Use of curvature based features for beat detection

• US 20040010200A1
• Filed: 07/15/2002
• Published: 01/15/2004
• Est. Priority Date: 07/15/2002
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Sweeney, Robert J.
• Granted Patent: US 6,950,702 B2
• Time in Patent Office: Days
• US Class Current: 600/517
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: A61N 1/365 controlled by a physiological parameter, e.g. heart potential evoked response A61N1/371

Abstract

A cardiac rhythm management system includes a sensing circuit to sense a cardiac signal and a sensing processor to detect cardiac depolarizations (beats) by utilizing certain morphological context of the sensed cardiac signal. The sensing processor samples the sensed cardiac signal, computes curvatures from the sampled cardiac signal to generate a cardiac curvature signal corresponding to the cardiac signal, derives cardiac signal features reflecting morphologically significant points along the cardiac signal from the cardiac curvature signal, and detects cardiac depolarizations based on an analysis of the cardiac signals features.

Claims

1. A system, comprising:

a sensing circuit to sense a cardiac signal;

a sampling circuit, coupled to the sensing circuit, to sample the cardiac signal on a continuous basis;

a feature analyzer, coupled to the sampling circuit, to derive cardiac signal features based on predetermined detection criteria;

a counter, coupled to the feature analyzer, to count the cardiac signal features over a predetermined period of time; and

a comparator, coupled to the counter, to receive a first input representative of a number of the cardiac signal features counted over the predetermined period of time and compare that input to a second input representative of a predetermined threshold number, and to provide a depolarization indicating signal when the number of the cardiac signal features counted over the predetermined period of time exceeds the threshold number.

2. The system of claim 1, further comprising a therapy circuit, coupled to the comparator, to trigger or inhibit a delivery of a cardiac therapy based on the depolarization indicating signal.

3. The system of claim 1, wherein the feature analyzer comprises:

a curvature generator, coupled to the sampling circuit, to generate a cardiac curvature signal corresponding to the cardiac signal by computing a curvature, after each sample is taken, based on the each sample and a predetermined number of preceding samples; and

a feature detector adapted to detect the cardiac signal features from the cardiac curvature signal.

4. The system of claim 3, further comprising an intracardiac electrode coupled to the sensing circuit.

5. The system of claim 3, wherein the feature detector comprises a feature comparator adapted to compare an amplitude of the cardiac curvature signal to a predetermined threshold amplitude and generate a signal indicating that a cardiac signal feature has been detected when the amplitude of the cardiac curvature signal exceeds the predetermined threshold amplitude.

6. The system of claim 3, wherein the feature detector comprises:

a zero-crossing detector to detect lobes of the cardiac curvature signal, the lobes each including a beginning time when the cardiac curvature signal reaches a first threshold and an ending time when the cardiac curvature signal reaches a second threshold, the first and second thresholds each being slightly away from or approximately equal to a baseline of the cardiac curvature signal;

a size calculator to calculate an approximate area between the cardiac curvature signal and the baseline for each of the lobes, and

a centroid locator to temporally locate a centroid of the calculated approximate area of the each of the lobes, the centroid indicative of an approximate time of occurrence of one of the cardiac signal features representing the each of the lobes.

7. A system comprising:

a sensing circuit to sense a cardiac signal;

a sampling circuit, coupled to the sensing circuit, to sample the cardiac signal on a continuous basis;

a feature analyzer, coupled to the sampling circuit, to derive cardiac signal features based on predetermined detection criteria;

a metric generator, coupled the feature analyzer, to compute a metric based on one or more of the cardiac signal features; and

a metric comparator, coupled to the metric generator, to receive a first metric input representative of the metric and compare that input to a second metric input representative of a predetermined threshold, and to provide an output signal indicating whether a depolarization has been detected.

8. The system of claim 7, further comprising a therapy circuit, coupled to the metric comparator, to trigger or inhibit a delivery of a cardiac therapy based on the output signal indicating whether the depolarization has been detected.

