Active implantable cardiac devices include such systems as cardiac monitors, pacemakers, implantable defibrillators and cardiac resynchronization devices, among others. Such systems typically include implantable electrodes coupled to circuitry for sensing and analyzing electrical signals. Some systems are designed with multiple sensing electrodes to define multiple sensing vectors. For example, implantable transvenous and subcutaneous systems for monitoring and treating cardiac conditions are disclosed in U.S. Pat. No. 7,623,909, titled IMPLANTABLE MEDICAL DEVICES AND PROGRAMMERS ADAPTED FOR SENSING VECTOR SELECTION, the disclosure of which is incorporated herein by reference. The '909 patent discusses methods for selecting a default or primary sensing vector from among several available sensing vectors. Some examples allow for selection of primary and secondary vectors in the '909 patent.
Additional examples of implantable systems with multiple sensing vectors can be found in U.S. Pat. No. 8,200,341, titled SENSING VECTOR SELECTION IN A CARDIAC STIMULUS DEVICE WITH POSTURAL ASSESSMENT, U.S. Pat. No. 7,392,085, titled MULTIPLE ELECTRODE VECTORS FOR IMPLANTABLE CARDIAC TREATMENT DEVICES, and U.S. Pat. No. 5,331,966, titled SUBCUTANEOUS MULTI-ELECTRODE SENSING SYSTEM, METHOD AND PACER, the disclosures of which are incorporated herein by reference. Continuing enhancement of such systems is desired.
In illustrative examples, the present invention provides systems, methods and software apparatuses for performing sensing vector selection in an implantable cardiac device by assessing biphasic or monophasic characteristics of the cardiac signal in vectors under analysis. A factor associated with the biphasic or monophasic nature of the cardiac signal, as seen from a given sensing vector, can be inserted into the assessment of which of several available sensing vectors is considered “best” for purposes of cardiac signal analysis. Other variables may also be considered.
This overview is intended to provide an overview of subject matter of the present patent application. It is not intended to provide an exclusive or exhaustive explanation of the invention. The detailed description is included to provide further information about the present patent application.
In the drawings, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed in the present document.
Each of the following non-limiting examples can stand on its own, or can be combined in various permutations or combinations with one or more of the other examples.
As used herein, a signal is sensed by an implantable cardiac device system, events are detected in the sensed signal, and cardiac rhythms are classified by use of the detected events. Detected events may also be referred to as detections. Classification of the cardiac rhythms may be referred to as rhythm analysis. Cardiac rhythm classification can include identification of malignant conditions, such as ventricular fibrillation or certain tachyarrhythmias, for example.
The present invention may be used in implantable monitoring or therapy systems. Implantable therapy systems make therapy/stimulus decisions in reliance upon rhythm classification, while monitoring systems make data recording decisions using rhythm classification, where applicable. Therapy systems may deliver electrical, pharmaceutical or other therapy. Some illustrative implementations of the present invention may be in pacemakers and defibrillators, though other implementations are also envisioned. Any of these systems can, if so configured and enabled, generate annunciating (audible tones or palpable vibrations) or communicating (telemetry) signals in response to rhythm classification, in addition to or as an alternative to therapy.
Other configurations and implant locations may be used instead. Examples include right-sided or anterior-posterior subcutaneous implantation, transvenous systems, epicardial systems, intravascular systems, and other implementations such as drug pumps or neurostimulation systems that may incorporate cardiac signal analysis. Some alternatives and additional details are discussed below.
A cardiac cycle typically includes several portions (often referred to as “waves”) which, according to well-known convention, are labeled with letters including P, Q, R, S, and T, each corresponding to certain physiological events. Each cardiac cycle usually has all of these parts, though not all may be visible on any given cardiac signal representation. Certain components may not be visible due to factors such as elevated rate, choice of sensing vector, anatomic anomaly, or active arrhythmia, for example. The combination of Q, R and S “waves” can be referred to as the QRS complex.
It has been shown (see, e.g., U.S. Pat. No. 7,392,085) that different sensing vectors provide different “views” of the cardiac cycle. For example, in one sensing vector, the R-wave may be much larger than the T-wave, while in another sensing vector, the differences between R-wave and T-wave will be less dramatic. Features may vary among patients and within a single patient, depending upon posture and activity level, among other factors. Sensing vector selection or optimization can be performed to provide an implantable system with the best opportunity to accurately assess the patient's cardiac rhythm. Some examples can be found in U.S. Pat. Nos. 7,623,909 and 8,200,341, the disclosures of which are incorporated herein by reference.
When detecting events, an implantable cardiac device may compare the sensed signal to a detection threshold. If/when the sensed signal crosses the detection threshold, a new detected event is declared. The detection threshold may be static or may change with time (or by dependence on other variables such as observed signal frequency, perceived noise, etc.), depending upon the system configuration. In some systems the detection threshold has a shape defined by a detection profile which can be applied anew after each detected event. Often the detection profile is configured for detecting R-waves or the QRS complex while passing over the rest of the cardiac cycle without making additional detections.
The overall detection profile in
The refractory period 40 may have a duration of, for example, 100 to 250 milliseconds, with illustrative examples of about 160 and 200 milliseconds, for example, in some subcutaneous systems. Depending upon the signal being captured, a shorter refractory period may be used, for example, a refractory period of 70-150 milliseconds may be used for a transvenous sensing vector, which will see a “narrower” QRS complex in a near-field vector, typically, than a subcutaneous sensing vector. Other durations may be used.
The early stage 52 is shown as having a constant threshold for a period of time. In one example, the early stage may be in the range of 100 to 400 milliseconds long, with a threshold that is a fixed voltage or a fixed percentage of the overall amplitude (peak) of the QRS, or an average of several peaks, or other measure. Next, a decaying threshold is used in the late period 54, for example, beginning from a fixed voltage or a percentage of the overall amplitude (peak) of the QRS, or an average of several peaks, or other measure, and decaying, using, for example, an exponential decay, to a lower limit such as the sensing threshold of the system.
Some illustrative detection profiles are shown in U.S. Pat. No. 8,565,878, titled ACCURATE CARDIAC EVENT DETECTION IN AN IMPLANTABLE CARDIAC STIMULUS DEVICE, and U.S. Pat. No. 5,709,215, titled R-WAVE DETECTION METHOD OF IMPLANTABLE CARDIOVERTER DEFIBRILLATORS, the disclosures of which are incorporated herein by reference.
Two sets of terminology are illustrated in
The overall sensing period in example 60, or the combination of early and late periods in example 62, may have durations of up to or more than one second. In another example, the overall sensing period plus refractory in example 60, or the combination of refractory, early period and late period in example 62 may add up to one second of duration. Different durations may be used, if desired. In one example, the overall length of refractory plus sensing in example 60, or the overall length of refractory plus early and late periods in example 62, is defined by the interval between consecutive detected events.
The specifics of a detection profile can vary widely, and the U.S. Pat. No. 8,565,878 provides several illustrative examples and points out numerous variants and modifications, as does the U.S. Pat. No. 5,709,215.
The detection profile of
Referring now to
Using the signal and noise values, a signal to noise ratio (SNR) can be calculated, typically by division of the measured signal amplitude by the measured noise amplitude, though other versions of SNR may be used. Given that implantable systems are power constrained, sometimes simplified versions of a calculation may be chosen in place of more calculation intensive versions (i.e., subtraction rather than division). For example, SNR could be calculated by simple subtraction, by adding or subtracting an offset to one or the other of the measured signal or noise value before division, by use of a look-up table, or otherwise. In one example, simple division is used to calculate the SNR, and a look-up table is used to evaluate the meaning of the SNR to vector selection once calculated.
