BABY SLEEP MONITOR

• US 20180000408A1
• Filed: 12/08/2015
• Published: 01/04/2018
• Est. Priority Date: 12/16/2014
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: HEINRICH, ADRIENNE, FONSECA, PEDRO MIGUEL
• Application Number:
  US15/533,388
• Publication Number:
  US 20180000408A1
• Time in Patent Office: Days
• CPC Class Codes: A61B 2503/04 Babies, e.g. for SIDS detection
• 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 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/1103 Detecting eye twinkling
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• 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 5/7267 involving training the classification device

Abstract

A sleep monitor for monitoring baby sleep uses sleep state classification based on heartbeat feature respiration features. The sleep monitor automatically retrains the classification during use of the sleep monitor. Training examples for use in this training process are generated automatically by detecting time instants whereat the baby in the bed is in a wake state, based on signals from the at least one of a sound feature detector a movement feature detector (112) and an open eye detector (114). The retraining may comprise using time sequence from the end of detection of wake states to assign a class to heartbeat feature and/or respiration feature values during that time sequence for the training process. In an embodiment, the retraining comprises clustering detected heartbeat feature and/or respiration feature values detected outside the detected wake states.

Claims

1. A sleep monitor for monitoring baby sleep, the sleep monitor comprising

a heartbeat feature detector and/or a respiration feature detector;

a heartbeat feature and/or respiration feature based sleep state classifier with an input coupled to the heartbeat feature detector and/or the respiration feature detector;

at least one of a sound feature detector, a movement feature detector and an open eye detector;

a processing circuit configured to repeatedly execute a retraining process of the sleep state classifier during use of the sleep monitor, wherein the processing circuit is configured to detect time instants whereat the baby in the bed is in a wake state based on signals from the at least one of a sound feature detector, movement feature detector and the open eye detector, and to use the detected time instants to generate or select training examples for the retraining process.

2. A sleep monitor according to claim 1, wherein the processing circuit is configured to detect the wake state based on whether a movement amplitude of a baby motion feature detected by the movement feature detector exceeds a first predetermined value, a loudness property of sound detected by the sound feature detector exceeds a second predetermined value, and/or the open eye detector detects an open eye on the baby in the bed.

3. A sleep monitor according to claim 1, comprising a movement feature detector, the processing circuit being configured to detect the wake state based at least on whether a movement amplitude of a baby movement feature detected by the movement feature detector exceeds a first predetermined value, the sleep state classifier having an input coupled to the movement feature detector, the sleep state classifier being configured to classify sleep states based on a value or values the heartbeat feature and/or the respiration feature and a value of the baby movement feature or a further baby movement feature detected by the movement feature detector.

4. A sleep monitor according to claim 1, wherein the processing circuit is configured to perform the retraining process comprising retraining classification of a plurality of sleeping states by the sleep state classifier, the processing circuit being configured to exclude a training example for use to train classification criteria for distinguishing between said plurality of sleeping states based on whether a measurement time interval used to obtain the training example comprises at least one of the detected time instants.

5. A sleep monitor according to claim 1, wherein the sleep state classifier is configured to assign measurement time intervals to sleep states from a wake state and a first sleeping state and a second sleeping state corresponding to quiet baby sleep and active baby sleep respectively, based at least on a value or values of the heartbeat feature, and/or the respiration feature obtained for said measurement time interval, the processing circuit being configured to provide training examples associated with the first sleeping state using heartbeat feature and/or respiration feature values obtained for training time intervals that follow directly after the detected time instants whereat the baby is in a nonsleep state.

6. A method of automatically monitoring baby sleep, the method comprising

detecting heartbeat features, movement features and/or respiration features of a baby for successive measurement time intervals;

automatically classifying sleep states of the baby associated with the successive measurement time intervals based on the heartbeat and/or respiration features of the measurement time intervals;

automatically repeatedly retraining the classification criteria used for said classifying during use, said retraining comprising

detecting time instants whereat the baby in the bed is in a wake state based on signals from at least one of a sound feature detector, a movement feature detector and an open eye detector,

using the detected time instants to generate or select training examples for the retraining.

7. A method according to claim 6, wherein said detecting of the time instants comprises detecting whether a movement amplitude of a baby movement feature detected by the movement feature detector exceeds a first predetermined value, a loudness property of sound detected by the sound feature detector exceeds a second predetermined value, and/or the open eye detector detects an open eye on the baby in the bed.

8. A method according to claim 6, comprising

detecting the wake state based at least on whether a movement amplitude of a baby movement feature detected by the movement feature detector exceeds a first predetermined value,

classifying sleep states based on a value or values the heartbeat feature and/or the respiration feature and on a value of the baby movement feature or a further baby movement feature detected by the movement feature detector.

9. A method according to claim 6, wherein said retraining comprises retraining the classification criteria of a plurality of sleeping states, the method comprising excluding training examples for use to train the classification criteria for distinguishing between said plurality of sleeping states based on whether a measurement time interval used to obtain the training example comprises at least one of the detected time instants.

10. A method according to claim 6, wherein said automatically classifying sleep states comprises assigning the measurement time intervals to sleep states from a wake state and sleeping states comprising a first sleeping state and a second sleeping state corresponding to active baby sleep and quiet baby sleep respectively, said retraining comprising providing training examples associated with the first sleeping state using heartbeat feature and/or respiration feature values obtained for training time intervals that follow directly after the detected time instants whereat the baby is in a non-sleep state.

11. A computer program product, comprising instructions for a programmable data processing system that, when executed by the data processing system, will cause the data processing system to execute the method of claim 6.