ELECTRONIC SWITCH FOR CONTROLLING A DEVICE IN DEPENDENCY ON A SLEEP STAGE

• US 20150302722A1
• Filed: 11/04/2013
• Published: 10/22/2015
• Est. Priority Date: 11/02/2012
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: HAAKMA, REINDER, BEREZHNYY, IGOR, FONSECA, PEDRO MIGUEL, HEINRICH, ADRIENNE
• Granted Patent: US 9,754,471 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2562/0247 Pressure sensors
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• 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: A61M 2021/0027 by the hearing sense
• CPC Class Codes: A61M 2021/0044 by the sight sense
• CPC Class Codes: A61M 2021/0083 especially for waking up
• CPC Class Codes: A61M 21/00 Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
• CPC Class Codes: A61M 2205/3331 Pressure; Flow
• CPC Class Codes: A61M 2205/502 User interfaces, e.g. screens or keyboards
• CPC Class Codes: A61M 2205/584 having a color code
• CPC Class Codes: A61M 2230/06 Heartbeat rate only
• CPC Class Codes: A61M 2230/10 Electroencephalographic signals
• CPC Class Codes: A61M 2230/42 Rate
• CPC Class Codes: A61M 2230/63 : Motion, e.g. physical activity
• CPC Class Codes: G04G 13/02 : at preselected times, e.g. alarm clocks
• CPC Class Codes: G04G 13/021 : Details
• CPC Class Codes: G04G 13/025 : acting only at one preselected time
• CPC Class Codes: G08B 13/181 : using active radiation detection systems
• CPC Class Codes: G08B 21/06 : indicating a condition of sleep, e.g. anti-dozing alarms

Abstract

An electronic switch for controlling a device (170) by switching a function of the device at least in dependency on a sleep stage of a human, the switch comprising an EEG data interface configured to receive brain activity data from an EEG sensor (120) configured to monitor electrical activity of the brain of the human during a training phase, an EEG sleep classifier (125) configured to classify sleep stages of the human from the received brain activity data, a body data interface configured to receive body activity data from an alternative sensor (30) configured to monitor a bodily function of the human both during the training phase and during a subsequent usage phase, the alternative sensor being different from the EEG sensor, an alternative sleep classifier (135) and a machine learning system (140), the machine learning system being configured to train the alternative sleep classifier (135) to classify a sleep stage of the human from the received body activity data, the learning system using sleep stages classified by the EEG sleep classifier (125) and concurrent body activity data received from the alternative sensor as training data, wherein in the usage phase the device (170) is controlled in dependency on sleep stages of the human classified by the alternative sleep classifier (135), and control logic (150) configured to at least determine that the classified sleep stage is one of a set of particular sleep stages and to switch a function of the device at least in dependency on said determination.

Claims

1. An electronic switch for controlling a device by switching a function of the device at least in dependency on a sleep stage of a human, the switch comprising

an EEG data interface configured to receive brain activity data from an EEG sensor configured to monitor electrical activity of the brain of the human during a training phase,

an EEG sleep classifier configured to classify sleep stages of the human from the received brain activity data,

a body data interface configured to receive body activity data from an alternative sensor configured to monitor a bodily function of the human both during the training phase and during a subsequent usage phase, the alternative sensor being different from the EEG sensor,

an alternative sleep classifier and a machine learning system, the machine learning system being configured to train the alternative sleep classifier to classify a sleep stage of the human from the received body activity data, the learning system using sleep stages classified by the EEG sleep classifier and concurrent body activity data received from the alternative sensor as training data, wherein in the usage phase the device is controlled in dependency on sleep stages of the human classified by the alternative sleep classifier, and

control logic configured to at least determine that the classified sleep stage is one of a set of particular sleep stages and to switch a function of the device at least in dependency on said determination,

the switch further comprising:

a statistical unit configured to

determine a statistical measure of the received body activity data during the training phase and store it as a reference measure, and to

determine the statistical measure of the received body activity data during the usage phase; and

a drift detection unit configured to detect a drift of the statistical measure determined during the usage phase and the reference measure, and upon detecting the drift signaling a user for recalibration of the alternative sleep classifier.