Steps to establish an amplitude measure are shown at 76. In the illustrative example, the highest peak signal in refractory is calculated, as shown at 78. An alternative example may consider both the height and width of the peak signal during refractory. The “Amplitude” measure may be a signed or unsigned value, depending on design preference. The use of a combination of SNR and amplitude is discussed in the U.S. Pat. No. 7,623,909 as a means to generate a “SCORE” indicating the qualities of the cardiac signal vector under analysis. Additional enhancements to a scoring approach are discussed in U.S. Pat. No. 7,783,340, titled SYSTEMS AND METHODS FOR SENSING VECTOR SELECTION IN AN IMPLANTABLE MEDICAL DEVICE USING A POLYNOMIAL APPROACH, the disclosure of which is incorporated herein by reference.
Turning now to
To establish a measure of how biphasic the signal is, the example shown at 80 identifies the most positive peak during the refractory period, as shown at 82, and also identifies the most negative peak during the refractory period, as shown at 84. These peaks 82, 84 are then compared at 86. Thus, this example focuses on whether the QRS portion of the cardiac cycle is biphasic. Other examples may look beyond the QRS portion of the cardiac cycle for biphasic characteristics, for example, if the T-wave is opposite in polarity to the largest peak of the QRS complex, this may be determined by expanding the search time-frame for peaks to include both the QRS as well as the T-wave.
In one example, a Biphasic Measure is calculated at block 86. The Biphasic Measure from block 86 is then rated using, for example, a look-up table or a calculation such as a polynomial or other formula, as shown at 88. The outcome of these steps 86, 88 is then incorporated in the vector selection calculation, as shown at 90.
In one example, the Biphasic Measure is calculated as a ratio of the most positive and most negative peaks from the refractory period. In another example, the peaks 82, 84 may be subtracted one from the other. Other calculations may be used. In one example, rather than the most positive and most negative peaks, instead, the largest overall peak may be chosen, and the largest peak of the opposing polarity that immediately precedes (or follows, in another example) the largest overall peak is chosen for use in comparison.
Certain examples herein disfavor a biphasic signal because it can create difficulties in the calculation of correlation. In an example, a signal analysis system compares the shape of two signals by selecting the largest peak of each signal as an alignment point. A monophasic signal will predictably select the same peak each time; a biphasic signal may dither between selecting the positive or negative peak, if the “largest” peak is sometimes positive and other times negative relative to baseline. Such a system may favor the monophasic signal to more predictably perform correlation analysis.
In an alternative example, a biphasic signal may be favored due to the ability to balance the signal about a quiescent point. A typical approach to maintaining the baseline/quiescent point of the system is to periodically correct the analog-to-digital converter output so that the average output over a relatively long period is treated as the baseline or “zero”. For a monophasic signal, a larger share of the cardiac signal power, particularly the QRS complex, is on one side of the isoelectric line, such that the cardiac signal isoelectric line and the baseline/quiescent point may not be the same. This phenomenon can be observed in
There may be other reasons to favor or disfavor biphasic signals as well, often driven by unique features of a given implementation and/or hardware.
In contrast, “Vector B”, shown at 110, is visibly biphasic. The positive amplitude peak during refractory (again indicated by two vertical lines) is larger than the noise peak noted outside of refractory by a wide margin. The amplitude of the most positive peak in refractory is similar to the amplitude of the most negative peak during refractory. As shown at 112, the signal has good amplitude and good SNR, but is identified as biphasic.
The distinction between monophasic and biphasic, in the illustrative embodiment, can be defined in several ways. Some examples are shown in the table, where “LP” indicates the absolute value of the amplitude of the larger peak of the largest positive and largest negative peaks during refractory, and “SP” indicates the absolute value of the smaller peak of the largest positive and largest negative peak during refractory. In this table, ST indicates the absolute sensing threshold of the system:
Thus, some examples are based on the size ratio between LP and SP, some are based on absolute differences, and at least one example integrates a requirement related to the absolute sensing threshold of the system. Some examples use three categories (Monophasic/Biphasic/Other) and other examples use just two categories (Monophasic/Biphasic).
In some examples, categorical statements about whether the signal is biphasic or monophasic may drive the analysis. For example, a system could select the least biphasic sensing vector for use in cardiac signal analysis. In other examples shown below, the biphasic nature of the signal is integrated into a variable that is included in the analysis. For example, biphasic-ness may be but one of several signal characteristics brought into consideration when selecting sensing vector(s).
In the illustration of
Bazett's formula, as well as various similar calculations (Fridericia's formula or the regression model from Sagie et al.), can be used to estimate the time at which a T-wave would occur following a QRS complex given a particular rate (Bazett postulates that the ratio of QT interval to the square root of the average R-R interval is fixed for a given patient). If desired, a system may use Bazett's formula or other calculations in combination with the observed cardiac rate to establish a limit on the quantity of signal to analyze for biphasic nature, though generally speaking a fixed window may be simple and fairly reliable.
For example, according to Fridericia's formula, a “normal” QT at 60 beats-per-minute is about 400 milliseconds and the QT interval for the same patient at 180 beats-per-minute (BPM) would be 277 milliseconds, and at 240 bpm, the QT interval would narrow to 251 milliseconds. Since QRS width greater than 120 milliseconds is considered “wide,” a 200 millisecond window allows ample time for the entire QRS complex without bringing T-waves into the analysis.
As noted above, in some alternative examples, the QRS complex plus the T-wave is considered in an assessment of whether a signal is biphasic. In further examples, the entire cardiac cycle may be assessed when determining whether the cardiac signal is biphasic. In another example, the assessment of whether a signal is biphasic is based on comparing the peaks at opposing ends of the longest monotonic segment (a segment lacking turning points is monotonic; here, length is defined as amplitude change) in the refractory (or other) period. The longest monotonic segment is shown at 104 and 114, respectively, in the Vector A and Vector B illustrations of
In some examples, the three factors noted at 102 and 112 are combined to generate an overall quality metric for each of Vector A and Vector B. In one example, each of the three factors is assessed to provide three variables which can be multiplied or summed to yield an overall quality metric. In another example, the three factors are compared to pass/fail boundaries for each metric and if all three factors pass individually, a combined metric is then calculated. When multiplying or summing the three variables, one factor may be more heavily or lightly weighted than the others. The factors may be graded according to a continuum or look-up table, or by use of a polynomial. Additional or different factors may also be used.
For example, U.S. Pat. No. 7,783,340 describes a method of vector selection that generates a pair of scoring factors related to amplitude (Sa) and SNR (Sr). Those factors are then multiplied to generate a total score for a vector. In an illustrative example, a similar approach can be taken to generating Sa and Sr using a polynomial or a look-up table, if desired. In addition, a third factor related to the biphasic nature of the signal can be calculated as Sb. The “score” for a sensing vector can then be calculated as Sa*Sb*Sr, as Sa+Sb+Sr, or, in another example, as (Sa*Sr)+Sb. Other combinations can be used.
In one example, Sa, Sr and Sb are all scaled to values from 1 to 10 and multiplied together to give a result in a range of 1 to 1000. In another example, Sa and Sr again are scaled to values between 1 and 10 and their product has a range of 1 to 100. Sb can be scaled to a range of 0 to 10, but is instead added to the product of Sa and Sr, giving the total outcome a range from 1 to 110. Other scales and scoring methods can be used.
In another example, Sb may be considered only if both Sa and Sr exceed a lower threshold in each of the vectors under consideration, or if the product of Sa and Sr in every vector under consideration meets some threshold. In this version, Sb would be used to distinguish among known “good” vectors, but could not promote a relatively poor vector in terms of amplitude and SNR above other, better vectors for amplitude and SNR. This is in part because, in this example, the monophasic or biphasic signal features provide an advantage for discriminating one arrhythmia from another, but accurate sensing, reliant on SNR and amplitude, is needed to get to the rhythm discrimination stage in the first place.
