DISCORDANCE MONITORING

• US 20160331247A1
• Filed: 05/13/2016
• Published: 11/17/2016
• Est. Priority Date: 05/13/2015
• Status: Active Grant

• Current Assignee: AliveCor Inc.
• Original Assignee: AliveCor Inc.
• Inventors: ALBERT, David E.
• Granted Patent: US 9,839,363 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/282 Holders for multiple electrodes for introduction into the body A61B5/287
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Described herein are systems, devices, and methods for cardiac monitoring. In particular, the systems, devices, and methods described herein may be used to conveniently sense the presence of an intermittent arrhythmia in an individual. The systems, devices, and methods described herein may be further configured to sense an electrocardiogram

Claims

1. A method for cardiac monitoring, comprising:

sensing an activity level value of an individual with a first sensor of a wearable device worn by said individual;

sensing a heart rate value of said individual with a second sensor of said wearable device;

determining a heart rate variability value with a processor of said wearable device;

determining if a discordance is present between two or more of said activity level value, said heart rate value, and said heart rate variability value with said processor; and

indicating to said individual with said wearable device to record an electrocardiogram when said discordance is determined to be present.

2. The method of claim 1, wherein said first sensor comprises an accelerometer.

3. The method of claim 1, wherein said first sensor comprises a gyroscope.

4. The method of claim 1, wherein said second sensor comprises a photosensor.

5. The method of claim 1, wherein said discordance is determined to be present when said activity level value is normal and said heart rate value is elevated.

6. The method of claim 1, wherein said discordance is determined to be present when said activity level value is normal, said heart rate value is elevated, and said heart rate variability value is increased.

7. The method of claim 6, comprising indicating a presence of atrial fibrillation.

8. The method of claim 1, wherein said discordance is determined to be present when said activity level value is normal, said heart rate value is elevated, and said heart rate variability value is decreased.

9. The method of claim 8, comprising indicating a presence of a supraventricular tachycardia.

10. The method of claim 1, comprising setting one or more threshold values based on said activity level value, said heart rate value, and said heart rate variability value.

11. The method of claim 10, wherein said one or more threshold values is determined using a machine learning algorithm.

12. A wearable device for cardiac monitoring, comprising:

a processor;

a first sensor configured to sense an activity level value of an individual, wherein said first sensor is coupled to said processor;

a second sensor configured to sense a heart rate value of an individual, wherein said second sensor is coupled to said processor;

a first electrode and a second electrode configured to sense an electrocardiogram;

a non-transitory computer readable storage medium encoded with a computer program including instructions executable by said processor to cause said processor to;

determine if a discordance is present between said activity level value of said individual and said heart rate value of said individual; and

indicate that said electrocardiogram be recorded when said discordance is determined to be present.

13. The device of claim 12, wherein said first sensor comprises an accelerometer.

14. The device of claim 12, wherein said first sensor comprises a gyroscope.

15. The device of claim 12, wherein said second sensor comprises a photosensor.

16. The device of claim 12, wherein said discordance is determined to be present when said activity level value is normal and said heart rate value is elevated.

17. The device of claim 12, wherein said computer program includes instructions that cause said processor to determine a heart rate variability value.

18. The device of claim 17, wherein said discordance is determined to be present when said activity level value is normal, said heart rate value is elevated, and said heart rate variability value is increased.

19. The device of claim 17, wherein said computer program includes instructions that cause said processor to indicate a presence of atrial fibrillation.

20. The device of claim 17, wherein said discordance is determined to be present when said activity level value is normal, said heart rate value is elevated, and said heart rate variability value is elevated.

21. The device of claim 20, wherein said computer program includes instructions that cause said processor to indicate a presence of a supraventricular tachycardia.

22. The method of claim 12, wherein said computer program includes instructions that cause said processor to set one or more threshold values based on said activity level value, and said heart rate value.

23. The method of claim 22, wherein said one or more threshold values is determined using a machine learning algorithm.

24. A method for cardiac monitoring, comprising:

sensing an activity level value of an individual with a first sensor of a wearable device worn by said individual;

sensing a heart rate value of said individual with a second sensor of said wearable device;

determining if a discordance is present between two or more of said activity level value and said heart rate value by using an activity level threshold and a heart rate threshold with a processor of said wearable device; and

adjusting said activity level threshold and said heart rate level threshold using a machine learning algorithm executed by said processor.