System for determining the quality of sleep

• US 10,368,799 B2
• Filed: 01/15/2016
• Issued: 08/06/2019
• Est. Priority Date: 01/27/2015
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Sannholm, Fredrik, Paalasmaa, Joonas, Leppakorpi, Lasse
• Primary Examiner(s): Layno, Carl H
• Assistant Examiner(s): Xie, Dacheng
• Application Number:
  US14/997,031
• Publication Number:
  US 20160213309A1
• Time in Patent Office: 1,299 Days
• Field of Search: 600300-301
• CPC Class Codes: A61B 2562/0257 Proximity sensors
• CPC Class Codes: A61B 2562/0261 Strain gauges
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/1102 Ballistocardiography
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/4815 Sleep quality
• CPC Class Codes: A61B 5/6892 Mats
• 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 5/7271 Specific aspects of physiological measurement analysis A61B5/316, A61B5/349 and A61B5/374 take precedence
• 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
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• 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

Abstract

Embodiments of the present invention provide a distributed computer system and a method for determining the quality of sleep of a sleeping user. The distributed computer system will determine the quality of sleep by detecting the changes in body posture of the sleeping user. The quality of sleep will be determined by the feature vectors associated with each posture of the sleeping user. The posture of the user will be determined by recording a body motion signal caused by the mechanical and muscle movement of the body of the user.

Claims

1. A method of determining quality of sleep of at least one user, the method comprising:

using a peripheral device to record a body motion signal of the at least one user, the peripheral device comprising a static sensor and a dynamic sensor;

using the peripheral device to establish a communication connection between the peripheral device and a mobile phone;

communicating the body motion signal from the peripheral device to the mobile phone; and

using the mobile phone to;

determine respiration amplitudes from the body motion signal;

detect a change in the body motion signal in a given window of time;

detect an increase or an absence of an increase in a respiration cycle amplitude in the given window of time, wherein the respiration cycle amplitude is an average of the respiration amplitudes taken over the given window of time;

determine body posture changes of the at least one user when the change in the body motion signal and the increase in the respiration cycle amplitude are detected simultaneously;

determine body movements of the at least one user when the change in the body motion signal and the absence of the increase in the respiration cycle amplitude are detected simultaneously; and

determine the quality of sleep of the at least one user based on occurrences of the determined body posture changes and the determined body movements.

2. The method as claimed in claim 1, wherein the body posture changes are further determined using a change in one or more of signals determined from the body motion signal, the signals include:

a respiration cycle shape, a heartbeat cycle shape, a heartbeat cycle amplitude, and a value of presence signals.

3. The method as claimed in claim 1, wherein the determination of the body posture changes of the at least one user includes:

classifying the body motional signal to feature vectors, the feature vectors associated with body postures.

4. The method as claimed in claim 1, further comprising:

capturing one or more images and data of body postures of the at least one user during sleep;

storing the one or more of images and the data of the body postures of the at least one user into a data storage; and

displaying the one or more of the images and the data of the body postures on a screen of the mobile phone.

5. The method as claimed in claim 1, wherein the dynamic sensor is one or more of a piezoelectric sensor and a piezo thin film sensor, and

the static sensor is one or more of a strain gauge, a capacitive sensor, a proximity sensor, a thermocouple, and an inductive sensor.

6. The method as claimed in claim 1, wherein the peripheral device comprises a plurality of sensors placed at multiple sensitive areas to determine one or more of (a) presence signals and (b) a position of the at least one user on a bed.