Numerically, here are certain examples:
In a first example, given an input range of up to 2.5 millivolts (mV), with a sensing floor at 0.1 mV, Sa is ten times the difference between the maximum amplitude (in mV) of the peak in refractory less 0.2 mV (giving a range from 0 to 23); Sr equals thrice the maximum amplitude (in mV) during refractory divided by the maximum peak outside of refractory with a maximum value of 10; and Sb equals ten divided by the difference between the absolute value of the maximum positive and negative peaks during refractory (in mV), with a maximum value of 10; the output “score” of the sensing vector is zero if Sa*Sr is less than 5, and is otherwise equal to the sum of Sb plus Sa*Sr. This first example favors sensing vectors with biphasic signals, as the difference between the absolute values of the positive and negative peaks would be smaller when biphasic making Sb larger.
In a second example, a selectable gain that can accommodate a 1.8 mV maximum signal at X2 gain and a 3.6 mV gain at X1 gain, Sa, Sr and Sb are taken from a lookup table. The vector “score” is the product of Sa*Sr*Sb. The lookup table is as follows, where “Ratio” is calculated as the ratio of the absolute value of the greatest positive amplitude during refractory divided by the greatest negative amplitude during refractory:
In a final set of examples, Sa and Sr are calculated using one or more polynomial formulas as disclosed in U.S. Pat. No. 7,783,340, titled SYSTEMS AND METHODS FOR SENSING VECTOR SELECTION IN AN IMPLANTABLE MEDICAL DEVICE USING A POLYNOMIAL APPROACH, the disclosure of which is incorporated herein by reference. For example, Sa can be calculated according to the formula graphed in
Once SNR and Amplitude data are captured at 152, the amplitude is compared to predefined boundaries at 154, as is the SNR at 156. If boundary conditions are not met, Vector A would fail the analysis, as shown at 158. Provision of separate screening and a failure outcome at 158 can be omitted in some examples. In the illustration shown, the inclusion of blocks 154 and 156 is intended to screen out sensing vectors having unsuitably small or large amplitudes and/or unsuitably low SNR.
After separately assessing amplitude and SNR, the method next generates a combination factor, SNRA, combining features for SNR and Amplitude together, as shown at 160. SNRA is compared to boundary conditions as well, as shown at 162 and, again, the vector may fail 158. In some examples, blocks 160 and 162 are omitted.
Using steps 152 to 162, the overall, general suitability of Sensing Vector A can be assessed. Similar steps would apply as well to Vector B 164, and other vectors 166. Upon finding that a vector is generally suitable for use, the method then proceeds to use biphasic assessments at 170, 172 and/or 174 to further inform the selection of a “best” vector in a comparison step at 176. If desired, boundary conditions to the biphasic nature of the signal may be applied as well, and one or more vectors may fail to reach the comparison at 176 on that basis. In some examples, a single “best” vector may be selected as a default vector for the implantable system. In other examples, two vectors may be selected for use in tiered or cooperative analysis.
In some examples, the “fail” block 158 may be omitted, and all vectors passed to the comparison block 176. In another example, the comparison block 176 may not be reached if a vector under analysis is found to have excellent sensing capabilities, allowing a bypass of additional vector selection analysis once a highly suitable sensing vector has been identified. For implantable systems, the opportunity to bypass further analysis once a “good” vector has been found may allow energy savings.
In addition to the consideration of “Biphasic” nature of the cardiac signal, other factors may be introduced as well or instead, as noted at block 178 of
In another example, beat-to-beat similarity may be incorporated to generate another score. For example, largest peaks for a number of consecutive detected events can be assessed (using, for example, sum of differences, variance or standard deviation, or maximum to minimum largest peak difference), and a score generated from the measure of beat to beat amplitude variation. A sensing vector with greater variability may be disfavored over a sensing vector with less variability. This may be useful, in particular, where sensing vector selection is performed in a controlled environment where the patient is sitting still or where the patient is known to be exercising. The patient may be asked to perform certain tasks (walking, exercise testing such as running, or the Valsalva maneuver, for example), or to breathe deeply during vector analysis to accentuate any such variability.
These additional factors may be assessed, as above, using a formula or a lookup table, as desired. Such factors may be an additional assessment once vector suitability is established, or may be integrated into analysis from the start.
The above methods and systems may be used to perform sensing vector selection of a default or primary sensing vector. A second or alternative sensing vector may also be chosen. In some systems, two sensing vectors are chosen for simultaneous use. In some systems, sensing vector selection may be used to select a “morphology” or far field vector, for use in conjunction with a rate vector, such as in a transvenous system having a rate channel configured to sense the R-wave, with a far field vector being selected from several options to allow discrimination.
Referring briefly again to
The canister 12 preferably contains operational circuitry for the implantable system. The operational circuitry may include a controller and any suitable analog and/or digital circuits needed for signal processing, memory storage and generation of high-power electrical, low-power electrical and/or non-electrical outputs. The operational circuitry may be coupled to suitable battery technology for an implantable device, with any of numerous examples well known in the art, and may use various capacitor technologies to assist in the short term build-up and/or storage of energy for defibrillation or other high output purposes.
The operational circuitry may include, for example, a set of switches, a switch matrix, or a multiplexer, to select inputs from among the various sensing vectors. Before and/or after signals reach the vector-selecting switches, matrix or multiplexer, analog to digital conversion and/or filtering can be applied. One or more vectors may be selected. In one example, the present invention may be used to establish a hierarchy within vectors, such that the system can use a first vector to determine whether a treatable cardiac rhythm is occurring, and turns to additional vectors if a conclusion cannot be reached. In other examples, a single vector is selected. In some examples, multiple vectors can be selected for combination in signal processing, as needed, or for use in other suitable methods.
The lead 14 and external shell for the canister 12 can be manufactured with various materials suitable for implantation, such as those widely known, along with coatings for such materials, throughout the art. For example, the canister 12 can be made using titanium, with a titanium nitride or iridium oxide (or other material) coating if desired, and the lead can be formed with a polymeric material such as a polyether, polyester, polyamide, polyurethane or polycarbonate, or other material such as silicon rubber. The electrodes 16, 18, and 20 can be formed of suitable materials as well, such as silver, gold, titanium or stainless steel such as MP35N stainless steel alloy, or other materials.
The location of system implant may vary. For example, the system shown is a subcutaneous-only system located on the anterior and lateral chest between the skin and ribcage of the patient. Other subcutaneous only systems (including systems without a lead 14, with multiple leads 14, or an array in place of lead 14) may be used with other anterior only placements and/or anterior-posterior, posterior only, left-right, etc. locations, including, for example, locations noted in U.S. Pat. Nos. 6,647,292, 6,721,597, 7,149,575, 7,194,302, each of which is incorporated herein by reference, and other locations as well. Subcutaneous placement can include any location between the skin and ribcage, including sub-muscular.
Other systems may include one or more transvenous leads or epicardial leads/electrodes, and may use different canister implant locations, such as placing the canister in a higher pectoral position closer to the clavicle for closer venous access, or abdominal placement. Illustrative transvenous systems include single chamber, dual chamber and biventricular systems. A fully intravenous system has also been proposed. Additional or other coatings or materials than those noted above may be used, particularly for epicardial, transvenous or intravenous systems, leads and canisters.
Various alternatives and details for these designs, materials and implantation approaches are known to those skilled in the art. Commercially available systems in which the above methods can be performed or which may be configured to perform such methods are known including the Boston Scientific Teligen® ICD and 5-ICD® System, Medtronic Concerto® and Virtuoso® systems, and St. Jude Medical Promote® RF and Current® RF systems.
A first illustrative example takes the form of a method of sensing vector selection in an implantable cardiac device, the implantable cardiac device including electrodes configured for sensing electrical signals while implanted coupled to operational circuitry configured for analyzing signals captured from the sensing electrodes, wherein the operational circuitry and electrodes are configured to define at least two sensing vectors for sensing cardiac signals, the method comprising, for a first sensing vector, the operational circuitry establishing each of: an estimate of signal-to-noise ratio; an estimate of cardiac signal amplitude; and a measure of biphasic or monophasic nature of sensed signals; and the operational circuitry combining the signal to noise ratio, cardiac signal amplitude and measure of biphasic or monophasic nature of sensed signals to generate a sensing quality metric for the first sensing vector.
