Therapeutics. |
| Shen, et al., “An iridium nanoparticles dispersed carbon based thick film electrochemical biosensor and its application for a single use, disposable glucose biosensor,” Article, Feb. 3, 2007, pp. 106-113, vol. 125, Issue 1, Sensors and Actuators B: Chemical, Science Direct. |
| “ATM-MPLS Network Interworking Version 2.0, af-aic-0178.001” ATM Standard, The ATM Forum Technical Committee, published Aug. 2003. |
| IEEE Std 802.3-2012 (Revision of IEEE Std 802.3-2008, published Dec. 28, 2012. |
| IEEE Std No. 177, “Standard Definitions and Methods of Measurement for Piezoelectric Vibrators,” published May 1966, The Institute of Electrical and Electronics Engineers, Inc., New York, N.Y. |
| Shi et al., An intuitive control console for robotic syrgery system, 2014, IEEE, p. 404-407 (Year: 2014). |
| Choi et al., A haptic augmented reality surgeon console for a laparoscopic surgery robot system, 2013, IEEE, p. 355-357 (Year: 2013). |
| Xie et al., Development of stereo vision and master-slave controller for a compact surgical robot system, 2015, IEEE, p. 403-407 (Year: 2015). |
| Sun et al., Innovative effector design for simulation training in robotic surgery, 2010, IEEE, p. 1735-1759 (Year: 2010). |
| Anonymous, “Internet of Things Powers Connected Surgical Device Infrastructure Case Study”, Dec. 31, 2016 (Dec. 31, 2016), Retrieved from the Internet: URL:https://www.cognizant.com/services-resources/150110_IoT_connected_surgicai_devices.pdf. |
| Draijer, Matthijs et al., “Review of laser pseckle contrast techniques for visualizing tissue perfusion,” Lasers in Medical Science, Springer-Verlag, LO, vol. 24, No. 4, Dec. 3, 2008, pp. 639-651. |
| Roy D Cullum, “Handbook of Engineering Design”, ISBN: 9780408005586, Jan. 1, 1988 (Jan. 1, 1988), XP055578597, ISBN: 9780408005586, 10-20, Chapter6, p. 138, right-hand column, paragraph 3. |
| “Surgical instrumentation: the true cost of instrument trays and a potential strategy for optimization”; Mhlaba et al.; Sep. 23, 2015 (Year: 2015). |
| Nabil Simaan et al, “Intelligent Surgical Robots with Situational Awareness: From Good to Great Surgeons”, DOI: 10.1115/1.2015-Sep-6 external link, Sep. 2015 (Sep. 2015), p. 3-6, Retrieved from the Internet: URL:http://memagazineselect.asmedigitalcollection.asme.org/data/journals/meena/936888/me-2015-sep6.pdf XP055530863. |
| Anonymous: “Titanium Key Chain Tool 1.1, Ultralight Multipurpose Key Chain Tool, Forward Cutting Can Opener—Vargo Titanium,” vargooutdoors.com, Jul. 5, 2014 (Jul. 5, 2014), retrieved from the internet: https://vargooutdoors.com/titanium-key-chain-tool-1-1.html. |
| Anonymous: “Screwdriver—Wikipedia”, en.wikipedia.org, Jun. 23, 2019, XP055725151, Retrieved from the Internet: URL:https://en.wikipedia.org/w/index.php?title=Screwdriver&oldid=903111203 [retrieved on Mar. 20, 2021]. |
| Nordlinger, Christopher, “The Internet of Things and the Operating Room of the Future,” May 4, 2015, https://medium.com/@chrisnordlinger/the-internet-of-things-and-the-operating-room-of-the-future-8999a143d7b1, retrieved from the internet on Apr. 27, 2021, 9 pages. |
| Screen captures from YouTube video clip entitled “Four ways to use the Lego Brick Separator Tool,” 2 pages, uploaded on May 29, 2014 by user “Sarah Lewis”. Retrieved from internet: https://www.youtube.com/watch?v=ucKiRD6U1LU (Year: 2014). |
| Sorrells, P., “Application Note AN680. Passive RFID Basics,” retrieved from http://ww1.microchip.com/downloads/en/AppNotes/00680b.pdf on Feb. 26, 2020, Dec. 31, 1998, pp. 1-7. |
| “ATM-MPLS Network Interworking Version 2.0, af-aic-0178.001” ATM Standard, The ATM Forum Technical Committe, published Aug. 2003. |
| Number | Date | Country | |
|---|---|---|---|
| 20190274716 A1 | Sep 2019 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62721996 | Aug 2018 | US | |
| 62692768 | Jun 2018 | US | |
| 62692748 | Jun 2018 | US | |
| 62650898 | Mar 2018 | US | |
| 62640417 | Mar 2018 | US | |
| 62640415 | Mar 2018 | US |