7. A distributed computer system to determine quality of sleep of at least one user, the distributed computer system comprising:

a mobile subscriber terminal comprising a processor;

a peripheral device configured to record a body motion signal and to communicate the body motion signal to the mobile subscriber terminal, the peripheral device comprising at least one static sensor and at least one dynamic sensor,

wherein the mobile subscriber terminal;

determines respiration amplitudes from the body motion signal;

detects a change in the body motion signal in a given window of time;

detects an increase or an absence of an increase in a respiration cycle amplitude in the given window of time, wherein the respiration cycle amplitude is an average of the respiration amplitudes taken over the given window of time;

determines body posture changes of the at least one user when the change in the body motion signal and the increase in the respiration cycle amplitude are detected simultaneously;

determines body movements of the at least one user when the change in the body motion signal and the absence of the increase in the respiration cycle amplitude are detected simultaneously; and

determines the quality of sleep of the at least one user based on occurrences of the determined body posture changes and the determined body movements.

8. The distributed computer system as claimed in claim 7, wherein the body posture changes are further determined using a change in one or more of signals determined from the body motion signal, the signals include:

a respiration cycle shape, a heartbeat cycle shape, a heartbeat cycle amplitude, and a value of presence signals.

9. The distributed computer system as claimed in claim 7, wherein the determination of the body posture changes of the at least one user includes:

classifying the body motion signal to feature vectors, the feature vectors associated with body postures.

10. The distributed computer system as claimed in claim 7, further comprising:

capturing one or more images and data of body postures of the at least one user during sleep;

storing the one or more of images and the data of the body postures of the at least one user into a data storage; and

displaying the one or more of the images and the data of the body postures on a screen of the mobile subscriber terminal.

11. The distributed computer system as claimed in claim 7, wherein the at least one dynamic sensor is one or more of a piezoelectric sensor and a piezo thin film sensor.

12. The distributed computer system as claimed in claim 7, wherein the at least one static sensor is one or more of a strain gauge, a capacitive sensor, a proximity sensor, a thermocouple, and an inductive sensor.

13. The distributed computer system as claimed in claim 7, wherein the peripheral device comprises a plurality of sensors placed in multiple sensitive areas to determine one or more of (a) presence signals and (b) a position of the at least one user on a bed.

14. A computer program product for determining the quality of sleep of at least one user, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, said computer-readable program code portions comprising instructions for:

using a peripheral device to record a body motion signal of the at least one user, the peripheral device comprising a static sensor and a dynamic sensor;

using the peripheral device to establish a communication connection between the peripheral device and a mobile phone;

communicating the body motion signal from the peripheral device to the mobile phone; and

using the mobile phone to;

determine respiration amplitudes from the body motional signal;

detect a change in the body motion signal in a given window of time;

detect an increase or an absence of an increase in a respiration cycle amplitude in the given time window of time, wherein the respiration cycle amplitude is an average of the respiration amplitudes taken over the given window of time;

determine body posture changes of the at least one user when the change in the body motion signal and the increase in the respiration cycle amplitude are detected simultaneously;

determine body movements of the at least one user when the change in the body motion signal and the absence of the increase in the respiration cycle amplitude are detected simultaneously; and

determine the quality of sleep of the at least one user based on occurrences of the determined body posture changes and the determined body movements.

15. The computer program product as claimed in claim 14, wherein the body posture changes are further determined using a change in one or more signals determined from the body motion signal, the signals include:

a respiration cycle shape, a heartbeat cycle shape, a heartbeat cycle amplitude, and a value of presence signals.

16. The computer program product as claimed in claim 14, wherein the determination of the body posture changes of the at least one user includes:

classifying the body motion signal to feature vectors, the feature vectors associated with body postures.

17. The computer program product as claimed in claim 14, further comprising:

capturing one or more images and data of body postures of the at least one user during sleep;

storing the one or more of images and the data of the body postures of the at least one user into a data storage; and

displaying the one or more of the images and the data of the body postures a screen of the mobile phone.

18. The computer program product claimed in claim 14, wherein the dynamic sensor is one or more of a piezoelectric sensor and a piezo thin film sensor,

the static sensor is one or more of a strain gauge, a capacitive sensor, a proximity sensor, a thermocouple, and an inductive sensor, and

the peripheral device further comprises a plurality sensors placed on multiple sensitive areas to determine one or more of (a) presence signals and (b) a position of the at least one user on a bed.