A second illustrative example builds on the first illustrative example and further comprises, for the first sensing vector, the operational circuitry sensing a plurality of cardiac cycles with selected electrodes by applying a detection profile to a sensed cardiac signal to detect a cardiac cycle, wherein the detection profile includes a refractory period and a sensing period, the refractory period being applied to a first portion of the cardiac cycle and the sensing period being applied to at least a second portion of the cardiac cycle; wherein the step of the operational circuitry establishing an estimate of cardiac signal amplitude comprises the operational circuitry analyzing a sensed amplitude from the first portion of the cardiac cycle for each of several cardiac cycles.
A third illustrative example builds on the first illustrative example and further comprises, for the first sensing vector, the operational circuitry sensing a plurality of cardiac cycles with selected electrodes by applying a detection profile to a sensed cardiac signal to detect a cardiac cycle, wherein the detection profile includes a refractory period and a sensing period, the refractory period being applied to a first portion of the cardiac cycle and the sensing period being applied to at least a second portion of the cardiac cycle; wherein the step of the operational circuitry establishing an estimate of signal to noise ratio includes the operational circuitry comparing a sensed amplitude from the first portion of the cardiac cycle to a sensed amplitude from the second portion of the cardiac cycle for each of several cardiac cycles.
A fourth illustrative example builds on the first illustrative example and further comprises for the first sensing vector, the operational circuitry sensing a plurality of cardiac cycles with selected electrodes by applying a detection profile to a sensed cardiac signal to detect a cardiac cycle, wherein the detection profile includes a refractory period and a sensing period, the refractory period being applied to a first portion of the cardiac cycle and the sensing period being applied to at least a second portion of the cardiac cycle; wherein the step operational circuitry establishing a measure of biphasic or monophasic nature of cardiac cycles comprises the operational circuitry comparing a sensed positive amplitude from the first portion of the cardiac cycle to a sensed negative amplitude from the first portion of the cardiac cycle for each of several cardiac cycles.
A fifth illustrative example builds on the first illustrative example and further comprises, for the first sensing vector, the operational circuitry sensing a plurality of cardiac cycles with selected electrodes by applying a detection profile to a sensed cardiac signal to detect a cardiac cycle, wherein the detection profile includes a refractory period and a sensing period, the refractory period being applied to a first portion of the cardiac cycle and the sensing period being applied to at least a second portion of the cardiac cycle; wherein the step operational circuitry establishing a measure of biphasic or monophasic nature of cardiac cycles comprises the operational circuitry comparing an average sensed positive amplitude from the first portion of several of the cardiac cycles to an average sensed negative amplitude from the first portion of several of the cardiac cycles.
A sixth illustrative example builds on the first illustrative example, wherein the step of the operational circuitry combining the signal to noise ratio, cardiac signal amplitude and measure of biphasic or monophasic nature of cardiac signals to generate a sensing quality metric for the first sensing vector comprises the operational circuitry finding the sum or product of: a first metric related to the signal to noise ratio; a second metric related to the cardiac signal amplitude; and a third metric related to the measure of biphasic or monophasic nature of cardiac signals.
A seventh illustrative example builds upon the first illustrative example, wherein the step of the operational circuitry combining the signal to noise ratio, cardiac signal amplitude and measure of biphasic or monophasic nature of cardiac signals to generate a sensing quality metric for the first sensing vector comprises the operational circuitry establishing a sensing vector score for the first vector using the signal to noise ratio and the cardiac signal amplitude, and adjusting the score in view of the measure of biphasic or monophasic nature of cardiac signals.
An eighth illustrative example builds on the first illustrative example and further comprises, for a second sensing vector, the operational circuitry establishing each of: an estimate of signal-to-noise ratio; an estimate of cardiac signal amplitude; and a measure of biphasic or monophasic nature of sensed signals; and the operational circuitry combining the signal to noise ratio, cardiac signal amplitude and measure of biphasic or monophasic nature of sensed signals to generate a sensing quality metric for the second sensing vector; and the operational circuitry using the sensing quality metrics for the first and second sensing vectors to select from at least the first and second sensing vectors a sensing vector for use in cardiac signal analysis.
A ninth illustrative example takes the form of a method of sensing vector selection in an implantable cardiac device, the implantable cardiac device including electrodes configured for sensing electrical signals while implanted coupled to operational circuitry configured for analyzing signals captured from the sensing electrodes, wherein the operational circuitry and electrodes are configured to define at least two sensing vectors for sensing cardiac signals, the method comprising: for the first sensing vector, the operational circuitry establishing a measure of biphasic or monophasic nature of cardiac signals; the operational circuitry selecting a default sensing vector for use in the analysis of cardiac signals using at least one factor related to the measure of biphasic or monophasic nature of cardiac signals generated for the first sensing vector.
A tenth illustrative example builds on the ninth illustrative example and further comprises the operational circuitry combining the measure of biphasic or monophasic nature of cardiac signals for the first sensing vector with at least one other factor related to the signals captured via the first sensing vector to generate a sensing quality metric for the first sensing vector.
An eleventh illustrative example builds on the ninth illustrative example, wherein the step of establishing a measure of biphasic or monophasic nature of cardiac signals comprises: identifying a QRS portion of a cardiac cycle; and comparing a positive peak in the QRS portion of the cardiac cycle to a negative peak in the QRS portion of the cardiac cycle.
A twelfth illustrative example builds on the ninth illustrative example, wherein the step of establishing a measure of biphasic or monophasic nature of cardiac signals comprises: detecting an event in a signal sensed along the first sensing vector; defining a window associated with the detected event; and comparing a positive peak in the window to a negative peak in the window.
A thirteenth illustrative example takes the form of an implantable cardiac device comprising: a plurality of electrodes configured for sensing electrical signals while implanted; and operational circuitry configured for analyzing signals received from the sensing electrodes. In the thirteenth illustrative example, the operational circuitry and electrodes are configured to define at least two sensing vectors for sensing cardiac signals and the operational circuitry is configured to perform the following: for a first sensing vector, calculating each of: an estimate of signal-to-noise ratio; an estimate of cardiac signal amplitude; and a measure of biphasic or monophasic nature of sensed signals; and combining the signal to noise ratio, cardiac signal amplitude and measure of biphasic or monophasic nature of sensed signals to generate a sensing quality metric for the first sensing vector.
A fourteenth illustrative example builds on the thirteenth illustrative example, wherein the operational circuitry is further configured to sense a plurality of cardiac cycles with selected electrodes for the first vector by applying a detection profile to a sensed cardiac signal to detect a cardiac cycle, wherein the detection profile includes a refractory period and a sensing period, the refractory period being applied to a first portion of the cardiac cycle and the sensing period being applied to at least a second portion of the cardiac cycle; and the operational circuitry is configured to calculate the estimate of cardiac signal amplitude by analyzing a sensed amplitude from the first portion of the cardiac cycle for each of several cardiac cycles.
A fifteenth illustrative example builds on the thirteenth illustrative example, wherein the operational circuitry is further configured to sense a plurality of cardiac cycles with selected electrodes for the first vector by applying a detection profile to a sensed cardiac signal to detect a cardiac cycle, wherein the detection profile includes a refractory period and a sensing period, the refractory period being applied to a first portion of the cardiac cycle and the sensing period being applied to at least a second portion of the cardiac cycle; and the operational circuitry is configured to calculate an estimate of signal to noise ratio by comparing a sensed amplitude from the first portion of the cardiac cycle to a sensed amplitude from the second portion of the cardiac cycle for each of several cardiac cycles.
