IP Library › Granted Patent US 10,542,939
Granted Patent B2
US 10,542,939 · App. 15/350,849 · Granted Jan 28, 2020

System and methods of processing accelerometer signals

Inventors: Rodolphe Katra (Blaine, MN); Matthew Edelman (Lino Lakes, MN); Scott Williams (Minneapolis, MN); Niranjan Chakravarthy (Eden Prairie, MN); Arthur Lai (Minnetonka, MN)
Assignee: Medtronic Monitoring, Inc.
A61B5/7246A61B5/0002A61B5/046A61B5/0464A61B5/1116A61B5/1118A61B5/6832A61B5/6847A61B5/7275A61B5/7282A61B5/7285G16H20/30G16H40/63A61B5/0022A61B5/168A61B5/22A61B5/4076A61B2505/07A61B2560/0209A61B2562/0219
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Quick Facts
Patent No.
US 10,542,939
App. No.
15/350,849
Granted
Jan 28, 2020
Kind
B2
Abstract

Embodiments of the present disclosure describe a method of monitoring a patient comprising generating an accelerometer signal of a patient via a patient medical device and capturing and sampling the accelerometer signal at a sampling rate that utilizes non-regular timing intervals. Embodiments further describe a patient medical device comprising sensors for monitoring an accelerometer signal of a patient and circuitry for sampling the accelerometer signal at a sampling rate that utilizes non-regular timing intervals. Embodiments also describe a method of processing physiological signals comprising monitoring ECG signals and accelerometer signals of a patient via a patient medical device and capturing an ECG segment and sampling the accelerometer signal at a sampling rate that utilizes non-regular timing intervals.

Claims (31)

1. A method of monitoring a patient, comprising:

generating an accelerometer signal of a patient via a patient medical device;

sampling the accelerometer signal, without using an anti-aliasing low-pass filter, at a reduced sampling rate that utilizes non-regular timing intervals, wherein the sampling at non-regular timing intervals includes sampling according to the formula: (t n +Δ), wherein t n is a sampling time at a regular interval n and Δ is a random or pseudo random integer independently selected for each t n ,

wherein the sampled accelerometer signal retains low frequency content including posture information and high frequency content including activity information, and

wherein at least one of the posture information and activity information is utilized to determine a severity level of one or more arrhythmic episodes.

2. The method of claim 1 , wherein at least one of the posture information and activity information is utilized to prioritize a reporting of one or more arrhythmic episodes.

3. The method of claim 1 , wherein the severity level of the arrhythmia is high if a tachycardia is detected and the activity level of the patient is characterized as sedentary or at rest.

4. The method of claim 1 , wherein the severity level of the arrhythmia is high if a bradycardia is detected and the activity level of the patient is characterized as active.

5. The method of claim 1 , wherein at least one of the posture information and activity information is utilized to determine a level of debilitation of a patient.

6. The method of claim 1 , wherein at least one of the posture information and activity information is communicated to a remote monitoring center.

7. The method of claim 1 , further comprising extracting patient activity and posture information from the captured and processed accelerometer signal.

8. The method of claim 1 , further comprising reporting an activity profile, the activity profile including the extracted patient activity and posture information.

9. The method of claim 1 , wherein the reduced sampling rate is about 10 Hz or less.

10. A patient medical device, comprising: sensors for monitoring an accelerometer signal of a patient; and circuitry for sampling the accelerometer signal, without using an anti-aliasing low-pass filter, at a reduced sampling rate that utilizes non-regular timing intervals, wherein the sampling at non-regular timing intervals includes sampling according to the formula: (t n +Δ), wherein t n is a sampling time at a regular interval n and Δ is a random or pseudo random integer independently selected for each t n ,

wherein the sampled accelerometer signal retains low frequency content and high frequency content, the low frequency content including posture information and the high frequency content include activity information, and

wherein at least one of the posture information and activity information is utilized to determine a severity level of one or more arrhythmic episodes.

11. The patient medical device of claim 10 , wherein at least one of the posture information and activity information is utilized to construct an activity profile.

12. The patient medical device of claim 10 , wherein at least one of the posture information and activity information is utilized to prioritize a reporting of one or more arrhythmic episodes.

13. The patient medical device of claim 10 , wherein at least one of the posture information and activity information is utilized to determine a level of debilitation of a patient.

14. The patient medical device of claim 10 , further comprising sensors for monitoring an electrocardiogram (ECG) signal of a patient.

15. The method of claim 10 , wherein the reduced sampling rate is about 10 Hz or less.

16. A method of processing physiological signals, comprising:

monitoring ECG signals and accelerometer signals of a patient via a patient medical device; and

capturing an ECG segment and sampling the accelerometer signal, wherein the accelerometer signal is sampled, without using an anti-aliasing low-pass filter, at a reduced sampling rate that utilizes non-regular timing intervals, wherein the sampling at non-regular timing intervals includes sampling according to the formula: (t n +Δ), wherein t n is a sampling time at a regular interval n and Δ is a random or pseudo random integer independently selected for each t n ,

wherein the accelerometer signal is sampled in response to a triggering event based on the ECG segment.

17. The method of claim 16 , wherein all monitored ECG signals are captured and stored and all accelerometer signals are sampled and stored.

18. The method of claim 17 , wherein the stored ECG signals and accelerometer signals are communicated to a remote monitoring center.

19. The method of claim 16 , wherein the triggering event is an abnormal ECG segment.

20. The method of claim 16 , wherein the ECG segment is captured in response to a triggering event based on the accelerometer signal.

21. The method of claim 20 , wherein the triggering event is an abnormal accelerometer signal.

22. The method of claim 16 , wherein the reduced sampling rate is about 10 Hz or less.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 9, 2016
From: KATRA, RODOLPHE; EDELMAN, MATTHEW; WILLIAMS, SCOTT; CHAKRAVARTHY, NIRANJAN; LAI, ARTHUR
To: MEDTRONIC MONITORING, INC.
Reel/Frame 040699/0828 →
Continuity (1)
Related Publication 20180132793A1 · May 17, 2018