APPARATUS AND METHOD FOR PATIENT ACTIVITY ESTIMATION AND CLASSIFICATION

• US 20140257115A1
• Filed: 03/07/2014
• Published: 09/11/2014
• Est. Priority Date: 03/08/2013
• Status: Active Grant

• Current Assignee: Greatbatch Limited (Greatbatch Incorporated)
• Original Assignee: Greatbatch Limited (Greatbatch Incorporated)
• Inventors: Katra, Rodolphe, Chakravarthy, Niranjan
• Granted Patent: US 10,376,184 B2
• Time in Patent Office: Days
• US Class Current: 600/483
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/30 Input circuits therefor
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts

Abstract

A medical device includes a housing and an electrode arrangement coupled to the housing and configured to sense an electrical physiologic signal from a patient. The device also includes detection circuitry coupled to the electrode arrangement and configured to obtain a cardiac signal component and a non-cardiac signal component from the physiological signal. A processor is coupled to the detection circuitry. The processor is configured to detect patient activity using at least the non-cardiac signal component and discriminate between voluntary and involuntary activity of the patient based on a comparison of temporally aligned cardiac and non-cardiac signal components.

Claims

1. A method comprising:

sensing, from a patient, an electrical physiologic signal between a single electrode pair;

obtaining a cardiac signal component from the physiological signal;

obtaining a non-cardiac signal component from the physiologic signal;

comparing the cardiac and non-cardiac signal components to thresholds established for the patient;

detecting patient activity using at least the non-cardiac signal component; and

discriminating between voluntary and involuntary activity of the patient based on the comparison and temporal alignment of the cardiac signal component relative to the non-cardiac signal component.

2. The method of claim 1, wherein discriminating between voluntary and involuntary activity of the patient comprises discriminating between sustained and transient activity of the patient.

3. The method of claim 1, wherein discriminating between voluntary and involuntary activity of the patient comprises performing a mathematical correlation between temporally aligned cardiac and non-cardiac signal components.

4. The method of claim 1, wherein:

comparing comprises comparing a trajectory of the cardiac signal component to a trajectory of the non-cardiac signal component during a detection window; and

discriminating between voluntary and involuntary activity of the patient based on the trajectory comparison.

5. The method of claim 1, further comprising:

determining a sleep status of the patient using the non-cardiac signal component and the cardiac signal component;

wherein discriminating between voluntary and involuntary activity of the patient is based at least in part on the sleep status of the patient.

6. The method of claim 1, further comprising:

determining a duration of the non-cardiac signal component;

wherein discriminating between voluntary and involuntary activity of the patient is based at least in part on the duration of the non-cardiac signal component.

7. The method of claim 1, further comprising:

determining a power of the non-cardiac signal component;

wherein discriminating between voluntary and involuntary activity of the patient is based at least in part on the power of the non-cardiac signal component.

8. The method of claim 1, further comprising:

determining a periodicity of the non-cardiac signal component;

wherein discriminating between voluntary and involuntary activity of the patient is based at least in part on the periodicity of the non-cardiac signal component.

9. The method of claim 1, wherein discriminating between voluntary and involuntary patient activity comprises distinguishing between compensated and non-compensated cardiac rhythms.

10. The method of claim 1, wherein discriminating between voluntary and involuntary patient activity comprises identifying an episode of epileptic seizure.

11. The method of claim 1, wherein:

detecting patient activity comprises comparing the non-cardiac signal component to a threshold; and

the method comprises adjusting the threshold over time based on changes in patient activity over time.

12. The method of claim 11, comprising detecting a change in patient status based on a change in the threshold.

13. The method of claim 1, comprising detecting disparate types of patient activity based on the comparison and temporal alignment of the cardiac signal component relative to the non-cardiac signal component;

14. A method comprising:

sensing, from a patient, an electrical physiologic signal between a single electrode pair;

obtaining a cardiac signal component from the physiological signal;

deriving a cardiac metric using the cardiac signal component;

obtaining a non-cardiac signal component from the physiologic signal;

deriving an activity metric using the non-cardiac signal component;

comparing the cardiac and activity metrics; and

discriminating between voluntary and involuntary activity of the patient based on the comparison and temporal alignment of the cardiac and activity metrics.

15. The method of claim 14, wherein:

the cardiac metric comprises at least one of heart rate, QRS width, intervals between any of PQRST features, time-domain characterization, frequency domain characterization, and morphology; and

the activity metric comprises at least one of intensity, duration, power, rhythmicity or periodicity, pattern, and concatenation.

16. The method of claim 14, wherein discriminating between voluntary and involuntary activity of the patient comprises discriminating between sustained and transient activity of the patient.

17. The method of claim 14, wherein discriminating between voluntary and involuntary activity of the patient comprises performing a mathematical correlation between temporally aligned cardiac and activity metrics.

18. The method of claim 14, wherein:

detecting patient activity comprises comparing the non-cardiac signal component to a threshold; and

the method comprises adjusting the threshold over time based on changes in patient activity over time.

19. The method of claim 18, comprising detecting a change in patient status based on a change in the threshold.

20. A medical device comprising:

a housing;

an electrode arrangement coupled to the housing and configured to sense an electrical physiologic signal from a patient;

detection circuitry coupled to the electrode arrangement and configured to obtain a cardiac signal component and a non-cardiac signal component from the physiological signal; and

a processor coupled to the detection circuitry, the processor configured to detect patient activity using at least the non-cardiac signal component and discriminate between voluntary and involuntary activity of the patient based on a comparison of temporally aligned cardiac and non-cardiac signal components.

21. The device of claim 20, wherein the processor is configured to discriminate between sustained and transient activity of the patient.

22. The device of claim 20, wherein the processor is configured to perform a mathematical correlation between the temporally aligned cardiac and non-cardiac signal components.

23. The device of claim 20, wherein:

the detection circuitry is configured to compare the non-cardiac signal component to a threshold, and

the processor is configured to adjust the threshold over time based on changes in patient activity over time.

24. The device of claim 23, wherein the processor is configured to detect a change in patient status based on a change in the threshold.

25. The device of claim 20, wherein the processor is configured to detect a plurality of disparate types of patient activity.