A sixteenth illustrative example builds on the thirteenth illustrative example, wherein the operational circuitry is further configured to sense a plurality of cardiac cycles with selected electrodes for the first vector by applying a detection profile to a sensed cardiac signal to detect a cardiac cycle, wherein the detection profile includes a refractory period and a sensing period, the refractory period being applied to a first portion of the cardiac cycle and the sensing period being applied to at least a second portion of the cardiac cycle; and the operational is configured to calculate a measure of biphasic or monophasic nature of cardiac cycles by comparing a sensed positive amplitude from the first portion of the cardiac cycle to a sensed negative amplitude from the first portion of the cardiac cycle for each of several cardiac cycles.
A seventeenth illustrative example builds on the thirteenth illustrative example, wherein the operational circuitry is further configured to sense a plurality of cardiac cycles with selected electrodes for the first vector by applying a detection profile to a sensed cardiac signal to detect a cardiac cycle, wherein the detection profile includes a refractory period and a sensing period, the refractory period being applied to a first portion of the cardiac cycle and the sensing period being applied to at least a second portion of the cardiac cycle; and the operational circuitry is configured to calculate a measure of biphasic or monophasic nature of cardiac cycles by comparing an average sensed positive amplitude from the first portion of several of the cardiac cycles to an average sensed negative amplitude from the first portion of several of the cardiac cycles.
An eighteenth illustrative example builds on the thirteenth illustrative example, wherein the operational circuitry is configured to combine the signal to noise ratio, cardiac signal amplitude and measure of biphasic or monophasic nature of cardiac signals to generate a sensing quality metric for the first sensing vector comprises the operational circuitry by finding the sum or product of: a first metric related to the signal to noise ratio; a second metric related to the cardiac signal amplitude; and a third metric related to the measure of biphasic or monophasic nature of cardiac signals.
A nineteenth illustrative example builds on the thirteenth illustrative example, wherein the operational circuitry is configured to combine the signal to noise ratio, cardiac signal amplitude and measure of biphasic or monophasic nature of cardiac signals to generate a sensing quality metric for the first sensing vector comprises the operational circuitry by calculating a sensing vector score for the first vector using the signal to noise ratio and the cardiac signal amplitude, and adjusting the score in view of the measure of biphasic or monophasic nature of cardiac signals.
A twentieth illustrative example builds on the thirteenth illustrative example, wherein the operational circuitry is further configured to perform the following: for a second sensing vector, the operational circuitry calculating each of: an estimate of signal-to-noise ratio; an estimate of cardiac signal amplitude; and a measure of biphasic or monophasic nature of sensed signals; and combining the signal to noise ratio, cardiac signal amplitude and measure of biphasic or monophasic nature of sensed signals to generate a sensing quality metric for the second sensing vector; and using the sensing quality metrics for the first and second sensing vectors to select from at least the first and second sensing vectors a sensing vector for use in cardiac signal analysis.
The above detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show, by way of illustration, specific embodiments in which the invention can be practiced. These embodiments are also referred to herein as “examples.” Such examples can include elements in addition to those shown or described. However, the present inventors also contemplate examples in which only those elements shown or described are provided. Moreover, the present inventors also contemplate examples using any combination or permutation of those elements shown or described (or one or more aspects thereof), either with respect to a particular example (or one or more aspects thereof), or with respect to other examples (or one or more aspects thereof) shown or described herein.
In the event of inconsistent usages between this document and any documents so incorporated by reference, the usage in this document controls.
In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one, independent of any other instances or usages of “at least one” or “one or more.” In this document, the term “or” is used to refer to a nonexclusive or, such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. In this document, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Also, in the following claims, the terms “including” and “comprising” are open-ended, that is, a system, device, article, composition, formulation, or process that includes elements in addition to those listed after such a term in a claim are still deemed to fall within the scope of that claim. Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects.
Method examples described herein can be machine or computer-implemented at least in part. Some examples can include a computer-readable medium or machine-readable medium encoded with instructions operable to configure an electronic device to perform methods as described in the above examples. An implementation of such methods can include code, such as microcode, assembly language code, a higher-level language code, or the like. Such code can include computer readable instructions for performing various methods. The code may form portions of computer program products. Further, in an example, the code can be tangibly stored on one or more volatile, non-transitory, or non-volatile tangible computer-readable media, such as during execution or at other times. Examples of these tangible computer-readable media can include, but are not limited to, hard disks, removable magnetic disks, removable optical disks (e.g., compact disks and digital video disks), magnetic cassettes, memory cards or sticks, random access memories (RAMs), read only memories (ROMs), and the like.
