Application US20200397366

Sleep Activity Detection Method And Apparatus
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US20200397366

1-32. (canceled) (0)

33. A method for detecting sleep activity, the method comprising: (12) (6)

receiving one or more input signals;

performing normalisation of the one or more input signals;

calculating a circadian rhythm value from a circadian rhythm model and a sleep-wake pressure value from a sleep-wake pressure model;

performing segmentation of the normalised one or more input signals;

calculating a sleep probability value as a function of at least one characteristic of the segmented normalised one or more input signals, the calculated circadian rhythm value and the calculated sleep-wake pressure value; and

outputting an output signal indicating that the one or more input signals comprises a sleep episode, if the sleep probability value is above a predefined sleep detection threshold.

34. The method according to claim 33 wherein the one or more input signals are acceleration, light and sound signals. (0)

35. The method according to claim 33 wherein the segmentation is performed by applying the Bayesian Online Change Point Detection method to the one or more input signals. (0)

36. The method according to claim 33 wherein outlier detection and elimination is performed before the normalisation is performed. (0)

37. The method according to claim 33 wherein the one or more input signals are pre-processed to extract a specific characteristic of the signal which is in turn used as an input signal. (0)

38. The method according to claim 33 wherein the sleep detection threshold is determined based on a desired sensitivity and/or specificity. (0)

39. The method according to claim 33 wherein the input signals are combined using a weighted average function to calculate the sleep probability. (1) (0)

43. The method according to claim 33 wherein the one or more input signals consist of time series of digital sensor data from any of a heart rate sensor, a heart rate variability (HRV) sensor, a skin conductance sensor and derivatives thereof; an acceleration sensor, a rotation sensor, an orientation sensor, a geolocation sensor and a speed sensors; a sound sensor, a light sensor, an ambient air temperature sensor, a humidity sensor and an atmospheric pressure sensor. (0)

44. The method according claim 33 wherein the one or more input signals are received from a electrodermal response sensor, a body temperature sensor, an acceleration sensor, a rotation sensor, an orientation sensor, a geolocation sensor and a speed sensor; a sound sensor, a light sensor, an ambient air temperature sensor, a humidity sensor and/or an atmospheric pressure sensor. (0)

45. The method according to claim 33 wherein the one or more input signals comprises analogue sensor time series data discretised and converted into a digital time series prior to performing the method. (0)

46. The method according to claim 33 wherein the one or more input signal is a multi-channel sensor signal combined into a single channel. (2) (0)

49. The method according to claim 33 wherein the circadian rhythm model outputs the cardiac rhythm value as a function of time. (0)

50. The method according to claim 33 wherein the sleep-wake pressure model outputs a sleep-awake pressure value as a function of estimated sleep time and estimated awake time during a previous time period. (0)

51. An apparatus for detecting sleep activity, the apparatus comprising: (0) (8)

an input for receiving one or more input signals;

a processor for processing the input signals;

the processor being configured to execute a method comprising:

performing normalisation of the one or more input signals received by the input;

calculating a circadian rhythm value from a circadian rhythm model and a sleep-wake pressure value from a sleep-wake pressure model;

performing segmentation of the normalised one or more input signals;

outputting an output signal indicating that the one or more input signals comprises a sleep episode, if the sleep probability value is above a predefined sleep detection threshold.

52. A non-transitory computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out a method comprising: (0) (6)

receiving one or more input signals;

performing normalisation of the one or more input signals;

calculating a circadian rhythm value from a circadian rhythm model and a sleep-wake pressure value from a sleep-wake pressure model;

performing segmentation of the normalised one or more input signals;

outputting an output signal indicating that the one or more input signals comprises a sleep episode, if the sleep probability value is above a predefined sleep detection threshold.

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Application US20200397366

Sleep Activity Detection Method And Apparatus

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