Sleep scoring based on physiological information

• US 10,555,698 B2
• Filed: 10/09/2018
• Issued: 02/11/2020
• Est. Priority Date: 03/11/2017
• Status: Active Grant

• Current Assignee: Fitbit, Inc. (Alphabet Inc.)
• Original Assignee: Fitbit, Inc. (Alphabet Inc.)
• Inventors: Russell, Allison Maya, Beattie, Zachary Todd, Statan, Alexander, Quinn, Emma Jane
• Primary Examiner(s): Lu, Shirley
• Application Number:
  US16/155,139
• Publication Number:
  US 20190254589A1
• Time in Patent Office: 490 Days
• CPC Class Codes: A61B 2505/07 Home care
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/02 Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
• 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 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/4806 Sleep evaluation A61B5/4821 takes precedence; devices for inducing sleep A61M21/02
• CPC Class Codes: A61B 5/4815 Sleep quality
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6824 Arm or wrist
• CPC Class Codes: A61B 5/7405 using sound
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/744 Displaying an avatar, e.g. an animated cartoon character
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick

Abstract

Assessing the sleep quality of a user in association with an electronic device with one or more physiological sensors includes detecting an attempt by the user to fall asleep, and collecting physiological information associated with the user. The disclosed method of assessing sleep quality may include determining respective values for one or more sleep quality metrics, including a first set of sleep quality metrics associated with sleep quality of a plurality of users, and a second set of sleep quality metrics associated with historical sleep quality of the user, based at least in part on the collected physiological information and at least one wakeful resting heart rate of the user, and determining a unified score for sleep quality of the user, based at least in part on the respective values of the one or more sleep quality metrics.

Claims

1. A wearable device, comprising:

a housing;

one or more physiological sensors disposed in the housing, the one or more sensors operable to capture one or more signals, the one or more signals including signals representative of movement;

one or more processors disposed in the housing;

a display; and

control circuitry configured to;

detect a lack of movement for a threshold period of time;

collect physiological data, including at least one sleeping heart rate;

determine respective values for one or more sleep quality metrics, based at least in part on the collected physiological data and at least one wakeful resting heart rate; and

present, on the display, a representation of a score for sleep quality, the score for sleep quality based at least in part on the respective values of the one or more sleep quality metrics.

2. The wearable device of claim 1, wherein the one or more sleep quality metrics includes a first set of sleep quality metrics associated with sleep quality of a plurality of users, and a second set of sleep quality metrics associated with historical sleep quality of one user.

3. The wearable device of claim 1, wherein the control circuitry and the one or more processors being configured to determine the score for sleep quality includes being configured to:

determine a respective metric-score for each of the one or more sleep quality metrics; and

apply a respective weighting for each of the one or more sleep quality metrics.

4. The wearable device of claim 1, wherein the control circuitry and the one or more processors are further configured to determine the at least one wakeful resting heart rate before detecting the lack of movement.

5. The wearable device of claim 1, wherein the physiological data includes one or more sets of values associated with at least one of:

movement, total sleep duration, total deep sleep duration, duration of wake time after sleep onset, total rapid-eye-movement sleep duration, total light sleep duration, breathing patterns, breathing disturbances, and temperature.

6. The wearable device of claim 1, wherein the control circuitry and the one or more processors are further configured to:

collect sleep quality feedback; and

determine the score for sleep quality based at least in part on the collected sleep quality feedback.

7. The wearable device of claim 1, wherein the control circuit and the one or more processors being configured to determine respective values for the one or more sleep quality metrics includes being configured to compare the at least one sleeping heart rate and the at least one wakeful resting heart rate.

8. The wearable device of claim 1, wherein the control circuitry and the one or more processors are further configured to:

detect an onset of sleep; and

determine a duration of time from the lack of movement to the onset of sleep.

9. The wearable device of claim 8, wherein the control circuitry and the one or more processors are further configured to:

detect an awake status after the onset of sleep; and

determine the respective values for one or more sleep quality metrics, in response to detecting the awake status.

10. A computer-implemented method, comprising:

receiving one or more signals indicating a lack of movement for a threshold period of time;

receiving physiological data including at least one sleeping heart rate, the physiological data generated by one or more physiological sensors;

determining respective values for one or more sleep quality metrics based at least in part on the physiological data and at least one wakeful resting heart rate; and

determining a score for sleep quality, based at least in part on the respective values of the one or more sleep quality metrics;

presenting, on the display, a representation of a score for sleep quality, the score for sleep quality based at least in part on the respective values of the one or more sleep quality metrics.

11. The computer-implemented method of claim 10, wherein the at least one wakeful resting heart rate includes a representative value of one or more of heart rate values during a period of relative inactivity.

12. The computer-implemented method of claim 10, wherein the one or more sleep quality metrics includes a first set of sleep quality metrics associated with sleep quality of a plurality of users, and a second set of sleep quality metrics associated with historical sleep quality of one user.

13. The computer-implemented method of claim 10, wherein determining the score for sleep quality includes:

determining a respective metric-score for each of the one or more sleep quality metrics; and

applying a respective weighting for each of the one or more sleep quality metrics.

14. The computer-implemented method of claim 10, wherein the at least one wakeful resting heart rate is determined before receiving one or more signals indicating the lack of movement.

15. The computer-implemented method of claim 10, wherein the physiological data includes one or more sets of values associated with at least one of:

movement, total sleep duration, total deep sleep duration, duration of wake time after sleep onset, total rapid-eye-movement sleep duration, total light sleep duration, breathing patterns, breathing disturbances, and temperature.

16. The computer-implemented method of claim 10, further comprising:

receiving sleep quality feedback; and

determining the score for sleep quality based at least in part on the sleep quality feedback.

17. The computer-implemented method of claim 10, wherein determining the respective values for the one or more sleep quality metrics includes comparing the at least one sleeping heart rate and the at least one wakeful resting heart rate.

18. The computer-implemented method of claim 10, further comprising:

receiving one or more signals indicating an onset of sleep; and

determining a duration of time from the lack of movement to the onset of sleep.

19. The computer-implemented method of claim 18, further comprising:

receiving one or more signals indicating an awake status after the onset of sleep; and

determining the respective values for one or more sleep quality metrics, in response to receiving one or more signals indicating the awake status.

20. A computing system, comprising:

one or more processors; and

memory including instructions that, when executed by the at least one processor, cause the computing system to;

receive movement data from a wearable device, the movement data including a lack of movement for a threshold period of time;

collect, from the wearable device, physiological data including at least one sleeping heart rate;

determine respective values for one or more sleep quality metrics, based at least in part on the collected physiological data and at least one wakeful resting heart rate; and

determine a score for sleep quality, based at least in part on the respective values of the one or more sleep quality metrics;

present, on the display, a representation of a score for sleep quality, the score for sleep quality based at least in part on the respective values of the one or more sleep quality metrics.