The above description is intended to be illustrative, and not restrictive. For example, the above-described examples (or one or more aspects thereof) may be used in combination with each other. Other embodiments can be used, such as by one of ordinary skill in the art upon reviewing the above description. The Abstract is provided to comply with 37 C.F.R. §1.72(b), to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Also, in the above Detailed Description, various features may be grouped together to streamline the disclosure. This should not be interpreted as intending that an unclaimed disclosed feature is essential to any claim. Rather, inventive subject matter may lie in less than all features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that such embodiments can be combined with each other in various combinations or permutations. The scope of the invention should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.
The present application claims the benefit of and priority to U.S. Provisional Patent Application No. 61/777,843, filed Mar. 12, 2013, the disclosure of which is incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
3653387 | Ceier | Apr 1972 | A |
3710374 | Kelly | Jan 1973 | A |
3911925 | Tillery, Jr. | Oct 1975 | A |
4030509 | Heilman et al. | Jun 1977 | A |
4157720 | Greatbatch | Jun 1979 | A |
4164946 | Langer | Aug 1979 | A |
4184493 | Langer et al. | Jan 1980 | A |
4191942 | Long | Mar 1980 | A |
4210149 | Heilman et al. | Jul 1980 | A |
RE30387 | Denniston, III et al. | Aug 1980 | E |
4223678 | Langer et al. | Sep 1980 | A |
4248237 | Kenny | Feb 1981 | A |
4254775 | Langer | Mar 1981 | A |
4291707 | Heilman et al. | Sep 1981 | A |
4300567 | Kolenik et al. | Nov 1981 | A |
4314095 | Moore et al. | Feb 1982 | A |
4375817 | Engle et al. | Mar 1983 | A |
4402322 | Duggan | Sep 1983 | A |
4407288 | Langer et al. | Oct 1983 | A |
4424818 | Doring et al. | Jan 1984 | A |
4450527 | Sramek | May 1984 | A |
4548209 | Wielders et al. | Oct 1985 | A |
4550502 | Grayzel | Nov 1985 | A |
4567900 | Moore | Feb 1986 | A |
4589420 | Adams et al. | May 1986 | A |
4595009 | Leinders | Jun 1986 | A |
4602637 | Elmqvist et al. | Jul 1986 | A |
4603705 | Speicher et al. | Aug 1986 | A |
4693253 | Adams | Sep 1987 | A |
4727877 | Kallok | Mar 1988 | A |
4750494 | King | Jun 1988 | A |
4765341 | Mower et al. | Aug 1988 | A |
4768512 | Imran | Sep 1988 | A |
4779617 | Whigham | Oct 1988 | A |
4800883 | Winstrom | Jan 1989 | A |
4830005 | Woskow | May 1989 | A |
4944300 | Saksena | Jul 1990 | A |
4960126 | Conlon et al. | Oct 1990 | A |
5044374 | Lindemans et al. | Sep 1991 | A |
5105810 | Collins et al. | Apr 1992 | A |
5105826 | Smits et al. | Apr 1992 | A |
5109842 | Adinolfi | May 1992 | A |
5129392 | Bardy et al. | Jul 1992 | A |
5133353 | Hauser | Jul 1992 | A |
5137025 | Turner, II | Aug 1992 | A |
5144946 | Weinberg et al. | Sep 1992 | A |
5184616 | Weiss | Feb 1993 | A |
5191901 | Dahl et al. | Mar 1993 | A |
5193550 | Duffin | Mar 1993 | A |
5203348 | Dahl et al. | Apr 1993 | A |
5215081 | Ostroff | Jun 1993 | A |
5230337 | Dahl et al. | Jul 1993 | A |
5255692 | Neubauer et al. | Oct 1993 | A |
5261400 | Bardy | Nov 1993 | A |
5271411 | Ripley et al. | Dec 1993 | A |
5291895 | McIntyre | Mar 1994 | A |
5299119 | Kraf et al. | Mar 1994 | A |
5300106 | Dahl et al. | Apr 1994 | A |
5313953 | Yomtov et al. | May 1994 | A |
5331966 | Bennett et al. | Jul 1994 | A |
5342407 | Dahl et al. | Aug 1994 | A |
5366496 | Dahl et al. | Nov 1994 | A |
5370667 | Alt | Dec 1994 | A |
5376103 | Anderson et al. | Dec 1994 | A |
5376104 | Sakai et al. | Dec 1994 | A |
5385574 | Hauser et al. | Jan 1995 | A |
5391200 | KenKnight et al. | Feb 1995 | A |
5405363 | Kroll et al. | Apr 1995 | A |
5411031 | Yomtov | May 1995 | A |
5411539 | Neisz | May 1995 | A |
5411547 | Causey, III | May 1995 | A |
5413591 | Knoll | May 1995 | A |
5423326 | Wang et al. | Jun 1995 | A |
5431693 | Schroeppel | Jul 1995 | A |
5439485 | Mar et al. | Aug 1995 | A |
5441518 | Adams et al. | Aug 1995 | A |
5447521 | Anderson et al. | Sep 1995 | A |
5464431 | Adams et al. | Nov 1995 | A |
5476503 | Yang | Dec 1995 | A |
5486199 | Kim et al. | Jan 1996 | A |
5501702 | Plicchi et al. | Mar 1996 | A |
5509923 | Middleman et al. | Apr 1996 | A |
5509928 | Acken | Apr 1996 | A |
5522852 | White et al. | Jun 1996 | A |
5531765 | Pless | Jul 1996 | A |
5531766 | Kroll et al. | Jul 1996 | A |
5534019 | Paspa | Jul 1996 | A |
5534022 | Hoffmann et al. | Jul 1996 | A |
5540727 | Tockman et al. | Jul 1996 | A |
5558098 | Fain | Sep 1996 | A |
5597956 | Ito et al. | Jan 1997 | A |
5601607 | Adams | Feb 1997 | A |
5603732 | Dahl et al. | Feb 1997 | A |
5607455 | Armstrong | Mar 1997 | A |
5618287 | Fogarty et al. | Apr 1997 | A |
5620477 | Pless et al. | Apr 1997 | A |
5643328 | Cooke et al. | Jul 1997 | A |
5645070 | Turcott | Jul 1997 | A |
5645586 | Meltzer | Jul 1997 | A |
5658317 | Haefner et al. | Aug 1997 | A |
5658319 | Kroll | Aug 1997 | A |
5658321 | Fayram et al. | Aug 1997 | A |
5674260 | Weinberg | Oct 1997 | A |
5690648 | Fogarty et al. | Nov 1997 | A |
5690683 | Haefner et al. | Nov 1997 | A |
5697953 | Kroll et al. | Dec 1997 | A |
5707398 | Lu | Jan 1998 | A |
5709215 | Perttu et al. | Jan 1998 | A |
5713926 | Hauser et al. | Feb 1998 | A |
5755738 | Kim et al. | May 1998 | A |
5766226 | Pedersen | Jun 1998 | A |
5776169 | Schroeppel | Jul 1998 | A |
5814090 | Latterell et al. | Sep 1998 | A |
5827197 | Bocek et al. | Oct 1998 | A |
5827326 | Kroll et al. | Oct 1998 | A |
5836976 | Min et al. | Nov 1998 | A |
5843132 | Ilvento | Dec 1998 | A |
5895414 | Sanchez-Zambrano | Apr 1999 | A |
5904705 | Kroll et al. | May 1999 | A |
5919211 | Adams | Jul 1999 | A |
5919222 | Hjelle et al. | Jul 1999 | A |
5925069 | Graves et al. | Jul 1999 | A |
5935154 | Westlund | Aug 1999 | A |
5941904 | Johnston et al. | Aug 1999 | A |
5957956 | Kroll et al. | Sep 1999 | A |
5987352 | Klein et al. | Nov 1999 | A |
5991657 | Kim | Nov 1999 | A |
5999853 | Stoop et al. | Dec 1999 | A |
6014586 | Weinberg et al. | Jan 2000 | A |
6016442 | Hsu et al. | Jan 2000 | A |
6026325 | Weinberg et al. | Feb 2000 | A |
6029086 | Kim et al. | Feb 2000 | A |
6041251 | Kim et al. | Mar 2000 | A |
6044297 | Sheldon et al. | Mar 2000 | A |
6047210 | Kim et al. | Apr 2000 | A |
6052617 | Kim | Apr 2000 | A |
6058328 | Levine et al. | May 2000 | A |
6093173 | Balceta et al. | Jul 2000 | A |
6095987 | Shmulewitz et al. | Aug 2000 | A |
6115628 | Stadler et al. | Sep 2000 | A |
H1905 | Hill | Oct 2000 | H |
6128531 | Campbell-smith | Oct 2000 | A |
