Sleep scoring based on physiological information

Patent metadata

Field	Value
Publication number	US-10555698-B2
Application number	US-201816155139-A
Country	US
Kind code	B2
Filing date	Oct 9, 2018
Priority date	Mar 11, 2017
Publication date	Feb 11, 2020
Grant date	Feb 11, 2020

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.

First claim

What is claimed is:

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.

Assignees

• Fitbit Inc

Inventors

• Russell Allison Maya
• Beattie Zachary Todd
• Statan Alexander
• Quinn Emma Jane

Classifications

• A61B5/4815 Primary

  Sleep quality · CPC title

• A61B5/4806 Primary

  Sleep evaluation (A61B5/4821 takes precedence; devices for inducing sleep A61M21/02) · CPC title

• A61B5/681

  Wristwatch-type devices · CPC title

• A61B5/7405

  using sound · CPC title

• A61B5/486

  Biofeedback (using electroencephalography [EEG] A61B5/375) · CPC title