Portable monitoring devices for processing applications and processing analysis of physiological conditions of a user associated with the portable monitoring device

• US 10,588,519 B2
• Filed: 06/25/2018
• Issued: 03/17/2020
• Est. Priority Date: 09/30/2010
• Status: Active Grant

• Current Assignee: Fitbit, Inc. (Alphabet Inc.)
• Original Assignee: Fitbit, Inc. (Alphabet Inc.)
• Inventors: Yuen, Shelten Gee Jao, Park, James, Friedman, Eric Nathan, Martinez, Mark Manuel, Axley, Andrew Larsen
• Primary Examiner(s): Luan, Scott
• Application Number:
  US16/017,870
• Publication Number:
  US 20190059744A1
• Time in Patent Office: 631 Days
• CPC Class Codes: A61B 2560/0209 adapted for power saving
• 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 5/02427 Details of sensor
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/683 Means for maintaining contact with the body A61B5/6802 takes precedence
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence

Abstract

An activity monitoring device, methods and computer readable media are provided. The activity monitoring device includes a housing configured for attachment to a body part of a user and a display screen attached to the housing. Further included is a first sensor disposed in the housing for capturing motion of the activity monitoring device when attached to the body part of the user and a second sensor disposed in the housing for sampling a heart rate of the user. Memory is disposed in the housing for storing the motion captured by the first sensor and the heart rate sampled by the second sensor. A processor is disposed in the housing and is configured to determine a physical state of the user during a period of time. For motion that is below a threshold the processor identifies the physical state to be a sedentary state and for motion that is at or above the threshold the processor identifies the physical state to be an active state. The processor is configured to reduce a rate at which to sample the heart rate of the user when the physical state of the user is identified to be the sedentary state during the period of time. The processor is configured to increase the rate at which the sampling of the heart rate of the user is processed when the physical state of the user is identified to be the active state during the period of time.

Claims

1. An activity monitoring device, comprising,

a housing configured for attachment to a body part of a user;

a first sensor disposed in the housing and configured to capture motion data describing motion of the activity monitoring device;

a second sensor disposed in the housing and configured to sample a heart rate of the user to generate heart rate data when the activity monitoring device is worn on the body part of the user;

memory disposed in the housing for storing the motion data captured by the first sensor and the heart rate data generated by the second sensor; and

a processor disposed in the housing, wherein the memory further stores computer-executable instructions for controlling the processor to;

determine a physical state of the user during a period of time, wherein for motion that is below a threshold, the instructions cause the processor to determine that the physical state is a sedentary state, and for motion that is at or above the threshold, the instructions cause the processor to determine that the physical state is an active state;

reduce a rate at which the second sensor samples the heart rate of the user when the physical state of the user is determined to be the sedentary state during the period of time; and

increase the rate at which the second sensor samples the heart rate of the user when the physical state of the user is determined to be the active state during the period of time.

2. The activity monitoring device of claim 1, wherein the second sensor is a photoplethysmography (PPG) sensor configured to capture light reflected from skin of the body part and thereby sample the heart rate of the user.

3. The activity monitoring device of claim 1, wherein the memory further stores computer-executable instructions for controlling the processor to cause the activity monitoring device to enter a reduced power consumption state in response to the processor determining that the physical state is the sedentary state.

4. The activity monitoring device of claim 1, wherein the memory further stores computer-executable instructions for controlling the processor to cause the activity monitoring device to enter a higher power consumption state in response to the processor determining that the physical state is the active state.

5. The activity monitoring device of claim 1, wherein the memory further stores computer-executable instructions for controlling the processor to control an amount of data processing performed by the activity monitoring device to thereby reduce power consumed by the activity monitoring device in response to the processor determining that the physical state is the sedentary state.

6. The activity monitoring device of claim 1, wherein the the memory further stores computer-executable instructions for controlling processor to calculate a heart rate variability metric based on measurements from the second sensor in response to the processor determining that the physical state is the sedentary state.

7. The activity monitoring device of claim 1, wherein the memory further stores computer-executable instructions for controlling the processor to measure the heart rate of the user via analog signal conditioning circuitry of the activity monitoring device to thereby reduce power consumed by the activity monitoring device in response to the processor determining that the physical state is the sedentary state.