6144866 | Miesel et al. | Nov 2000 | A |
6144879 | Gray | Nov 2000 | A |
6148230 | Kenknight | Nov 2000 | A |
6185450 | Seguine et al. | Feb 2001 | B1 |
6190324 | Kieval et al. | Feb 2001 | B1 |
6236882 | Lee et al. | May 2001 | B1 |
6266554 | Hsu et al. | Jul 2001 | B1 |
6266567 | Ishikawa et al. | Jul 2001 | B1 |
6278894 | Salo et al. | Aug 2001 | B1 |
6280462 | Hauser et al. | Aug 2001 | B1 |
6308095 | Hsu et al. | Oct 2001 | B1 |
6312388 | Marcovecchio et al. | Nov 2001 | B1 |
6334071 | Lu | Dec 2001 | B1 |
6345198 | Mouchawar et al. | Feb 2002 | B1 |
6377844 | Graen | Apr 2002 | B1 |
6381493 | Stadler et al. | Apr 2002 | B1 |
6411844 | Kroll et al. | Jun 2002 | B1 |
6490486 | Bradley | Dec 2002 | B1 |
6493579 | Gilkerson et al. | Dec 2002 | B1 |
6493584 | Lu | Dec 2002 | B1 |
6496715 | Lee et al. | Dec 2002 | B1 |
6516225 | Florio | Feb 2003 | B1 |
6539257 | KenKnight | Mar 2003 | B1 |
6567691 | Stadler | May 2003 | B1 |
6574505 | Warren | Jun 2003 | B1 |
6587720 | Hsu et al. | Jul 2003 | B2 |
6625490 | McClure et al. | Sep 2003 | B1 |
6636762 | Begemann | Oct 2003 | B2 |
6647292 | Bardy et al. | Nov 2003 | B1 |
6658292 | Kroll et al. | Dec 2003 | B2 |
6658293 | Vonk | Dec 2003 | B2 |
6684100 | Sweeney et al. | Jan 2004 | B1 |
6687540 | Marcovecchio | Feb 2004 | B2 |
6699200 | Cao et al. | Mar 2004 | B2 |
6708058 | Kim et al. | Mar 2004 | B2 |
6708062 | Ericksen et al. | Mar 2004 | B2 |
6721597 | Bardy et al. | Apr 2004 | B1 |
6728572 | Hsu et al. | Apr 2004 | B2 |
6728575 | Hedberg | Apr 2004 | B2 |
6731978 | Olson et al. | May 2004 | B2 |
6738667 | Deno et al. | May 2004 | B2 |
6745076 | Wohlgemuth et al. | Jun 2004 | B2 |
6751502 | Daum et al. | Jun 2004 | B2 |
6754528 | Bardy et al. | Jun 2004 | B2 |
6760615 | Ferek-Petric | Jul 2004 | B2 |
6766190 | Ferek-Petric | Jul 2004 | B2 |
6778860 | Ostroff et al. | Aug 2004 | B2 |
6788974 | Bardy et al. | Sep 2004 | B2 |
6810284 | Bradley | Oct 2004 | B1 |
6834204 | Ostroff et al. | Dec 2004 | B2 |
6856835 | Bardy et al. | Feb 2005 | B2 |
6865417 | Rissmann et al. | Mar 2005 | B2 |
6866044 | Bardy et al. | Mar 2005 | B2 |
6889079 | Bocek et al. | May 2005 | B2 |
6892092 | Palreddy et al. | May 2005 | B2 |
6909916 | Spinelli et al. | Jun 2005 | B2 |
6927721 | Ostroff | Aug 2005 | B2 |
6937907 | Bardy et al. | Aug 2005 | B2 |
6950705 | Bardy et al. | Sep 2005 | B2 |
6952608 | Ostroff | Oct 2005 | B2 |
6952610 | Ostroff et al. | Oct 2005 | B2 |
6954670 | Ostroff | Oct 2005 | B2 |
6959212 | Hsu et al. | Oct 2005 | B2 |
6975904 | Sloman | Dec 2005 | B1 |
6980856 | Sullivan et al. | Dec 2005 | B2 |
6988003 | Bardy et al. | Jan 2006 | B2 |
6993379 | Kroll et al. | Jan 2006 | B1 |
6996434 | Marcovecchio et al. | Feb 2006 | B2 |
7016730 | Ternes | Mar 2006 | B2 |
7020523 | Lu et al. | Mar 2006 | B1 |
7027858 | Cao et al. | Apr 2006 | B2 |
7027862 | Dahl et al. | Apr 2006 | B2 |
7031764 | Schwartz et al. | Apr 2006 | B2 |
7039459 | Bardy et al. | May 2006 | B2 |
7039463 | Marcovecchio | May 2006 | B2 |
7039465 | Bardy et al. | May 2006 | B2 |
7043299 | Erlinger et al. | May 2006 | B2 |
7062329 | Ostroff et al. | Jun 2006 | B2 |
7065407 | Bardy et al. | Jun 2006 | B2 |
7065410 | Bardy et al. | Jun 2006 | B2 |
7069080 | Bardy et al. | Jun 2006 | B2 |
7076294 | Bardy et al. | Jul 2006 | B2 |
7076296 | Bardy et al. | Jul 2006 | B2 |
7085599 | Kim et al. | Aug 2006 | B2 |
7090682 | Sanders et al. | Aug 2006 | B2 |
7092754 | Bardy et al. | Aug 2006 | B2 |
7120495 | Bardy et al. | Oct 2006 | B2 |
7120496 | Bardy et al. | Oct 2006 | B2 |
7130689 | Turcott | Oct 2006 | B1 |
7146212 | Bardy et al. | Dec 2006 | B2 |
7149575 | Ostroff et al. | Dec 2006 | B2 |
7162301 | Kim et al. | Jan 2007 | B2 |
7167747 | Gunderson et al. | Jan 2007 | B2 |
7177689 | Ternes et al. | Feb 2007 | B2 |
7181274 | Rissmann et al. | Feb 2007 | B2 |
7181281 | Kroll | Feb 2007 | B1 |
7184818 | Kim et al. | Feb 2007 | B2 |
7191004 | Kim et al. | Mar 2007 | B2 |
7194302 | Bardy et al. | Mar 2007 | B2 |
7248921 | Palreddy et al. | Jul 2007 | B2 |
7266409 | Gunderson | Sep 2007 | B2 |
7330757 | Ostroff et al. | Feb 2008 | B2 |
7366569 | Belalcazar | Apr 2008 | B2 |
7379772 | Bardy et al. | May 2008 | B2 |
7392085 | Warren et al. | Jun 2008 | B2 |
7412287 | Yonce et al. | Aug 2008 | B2 |
7623909 | Sanghera et al. | Nov 2009 | B2 |
7627367 | Warren et al. | Dec 2009 | B2 |
7783340 | Sanghera et al. | Aug 2010 | B2 |
8200341 | Sanghera et al. | Jun 2012 | B2 |
8483843 | Sanghera et al. | Jul 2013 | B2 |
8565878 | Allavatam et al. | Oct 2013 | B2 |
20010027330 | Sullivan et al. | Oct 2001 | A1 |
20010034487 | Cao et al. | Oct 2001 | A1 |
20020035377 | Bardy et al. | Mar 2002 | A1 |
20020035378 | Bardy et al. | Mar 2002 | A1 |
20020035379 | Bardy et al. | Mar 2002 | A1 |
20020035381 | Bardy et al. | Mar 2002 | A1 |
20020095184 | Bardy et al. | Jul 2002 | A1 |
20020107544 | Ostroff et al. | Aug 2002 | A1 |
20020107545 | Rissmann et al. | Aug 2002 | A1 |
20020165587 | Zhang et al. | Nov 2002 | A1 |
20020169484 | Mathis et al. | Nov 2002 | A1 |
20030083710 | Ternes et al. | May 2003 | A1 |
20030088277 | Ostroff | May 2003 | A1 |
20030144700 | Brown et al. | Jul 2003 | A1 |
20030191500 | Stokes et al. | Oct 2003 | A1 |
20030204215 | Gunderson et al. | Oct 2003 | A1 |
20040064162 | Manrodt et al. | Apr 2004 | A1 |
20040088018 | Sawchuk | May 2004 | A1 |
20040215240 | Lovett et al. | Oct 2004 | A1 |
20040230229 | Lovett et al. | Nov 2004 | A1 |
20040230243 | Haefner et al. | Nov 2004 | A1 |
20040230249 | Haefner | Nov 2004 | A1 |
20040236379 | Bardy et al. | Nov 2004 | A1 |
20040254611 | Palreddy et al. | Dec 2004 | A1 |
20040254613 | Ostroff et al. | Dec 2004 | A1 |
20050004613 | Zhang et al. | Jan 2005 | A1 |
20050004615 | Sanders | Jan 2005 | A1 |
20050049644 | Warren et al. | Mar 2005 | A1 |
20050192505 | Ostroff et al. | Sep 2005 | A1 |
20050192507 | Warren et al. | Sep 2005 | A1 |
20050203581 | Spinelli et al. | Sep 2005 | A1 |
20050245976 | Wang | Nov 2005 | A1 |
20060036288 | Bocek et al. | Feb 2006 | A1 |
20060052830 | Spinelli et al. | Mar 2006 | A1 |
20060079796 | Marcovecchio et al. | Apr 2006 | A1 |
20060085038 | Linder et al. | Apr 2006 | A1 |
20060116595 | Palreddy et al. | Jun 2006 | A1 |
20060116730 | Gunderson | Jun 2006 | A1 |
20060122676 | Ko et al. | Jun 2006 | A1 |
20060161205 | Mitrani et al. | Jul 2006 | A1 |
20060167502 | Haefner | Jul 2006 | A1 |
20060173498 | Banville et al. | Aug 2006 | A1 |
20060235476 | Gunderson et al. | Oct 2006 | A1 |
