CARDIAC RATE TRACKING IN AN IMPLANTABLE MEDICAL DEVICE

• US 20160045131A1
• Filed: 08/06/2015
• Published: 02/18/2016
• Est. Priority Date: 08/18/2014
• Status: Active Grant

• Current Assignee: Cameron Health Inc (Boston Scientific Corporation)
• Original Assignee: Cameron Health Inc (Boston Scientific Corporation)
• Inventors: Siejko, Krzysztof Z.
• Granted Patent: US 9,451,892 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/287 Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/341 Vectorcardiography [VCG]
• CPC Class Codes: A61B 5/35 by template matching
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61N 1/3704 Circuits specially adapted therefor, e.g. for sensitivity control
• CPC Class Codes: A61N 1/3925 Monitoring; Protecting
• CPC Class Codes: A61N 1/3956 Implantable devices for applying electric shocks to the heart, e.g. for cardioversion
• CPC Class Codes: A61N 1/3987 characterised by the timing or triggering of the shock
• CPC Class Codes: G06F 17/11 for solving equations , e.g. nonlinear equations, general mathematical optimization problems optimization specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 17/16 Matrix or vector computation , e.g. matrix-matrix or matrix-vector multiplication, matrix factorization matrix transposition G06F7/78
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

Self-correlation enhancements and implementations are described. In particular, certain examples demonstrate the use of a tracking mechanism to identify and/or confirm cardiac rate using data from iterative self-correlation performed at intervals over time. This may enable the interpolation of cardiac rate in an implantable medical device when data is insufficient, and may provide confidence in cardiac rate analyses.

Claims

1. A method of operation in an implantable cardiac device comprising:

analyzing cardiac data using a rate estimation method iteratively over time to yield a series of cardiac rate estimates;

determining that the series of cardiac rate estimates establishing a first cardiac rate track; and

following establishment of the first cardiac rate track, attempting a particular iteration of the rate estimation method and;

determining that the cardiac data of the particular iteration fails to provide a cardiac rate; and

interpolating a cardiac rate estimate using the first track.

2. The method of claim 1 wherein the rate estimation method comprises:

establishing a buffer of cardiac data including a quantity of data samples;

iteratively comparing at least a portion of the buffer of cardiac data to itself by shifting the quantity of data samples across the buffer to yield a function having peaks;

analyzing the peaks to determine whether any of the peaks alone represent a match of sufficient similarity to yield a reliable RR Estimate;

analyzing the peaks to determine whether any combination of peaks represent a match of sufficient regularity to yield a reliable RR Estimate; and

if either analysis of the peaks yields a reliable RR Estimate, determining an RR Estimate;

wherein, for the particular iteration, neither analysis of the peaks yields a reliable RR estimate.

3. The method of claim 1 wherein the step of interpolating a cardiac rate further requires that the rate estimation method identify a possible cardiac rate matching the first track.

4. The method of claim 1 wherein the implantable medical device is an implantable defibrillator.

5. The method of claim 4 wherein the implantable medical device comprises a plurality of electrodes disposed on a lead and a canister housing operational circuitry for the device, the canister being a conductive container usable for sensing cardiac signals, and in which the plurality of electrodes are coupled to the operational circuitry by coupling the lead to the canister such that the operational circuitry can obtain the cardiac data from electrical signals captured by the electrodes and/or conductive housing.

6. A method of cardiac signal analysis in an implantable medical device system comprising a plurality of electrodes for sensing cardiac signals coupled to operational circuitry configured to analyze signals generated by the plurality of electrodes, the method comprising:

sensing cardiac signals using the plurality of electrodes;

iteratively performing a self-correlation to generate a self-correlation function using the sensed cardiac signals;

for a plurality of iterations of the self-correlation, identifying peaks in the self-correlation function to yield a first estimate of cardiac rate and first affiliated confidence having ratings of at least low or high confidence, except if no peak can be identified sufficient to yield an estimate of cardiac rate;

tracking peaks and cardiac rate estimates generated by the identifying peaks step over time to yield a second estimate of cardiac rate with second affiliated confidence having ratings of at least low, medium or high confidence, in which the second estimate of cardiac rate may or may not match the first estimate of cardiac rate; and

using the first and second estimated cardiac rates and affiliated first and second confidences to decide whether a cardiac therapy is warranted.

7. A method as in claim 6 wherein the step of tracking peaks and cardiac rate estimates includes determining whether a quantity of first estimates of cardiac rate are similar to one another and, if so, to declaring a first rate track.

8. A method as in claim 7 wherein, following declaration of the first rate track, the tracking step includes determining whether, in a subsequent iteration, a first estimate of cardiac rate meets a rule associated with the first rate track, and, if so, reporting the second estimate of cardiac rate as a rate equal to the first estimate of cardiac rate, and with a high confidence.

