Fatigue monitoring and management system

Patent metadata

Field	Value
Publication number	US-2016270718-A1
Application number	US-201415028311-A
Country	US
Kind code	A1
Filing date	Oct 6, 2014
Priority date	Oct 9, 2013
Publication date	Sep 22, 2016
Grant date	—

Abstract

A system monitors fatigue of a user. The system ( 100 ) may include one or more data sources, such as a non-obtrusive sleep sensor, configured to generate objective sleep measures of the user. The system may also include a fatigue monitoring module, which may be configured to generate an assessment, such as in one or more processors, of the fatigue state of the user based on the data from the one or more data sources.

First claim

1 . A system for monitoring fatigue of a user, the system comprising:
one or more data sources, comprising: a non-obtrusive sleep sensor configured to generate objective sleep measures of the user; and a fatigue monitoring module of a processor, the module configured to generate an assessment of a fatigue state of the user based on the data from the one or more data sources.

2 . A system according to claim 1 , wherein the one or more data sources further comprises one or more of:
an activity sensor configured to generate physical activity data of the user; an environmental sensor configured to generate environmental data relating to ambient conditions in a sleep location of the user; a device configured to capture subjective user data related to the user's self-perceived fatigue state; a device configured to capture daytime vital signs data of the user; a device configured to capture objective measurements of fatigue or sleepiness of the user; a clock; and work pattern information for the user.

3 . A system according to claim 2 , wherein the subjective user data comprises lifestyle parameters comprising one or more of:
caffeine intake; stress levels; energy levels; state of mind; and perceived sleep quality.

4 . A system according to claim 2 , wherein the environmental data comprises one or more of season, weather, and allergy information.

5 . A system according to claim 2 , wherein the environmental data comprises one or more of ambient temperature, ambient audio levels, light levels, air quality, and humidity.

6 . A system according to claim 2 , wherein the objective measurements of fatigue or sleepiness are obtained from user tests.

7 . A system according to claim 2 , wherein the objective measurements of fatigue or sleepiness are obtained from game play by the user.

8 . A system according to claim 1 , wherein the fatigue monitoring module generates the assessment of the fatigue state of the user based on a historical database configured to capture data from the one or more data sources over a predetermined time window.

9 . A system according to claim 8 , wherein the fatigue monitoring module is further configured to generate the assessment of the fatigue state of the user based on baseline parameters for the user derived from trend analysis of the data in the historical database.

10 . A system according to claim 1 , wherein the fatigue monitoring module is further configured to generate the assessment of the fatigue state of the user based on a population database comprising data from the one or more data sources from multiple users of the system.

11 . A system according to claim 1 , wherein the fatigue monitoring module is further configured to generate the assessment of the fatigue state of the user based on baseline parameters for the user derived from responses to a questionnaire.

12 . A system according to claim 1 , wherein the sleep sensor is further configured to provide a sleep disordered breathing measure.

13 . A system according to claim 12 , wherein the sleep disordered breathing measure is a snoring measure.

14 . A system according to claim 13 , wherein the sleep sensor data is combined with audio data from an audio sensor to obtain the snoring measure.

15 . A system according to claim 14 , wherein the snoring measure is restricted to intervals when the sleep sensor data indicates that the user is present and asleep.

16 . A system according to claim 14 , wherein the sleep sensor is a movement sensor, and obtaining the snoring measure comprises detecting a snoring-like event in the audio data simultaneous with a high frequency component in a respiratory movement signal from the movement sensor.

17 . A system according to claim 12 , wherein the sleep disordered breathing measure is an apnea-hypopnea index.

18 . A system according to claim 12 , wherein the sleep disordered breathing measure is an elevated breathing rate.

19 . A system according to claim 1 , wherein the assessment of the fatigue state of the user comprises an estimate of a present fatigue state of the user.

20 . A system according to claim 1 , wherein the assessment of the fatigue state of the user comprises a prediction of a future fatigue state of the user at a specified time.

21 . A system according to claim 1 , wherein the objective sleep measures comprise one or more of:
heart rate; breathing rate; biomotion levels; sleep statistics; galvanic skin response; and body temperature.

22 . A system according to claim 21 , wherein the sleep statistics comprise one or more of:
duration of sleep; quality of sleep; number of interruptions of sleep; REM sleep duration; wake after sleep onset; sleep inertia; and sleep latency.

23 . A system according to claim 1 , further comprising a third party information module configured to provide information to a third party related to the assessment of the fatigue state of the user.

24 . A system according to claim 1 , further comprising a user information module configured to provide information to the user related to the assessment of the fatigue state of the user.

25 . A system according to claim 1 , wherein the sleep sensor is a sensor integrated with a respiratory pressure therapy device from which the user is receiving CPAP therapy.

26 . A system according to claim 1 , wherein the fatigue monitoring module is a linear classifier that is configured to linearly combine the data from the one or more data sources to generate a fatigue index.

27 . A system according to claim 1 , wherein the fatigue monitoring module applies a rule set to the data from the one or more data sources to generate a fatigue index.

28 . A system according to claim 26 , wherein the fatigue index is mapped to one of set of fatigue states.

29 . A system according to claim 1 , wherein the fatigue monitoring module is implemented on a processing device associated with the user, the processing device being connected to the one or more data sources.

30 . A system according to claim 1 , wherein the fatigue monitoring module is implemented at a remote server connected to the one or more data sources over a network.

31 . A method of monitoring fatigue of a user, the method comprising generating, in one or more processors, an assessment of a fatigue state of the user based on data from one or more data sources, the data comprising objective sleep measures of the user generated by a non-obtrusive sleep sensor.

32 . A method according to claim 31 , further comprising providing the user with the fatigue state assessment.

33 . A method according to claim 31 , further comprising making a recommendation to the user based on the fatigue state assessment.

34 . A method according to claim 33 , wherein the recommendation is an ideal time for the user to go to sleep.

35 . A method according to claim 33 , wherein the recommendation is an optimal time for the user to wake up.

36 . A method according to claim 33 , wherein the user is undergoing CPAP therapy, and the recommendation is a recommendation to improve the CPAP therapy.

37 . A method according to claim 31 , further comprising providing a third party with

Assignees

• Resmed Sensor Tech Ltd

Inventors

• Heneghan Conor
• Mccourt Ciaran Gerard
• Mcmahon Stephen
• Shouldice Redmond

Classifications

• A61M16/0069

  the speed thereof being controlled by respiratory parameters, e.g. by inhalation · CPC title

• A61B5/0478

  Human Necessities · mapped topic

• A61B5/02055

  Simultaneously evaluating both cardiovascular condition and temperature · CPC title

• A61B5/0533

  Measuring galvanic skin response · CPC title

• A61B5/7264

  Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems · CPC title