2. A switch as in claim 1, comprising a clock configured to indicate a current time, the switch being configurable with a first switching time-period, the control logic being configured to switch the function when both:

a current time indicated by the clock is in the first switching period, and

the classified sleep stage is one of the set of particular sleep stages.

3. A switch as in claim 2, configured to switch the function when a current time indicated by the clock is at the end of the first switching period regardless of the classified sleep stage.

4. A switch as in claim 1, wherein the control logic is configured to defer switching until the classified sleep stage remained in the set of particular sleep stages for a particular time period.

6. An electronic switch as in claim 1, wherein

the EEG sensor is configured to monitor when placed in close proximity or direct contact to the head of the human, and

the alternative sensor is configured to monitor without direct contact with the human.

7. An electronic switch as in claim 1 wherein the alternative sensor is configured to monitor at least one of respiration, heart and actigraph.

8. An electronic switch as in claim 1 wherein the alternative sensor comprises a pressure sensor for positioning in or under a mattress.

9. An alarm clock comprising

an electronic switch as in claim 1 configurable with a first switching time-period, and

a device configured to wake the human, e.g., through audio and/or visual stimuli, wherein

the control logic is configured to switch-on the device to wake the human.

10. An alarm clock as in claim 9, wherein at least the device configured to wake the human is arranged for wearing in a human ear.

11. A burglar alarm comprising

an electronic switch as in claim 1, and

an intrusion sensor for detecting an intrusion of a burglar,

a device configured to raise an alarm in response to the intrusion sensor detecting an intrusion, wherein

the control logic is configured to switch-on the device configured to raise an alarm.

12. An entertainment system comprising,

an electronic switch as in claim 1, and

a device configured to render video, wherein

the control logic is configured to switch-off the device configured to render video.

5. (canceled)

13. A method for controlling a device by switching a function of the device at least in dependency on a sleep stage of a human, the method comprising

monitoring electrical activity of the brain of the human during a training phase,

classifying sleep stages of the human from the monitored brain activity data by an electronic EEG sleep classifier,

monitoring a bodily function of the human both during the training phase and during a subsequent usage phase,

training an electronic alternative sleep classifier to classify a sleep stage of the human from the monitored body activity data, the learning system using sleep stages classified by the EEG sleep classifier and concurrent monitored body activity data as training data by a machine learning system,

classifying sleep stages of the human from the monitored body activity data by the alternative sleep classifier,

determining that the sleep stage classified by the alternative sleep classifier is one of a set of particular sleep stages, and

switching a function of a device at least in dependency on said determination,

the method further comprising:

determining a statistical measure of the received body activity data during the training phase and store it as a reference measure;

determining the statistical measure of the received body activity data during the usage phase;

detecting a drift of the statistical measure determined during the usage phase and the reference measure; and

upon detecting the drift signaling a user for recalibration of the alternative sleep classifier.

14. A computer program for controlling a device by switching a function of the device at least in dependency on a sleep stage of a human when the computer program is run on a computer, the computer program comprising computer program code means adapted to

receive brain activity data at an EEG data interface from an EEG sensor configured to monitor electrical activity of the brain of the human during a training phase,

classify sleep stages of the human from the received brain activity data,

receive body activity data from an alternative sensor configured to monitor a bodily function of the human both during the training phase and during a subsequent usage phase,

train an alternative sleep classifier to classify a sleep stage of the human from the received body activity data, the learning system using sleep stages classified by the EEG sleep classifier and concurrent body activity data received from the alternative sensor as training data,

classify sleep stages of the human from the monitored body activity data by the alternative sleep classifier,

determine that the sleep stage classified by the alternative sleep classifier is one of a set of particular sleep stages, and

switching a function of a device at least in dependency on said determination,

the computer method further comprising computer program code means adapted to:

determine a statistical measure of the received body activity data during the training phase and store it as a reference measure;

determine the statistical measure of the received body activity data during the usage phase;

detect a drift of the statistical measure determined during the usage phase and the reference measure; and

upon detecting the drift signal a user for recalibration of the alternative sleep classifier.

15. A computer program as claimed in claim 14 embodied on a computer readable medium.