9. A method as in claim 7 wherein:

during iterations of the step of identifying peaks, in addition to reporting the first estimate of cardiac rate, one or more possible cardiac rates are identified by analysis of the self-correlation function;

following declaration of the first rate track, the tracking step includes determining whether, in a subsequent iteration;

a) a first estimate of cardiac rate does not meet a rule associated with the first rate track, and

b) no possible cardiac rate identified by analysis of the self-correlation meets the rule associated with the first rate track, either;

then, if both a) and b) are true, the tracking step includes reporting a second estimate of cardiac rate which is both unequal to the first estimate of cardiac rate and falls within the first rate track, with a low second affiliated confidence, unless a condition indicating the first rate track is no longer valid is met.

10. A method as in claim 9 wherein a condition indicating the first rate track is not longer valid is met if both a) and b) remain true for at least a predetermined quantity of consecutive iterations.

11. A method as in claim 7 wherein:

during iterations of the step of identifying peaks, in addition to reporting the first estimate of cardiac rate, one or more possible cardiac rates are identified by analysis of the self-correlation function;

following declaration of the first rate track, the tracking step includes determining whether, in a subsequent iteration;

a) a first estimate of cardiac rate does not meet a rule associated with the first rate track, and

b) a possible cardiac rate identified by analysis of the self-correlation function does meet the rule associated with the first rate track;

then, if both a) and b) are true, the tracking step includes reporting a second estimate of cardiac rate which is unequal to the first estimate of cardiac rate and instead matches the possible cardiac rate used in b), with a medium confidence.

12. A method as in claim 7 further comprising determining that the first rate track is no longer valid if no first estimate of cardiac rate meets a rule associated with the first rate track for a predetermined period of time or number of iterations.

13. A method as in claim 7 further comprising identifying a jump from the first rate track to a second rate track if, over a series of iterations, at least a predetermined number of first estimates of cardiac rate are similar to one another and do not meet a rule associated with the first rate track.

14. A method as in claim 6 further comprising:

comparing a detection threshold to the sensed cardiac signals to identify individual cardiac cycles and generate a third estimate of cardiac rate;

wherein the step of using the first and second estimated cardiac rates and affiliated first and second confidences to decide whether a cardiac therapy is warranted further comprises;

determining which of the first, second and third estimated cardiac rates is likely the most reliable, and

using the likely most reliable estimated cardiac rate to decide whether a cardiac therapy is warranted.

15. A method of cardiac signal analysis in an implantable medical device system comprising a plurality of electrodes for sensing cardiac signals coupled to operational circuitry configured to analyze signals generated by the plurality of electrodes, the method comprising:

sensing cardiac signals using the plurality of electrodes;

iteratively performing a self-correlation to generate a self-correlation function using the sensed cardiac signals;

for a plurality of iterations of the self-correlation, identifying peaks in the self-correlation function to yield a first estimate of cardiac rate and one or more possible cardiac rates, except if no peak can be identified sufficient to yield an estimate of cardiac rate;

tracking peaks and cardiac rate estimates generated by the identifying peaks step over time to yield a second estimate of cardiac rate with an affiliated confidence having ratings of at least low, medium or high confidence; and

using the second estimated cardiac rate and affiliated confidence to decide whether a cardiac therapy is warranted.

16. A method as in claim 15 wherein the step of tracking peaks and cardiac rate estimates includes determining whether a quantity of first estimates of cardiac rate are similar to one another and, if so, to declaring a first rate track.

17. A method as in claim 16 wherein, following declaration of the first rate track, the tracking step includes determining whether, in a subsequent iteration, a first estimate of cardiac rate meets a rule associated with the first rate track, and, if so, reporting the second estimate of cardiac rate as a rate equal to the first estimate of cardiac rate, and with a high confidence.

18. A method as in claim 16 wherein:

following declaration of the first rate track, the tracking step includes determining whether, in a subsequent iteration;

a) a first estimate of cardiac rate does not meet a rule associated with the first rate track, and

b) no possible cardiac rate identified by analysis of the self-correlation meets the rule associated with the first rate track, either;

then, if both a) and b) are true, the tracking step includes reporting a second estimate of cardiac rate which is both unequal to the first estimate of cardiac rate and falls within the first rate track, with a low second affiliated confidence, unless a condition indicating the first rate track is no longer valid is met.

19. A method as in claim 16 wherein:

following declaration of the first rate track, the tracking step includes determining whether, in a subsequent iteration;

a) a first estimate of cardiac rate does not meet a rule associated with the first rate track, and

b) a possible cardiac rate identified by analysis of the self-correlation function does meet the rule associated with the first rate track;

then, if both a) and b) are true, the tracking step includes reporting a second estimate of cardiac rate which is unequal to the first estimate of cardiac rate and instead matches the possible cardiac rate used in b), with a medium confidence.

20. A method as in claim 16 further comprising:

comparing a detection threshold to the sensed cardiac signals to identify individual cardiac cycles and generate a third estimate of cardiac rate;

wherein the step of using the first and second estimated cardiac rates and affiliated first and second confidences to decide whether a cardiac therapy is warranted further comprises;

determining which of the first, second and third estimated cardiac rates is likely the most reliable, and

using the likely most reliable estimated cardiac rate to decide whether a cardiac therapy is warranted.