8. A method of operating a processor of an activity monitoring device, the activity monitoring device having a housing configured for attachment to a body part of a user, the method comprising:

capturing motion data describing motion of the activity monitoring device using a first sensor disposed in the housing;

sampling a heart rate of the user to generate heart rate data using a second sensor disposed in the housing when the activity monitoring device is worn on the body part of the user;

storing the motion data captured by the first sensor and the heart rate data generated by the second sensor to a memory of the activity monitoring device;

determining a physical state of the user during a period of time, wherein for motion that is below a threshold, the physical state is determined to be a sedentary state, and for motion that is at or above the threshold, the physical state is determined to be an active state;

reducing a rate at which the heart rate of the user is sampled responsive to the physical state of the user being determined to be the sedentary state during the period of time; and

increasing the rate at which the heart rate of the user is sampled responsive to the physical state of the user being determined to be the active state during the period of time.

9. The method of claim 8, wherein the second sensor is a photoplethysmography (PPG) sensor, the second sensor being used for capturing light reflected from skin of the body part and thereby sample the heart rate of the user.

10. The method of claim 8, further comprising causing the activity monitoring device to enter a reduced power consumption state responsive to determining that the physical state is the sedentary state.

11. The method of claim 8, further comprising causing the activity monitoring device to enter a higher power consumption state responsive to determining that the physical state is the active state.

12. The method of claim 8, further comprising controlling an amount of data processing performed by the activity monitoring device to thereby reduce power consumed by the activity monitoring device responsive to determining that the physical state is the sedentary state.

13. The method of claim 8, further comprising calculating a heart rate variability metric based on measurements from the second sensor responsive to determining that the physical state is the sedentary state.

14. The method of claim 8, further comprising measuring the heart rate of the user via analog signal conditioning circuitry of the activity monitoring device to thereby reduce power consumed by the activity monitoring device responsive to determining that the physical state is the sedentary state.

15. A non-transitory computer-readable medium storing instructions configured to be executed by one or more processors of an activity monitoring device, the activity monitoring device having a housing configured to be worn on a body part of a user, the instructions comprising instructions for causing the one or more processors to:

capture motion data describing motion of the activity monitoring device using a first sensor disposed in the housing;

sample a heart rate of the user to generate heart rate data using a second sensor disposed in the housing when the activity monitoring device is worn on the body part of the user;

store the motion data captured by the first sensor and the heart rate data generated by the second sensor to a memory of the activity monitoring device;

determine a physical state of the user during a period of time, wherein for motion that is below a threshold, the physical state is determined to be a sedentary state and for motion that is at or above the threshold the physical state is determined to be an active state;

reduce a rate at which the heart rate of the user is sampled responsive to the physical state of the user being determined to be the sedentary state during the period of time; and

increase the rate at which the heart rate of the user is sampled responsive to the physical state of the user being determined to be the active state during the period of time.

16. The non-transitory computer-readable medium of claim 15, wherein the second sensor is a photoplethysmography (PPG) sensor, the second sensor being used for capturing light reflected from skin of the body part and thereby sample the heart rate of the user.

17. The non-transitory computer-readable medium of claim 15, wherein the non-transitory computer-readable medium further stores instructions for causing the one or more processors to cause the activity monitoring device to enter a reduced power consumption state responsive to determining that the physical state is the sedentary state.

18. The non-transitory computer-readable medium of claim 15, wherein the non-transitory computer-readable medium further stores instructions for causing the one or more processors to cause the activity monitoring device to enter a higher power consumption state responsive to determining that the physical state is the active state.

19. The non-transitory computer-readable medium of claim 15, wherein the non-transitory computer-readable medium further stores instructions for causing the one or more processors to control an amount of data processing performed by the activity monitoring device to thereby reduce power consumed by the activity monitoring device responsive to determining that the physical state is the sedentary state.

20. The non-transitory computer-readable medium of claim 15, wherein the non-transitory computer-readable medium further stores instructions for causing the one or more processors to calculate a heart rate variability metric based on measurements from the second sensor responsive to determining that the physical state is the sedentary state.