20060241512 | Kwok et al. | Oct 2006 | A1 |
20060247694 | Dong | Nov 2006 | A1 |
20070123947 | Wenger et al. | May 2007 | A1 |
20070232944 | Ghanem et al. | Oct 2007 | A1 |
20070232945 | Kleckner et al. | Oct 2007 | A1 |
20070232948 | Stadler et al. | Oct 2007 | A1 |
20070233196 | Stadler et al. | Oct 2007 | A1 |
20070233198 | Ghanem et al. | Oct 2007 | A1 |
20070239044 | Ghanem et al. | Oct 2007 | A1 |
20070239045 | Ghanem et al. | Oct 2007 | A1 |
20070239046 | Ghanem et al. | Oct 2007 | A1 |
20070239047 | Ghanem et al. | Oct 2007 | A1 |
20070239048 | Ghanem et al. | Oct 2007 | A1 |
20070239049 | Ghanem et al. | Oct 2007 | A1 |
20070239050 | Ghanem et al. | Oct 2007 | A1 |
20070239051 | Ghanem et al. | Oct 2007 | A1 |
20070239220 | Greenhut et al. | Oct 2007 | A1 |
20070270704 | Ghanem et al. | Nov 2007 | A1 |
20070276445 | Sanghera et al. | Nov 2007 | A1 |
20070276447 | Sanghera et al. | Nov 2007 | A1 |
20070276452 | Sanghera et al. | Nov 2007 | A1 |
20080188901 | Sanghera et al. | Aug 2008 | A1 |
20080243025 | Holmstrom et al. | Oct 2008 | A1 |
20080269813 | Greenhut | Oct 2008 | A1 |
20080275521 | Warren et al. | Nov 2008 | A1 |
20090093731 | Palreddy et al. | Apr 2009 | A1 |
20120245651 | Sanghera et al. | Sep 2012 | A1 |
20130274822 | Sanghera et al. | Oct 2013 | A1 |
Number | Date | Country |
---|---|---|
2008252063 | Sep 2011 | AU |
2004261227 | Aug 2012 | AU |
29801807 | Jun 1998 | DE |
0095727 | Dec 1983 | EP |
0316616 | May 1989 | EP |
0316616 | May 1989 | EP |
0347353 | Dec 1989 | EP |
0517494 | Dec 1992 | EP |
0517494 | Dec 1992 | EP |
0518599 | Dec 1992 | EP |
0518599 | Dec 1992 | EP |
0536873 | Dec 1992 | EP |
0517494 | Mar 1993 | EP |
0536873 | Apr 1993 | EP |
0586858 | Mar 1994 | EP |
0586858 | Mar 1994 | EP |
0627237 | Dec 1994 | EP |
0641573 | Mar 1995 | EP |
0641573 | Mar 1995 | EP |
0677301 | Oct 1995 | EP |
0813889 | Dec 1997 | EP |
0917887 | May 1999 | EP |
0923130 | Jun 1999 | EP |
1000634 | May 2000 | EP |
1184050 | Mar 2002 | EP |
1745741 | Jan 2007 | EP |
WO-9319809 | Oct 1993 | WO |
WO-9729802 | Aug 1997 | WO |
WO-9825349 | Jun 1998 | WO |
WO-9903534 | Jan 1999 | WO |
WO-9937362 | Jul 1999 | WO |
WO-9948554 | Sep 1999 | WO |
WO-9953991 | Oct 1999 | WO |
WO-0222208 | Mar 2000 | WO |
WO-0041766 | Jul 2000 | WO |
WO-0050120 | Aug 2000 | WO |
WO-0143649 | Jun 2001 | WO |
WO-0156166 | Aug 2001 | WO |
WO-0222208 | Mar 2002 | WO |
WO-0224275 | Mar 2002 | WO |
WO-0224275 | May 2002 | WO |
WO-02068046 | Sep 2002 | WO |
WO-03018121 | Mar 2003 | WO |
WO-03020367 | Mar 2003 | WO |
WO-03065613 | Aug 2003 | WO |
WO-2004091720 | Oct 2004 | WO |
WO-2004105871 | Dec 2004 | WO |
WO-2004108212 | Dec 2004 | WO |
WO-2007089959 | Aug 2007 | WO |
WO-2007140207 | Dec 2007 | WO |
WO-2007140209 | Dec 2007 | WO |
WO-2007140209 | Dec 2007 | WO |
WO-2007140214 | Dec 2007 | WO |
Entry |
---|
Bardy, Gust H, et al., “Multicenter Experience with a Pectoral Unipolar Implantable Cardioverter-Defibrillator”, JACC, vol. 28, No. 2, (Aug. 1996), 400-410. |
Burri, et al., “Utility of the Surface ECG Before VDD Pacemaker Implantation”, International Journal of Cardiology, vol. 117, No. 2, (Apr. 25, 2007), 211-213. |
Chrysostomakis, et al., “Implantable Loop Recorder Undersensing Mimicking Complete Heart Block”, Europace; vol. 4, No. 2, (2002), 211-213. |
Chrysostomakis, et al., “Sensing Issues Related to the Clinical Use of Implantable Loop Recorders”, Europace; vol. 5, No. 2, (2003), 143-148. |
Friedman, Richard A, et al., “Implantable Defibrillators in Children: From Whence to Shock”, Journal of Cardiovascular Electrophysiology, vol. 12, No. 3, (Mar. 2001), 361-362. |
Ge, Dingfei, et al., “Cardiac Arrhythmia Classification Using Autoregressive Modeling”, BioMedical Engineering OnLine, [Online]. Retrieved from the Internet: <http://www.biomedical-engineering-online.com>, (Nov. 13, 2002), 12 pgs. |
Gradaus, Rainer, et al., “Nonthoracotomy Implantable Cardioverter Defibrillator Placement in Children: Use of Subcutaneous Array Leads and Abdominally Placed Implantable Cardioverter Defibrillators in Children”, Journal of Cardiovascular Electrophysiology, 12(3), (Mar. 2001), 356-360. |
Higgins, Steven L, et al., “The First Year Experience with the Dual Chamber ICD”, Pace, vol. 23, (Jan. 18-25, 2000). |
Mirowski, M, et al., “Automatic Detection and Defibrillation of Lethal Arrhythmias—A New Concept”, JAMA, vol. 213, No. 4, (Jul. 27, 1970), 615-616. |
Olson, Walter H, et al., “Onset and Stability for Ventricular Tachyarrhythmia Detection in an Implantable Pacer-Cardioverter-Defibrillator”, IEEE, (1987), 167-170. |
Schuder, John C, “Completely Implanted Defibrillator”, JAMA, vol. 214, No. 6, (Nov. 9, 1970), 1123 pg. |
Schuder, John C, et al., “Experimental Ventricular Defibrillation with an Automatic and Completely Implanted System”, Trans. Am. Soc. Artif. Int. Organs, vol. 16, (1970), 207-212. |
Schuder, John C, et al., “Standby Implanted Defibrillators”, Arch Intern. Med, vol. 127, (Feb. 1971), 317 pg. |
Schuder, John C, “The Role of an Engineering Oriented Medical Research Group in Developing Improved Methods & Devices for Achieving Ventricular Defibrillation: The University of Missouri Experience”, PACE, vol. 16, Part I, (Jan. 1993), 95-124. |
Schuder, John C, et al., “Transthoracic Ventricular Defibrillation in the Dog with Truncated and Untruncated Exponential Stimuli”, IEEE Trans. on Bio-Medical Engin., vol. BME-18, No. 6, (Nov. 1971), 410-415. |
Schwake, H., et al., “Komplikationen mit Sonden bei 340 Patienten mit einem implantierbaren Kardioverter/Defibrilator”, Z Kardiol, vol. 88, No. 8, (1999), 559-565. |
Throne, Robert D, et al., “A Comparison of Four New Time-Domain Techniques for Discriminating Monomorphic Ventricular Tachycardia from Sinus Rhythm Using Ventricular Waveform Morphology”, IEEE Transactions on Biomedical Engineering, vol. 38, No. 6, (Jun. 1991), 561-570. |
Tietze, U, et al., “Halbleiter-Schaltungstechnik”, © Springer-Verlag (Berlin, Germany), (1991), 784-786. |
Valenzuela, Terrence D, et al., “Outcomes of Rapid Defibrillation by Security Officers After Cardiac Arrest in Casinos”, The New England Journal of Medicine, vol. 343, No. 17, (Oct. 26, 2000), 1206-1209. |
Walters, R A, et al., “Analog to Digital Conversion Techniques in Implantable Devices”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 13, No. 4, (1991), 1674-1676. |
Number | Date | Country | |
---|---|---|---|
20140275917 A1 | Sep 2014 | US |
Number | Date | Country | |
---|---|---|---|
61777843 | Mar 2013 | US |