9. The system of claim 7, wherein the feature analyzer comprises:

a curvature generator, coupled to the sampling circuit, to generate a cardiac curvature signal corresponding to the cardiac signal by computing a curvature, after each sample is taken, based on the each sample and a predetermined number of preceding samples; and

a feature detector adapted to detect the cardiac signal features from the cardiac curvature signal.

10. The system of claim 9, further comprising an intracardiac electrode coupled to the sensing circuit.

11. The system of claim 9, wherein the feature detector comprises a feature comparator adapted to compare an amplitude of the cardiac curvature signal to a predetermined threshold amplitude and generate a signal indicating that one of the cardiac signal features has occurred when the amplitude of the cardiac curvature signal exceeds the predetermined threshold amplitude.

12. The system of claim 9, wherein the feature detector comprises:

a zero-crossing detector to detect lobes of the cardiac curvature signal, the lobes each identifying one of the cardiac signal features and including a beginning time when the cardiac curvature signal reaches a first threshold and an ending time when the cardiac curvature signal reaches a second threshold, the first and second threshold each being slightly away from or approximately equal to a baseline of the cardiac curvature signal;

a direction detector to determine a direction of each of the cardiac signal features, the direction indicative of whether one of the lobes identifying the each of the cardiac signal features is above or below the baseline;

a size calculator to calculate a size of the each of the cardiac signal features, the size being an approximate area between the cardiac curvature signal and the baseline for the one of the lobes; and

a centroid locator to temporally locate a centroid of the calculated approximate area of the one of the lobes, the centroid indicative of an approximate time of occurrence of the each of the cardiac signal features representing the one of the lobes.

13. The system of claim 12, wherein the feature analyzer comprises an amplitude detector adapted to measure an amplitude of the cardiac signal at the approximate time of occurrence of the each of the cardiac signal features.

14. The system of claim 13, wherein the metric generator comprises an arithmetic module adapted to compute the metric based on one or more of the cardiac signal features.

15. The system of claim 14, wherein the arithmetic module is adapted to compute the metric based on at least one of the approximate time of occurrence, the size, the direction, and the amplitude of the cardiac signal associated with each of the one or more of the cardiac signal features.

16. A method comprising:

sensing a cardiac signal;

deriving cardiac signal features;

counting a number of the cardiac signal features over a predetermined period of time; and

determining that a depolarization has occurred when the number of the cardiac signal features counted over the predetermined period of time exceeds a predetermined threshold number.

17. The method of claim 16, further comprising triggering or inhibiting a cardiac therapy when the depolarization has occurred.

18. The method of claim 16, wherein deriving the cardiac signal features comprises identifying portions of the cardiac signal having at least one predetermined morphological characteristic.

19. The method of claim 18, wherein the sensing, deriving, counting, and determining comprise, respectively, sensing, deriving, counting, and determining in substantially real-time.

20. The method of claim 18, wherein deriving the cardiac signal features comprises:

sampling the cardiac signal;

computing curvatures on a continuous, sample-by-sample basis, based on the sampled cardiac signal; and

deriving the cardiac signal features from the computed curvatures.

21. The method of claim 20, wherein computing curvatures comprises computing a curvature after completion of taking of each sample of the cardiac signal, based on the each sample and a predetermined number of samples preceding the each sample.

22. The method of claim 21, wherein deriving the cardiac signal features comprises comparing the curvatures with a predetermined threshold.

23. The method of claim 21, wherein computing curvatures further comprises generating a cardiac curvature signal corresponding to the cardiac signal, and wherein deriving the cardiac signal features comprises computing an approximate centroid of each lobe of the cardiac curvature signal, the each lobe including an area between the cardiac curvature signal and a baseline of the cardiac curvature signal between a first point of time when the cardiac curvature signal reaches a first threshold and a second point of time when the cardiac curvature signal reaches a second threshold, the first and second thresholds each being slightly away from or approximately equal to the baseline.

24. A method comprising:

sensing a cardiac signal;

deriving cardiac signal features;

generating a parameter set associated with each of the cardiac signal features;

computing a metric based on portions of the parameter sets associated with the cardiac signal features;

comparing the metric with a predetermined threshold; and

determining whether a depolarization has occurred based on an outcome of the comparing.

25. The method of claim 24, further comprising determining whether to deliver a cardiac therapy based on whether the depolarization has occurred.

26. The method of claim 24, wherein deriving the cardiac signal features comprises identifying portions of the cardiac signal having at least one predetermined morphological characteristic.

27. The method of claim 26, wherein the sensing, deriving, generating, computing, comparing, and determining comprise, respectively, sensing, deriving, generating, computing, comparing, and determining in substantially real-time.

28. The method of claim 26, wherein deriving the cardiac signal features comprises:

sampling the cardiac signal;

computing curvatures on a continuous basis, based on the sampled cardiac signal; and

deriving the cardiac signal features from the computed curvatures;

29. The method of claim 28, wherein computing curvatures comprises computing a curvature after completion of taking of each sample of the cardiac signal, based on the each sample and a predetermined number of samples preceding the each sample.

30. The method of claim 29, wherein deriving the cardiac signal features comprises comparing the curvatures with a predetermined threshold.

31. The method of claim 29, wherein computing curvatures further comprises generating a cardiac curvature signal corresponding to the cardiac signal, and wherein deriving the cardiac signal features comprises computing an approximate centroid of each lobe of the cardiac curvature signal, the each lobe including an area between the cardiac curvature signal and a baseline of the cardiac curvature signal between a first point of time when the cardiac curvature signal reaches a first threshold and a second point of time when the cardiac curvature signal reaches a second threshold, the first and second thresholds each being slightly away from or approximately equal to the baseline.

32. The method of claim 24, wherein computing the metric comprises using an arithmetic formula to compute the metric based on one or more of the cardiac signal features each associated with one or more parameters.

33. The method of claim 32, wherein determining whether the depolarization has occurred comprises:

comparing the metric with a predetermined threshold; and

producing a depolarization signal when the metric exceeds the predetermined threshold.

34. The method of claim 33, wherein deriving the cardiac signal features comprises:

sampling the cardiac signal;

computing curvatures on a continuous basis, based on the sampled cardiac signal, to generate a cardiac curvature signal corresponding to the cardiac signal; and

computing approximate centroids of lobes of the cardiac curvature signal, the lobes each identifying one of the cardiac signal features and including an area between the cardiac curvature signal and a baseline of the cardiac curvature signal between a first point of time when the cardiac curvature signal reaches a first threshold and a second point of time when the cardiac curvature signal reaches a second threshold, the first and second thresholds each being slightly away from or approximately equal to the baseline.

35. The method of claim 34, wherein computing the metric comprises using the arithmetic formula to compute the metric based on one or more of the cardiac signal features each representing one of the approximate centroids computed from one of the lobes and associated with at least one of:

an approximate time of occurrence;

an amplitude of the cardiac signal at the approximate time of the occurrence;

a direction representative of whether the one of the lobes is positive or negative with respect to the baseline; and

a size representative of an approximate area of the one of the lobes.

36. A method, comprising:

receiving a sensor signal;

computing a curvature signal corresponding to the sensor signal;

deriving signal features based on the curvature signal; and

determining whether a predetermined physiological event has occurred based on the signal features.

37. The method of claim 36, wherein receiving the sensor signal comprises receiving at least one of:

an intracardiac electrogram signal;

an electrocardiogram (ECG) signal;

a mechanical motion signal;

a sound signal;

a pressure signal;

an acceleration signal; and

an impedance signal.

38. The method of claim 37, wherein determining whether the predetermined physiological event has occurred comprises determining whether a cardiac depolarization has occurred.

39. The method of claim 38, further comprising determining whether to deliver a cardiac therapy based on an outcome of the determining whether the cardiac depolarization has occurred.