User fatigue level analysis component

Patent metadata

Field	Value
Publication number	US-10624570-B2
Application number	US-201615197108-A
Country	US
Kind code	B2
Filing date	Jun 29, 2016
Priority date	Jul 1, 2015
Publication date	Apr 21, 2020
Grant date	Apr 21, 2020

Abstract

The disclosed embodiments include user fatigue level analysis components, real-time visual behavior measuring devices, and methods for determining the fatigue level of a user. In one embodiment, a user fatigue level analysis component includes a memory configured to store computer executable instructions and a processor for executing the computer executable instructions. The computer executable instructions comprise instructions for receiving at least a visual behavior parameter indicative of the real time visual behavior of the user, for providing at least one sleep quality history parameter indicative of the sleep quality history of the user, and for determining the fatigue level of the user based on the analysis of the combination of the at least one visual behavior parameter and the at least one sleep quality history parameter.

First claim

The invention claimed is:

1. A user fatigue level analysis component, comprising:
memory configured to store computer executable instructions; and
a processor for executing the computer executable instructions, wherein the computer executable instructions comprise instructions for:
receiving at least one visual behavior parameter indicative of a real time visual behavior of a user in activity;
receiving real-time head movement data relating to real time movement of the head of the user;
receiving life habit data relating to at least one parameter of a life habit of the user, the life habit of the user including at least one of: food consumption habits of the user or physical activity habits of the user;
obtaining at least one sleep quality history parameter indicative of a sleep quality history of the user, the sleep quality history being determined when the user is sleeping;
determining a fatigue level of the user based on an analysis of a combination of the at least one visual behavior parameter, the at least one sleep quality history parameter and the real-time head movement data; and
adjusting the fatigue level based on the life habit data.

2. The component of claim 1 , wherein a visual behavior parameter of the at least one visual behavior parameter relates at least to an eyelids activity of the user.

3. The component of claim 1 , wherein the computer executable instructions further comprise instructions for:
receiving real-time environment data relating to at least one real-time parameter of an environment of the user; and
determining the fatigue level considering the real-time environment data.

4. The component of claim 3 , wherein a real-time parameter of the at least one real time parameter of the environment of the user relates to features of light received by the user, said features comprising at least one of temporal features, spectral features, intensity of the light.

5. The component of claim 3 , wherein a real-time parameter of the at least one real-time parameter of the environment of the user relates to at least one of temperature of the environment of the user, noise of the environment of the user and a time of a day.

6. The component of claim 3 , wherein the computer executable instructions further comprise instructions for:
receiving real-time physiological data relating to at least one real-time parameter of a physiology of the user; and
determining the fatigue level considering the real-time physiological data.

7. The component of claim 6 , wherein a sleep quality history parameter of the at least one sleep quality history parameters relates at least to a sleep cycle efficiency history of the user.

8. The component of claim 7 , wherein the sleep quality history parameter relates at least to sleeping physiological data relating to at least one parameter of a physiology of the user upon sleeping, and wherein the computer executable instructions further comprises instructions for determining the fatigue level considering the real-time physiological data.

9. The component of claim 7 , wherein the sleep quality history parameter relates at least to sleeping environment data relating to at least one parameter of an environment of the user upon sleeping, and wherein the computer executable instructions further comprise instructions for determining the fatigue level considering the sleeping environment data.

10. The component of claim 1 , wherein the computer executable instructions further comprise instructions for:
receiving a feedback from the user on his level of fatigue; and
adjusting the analysis of the combination of the at least one visual behavior parameter and the at least one sleep quality history parameter used to determine the fatigue, such adjustment being based on the feedback from the user.

11. A real-time visual behavior measuring device comprising:
at least one sensor configured to measure in real time at least one visual behavior parameter indicative of the visual behavior of a user; and
a communication circuit configured to communicate a measured real time visual behavior parameter to a user fatigue level analysis component, the user fatigue level analysis component comprising:
memory configured to store computer executable instructions; and
a processor for executing the computer executable instructions,

wherein the computer executable instructions comprise instructions for:
receiving at least a visual behavior parameter indicative of the real time visual behavior of the user in activity;
receiving real-time head movement data relating to real time movement of the head of the user;
receiving life habit data relating to at least one parameter of a life habit of the user, the life habit of the user including at least one of: food consumption habits of the user or physical activity habits of the user;
obtaining at least one sleep quality history parameter indicative of the sleep quality history of the user, the sleep quality history being determined when the user is sleeping;
determining the fatigue level of the user based on the analysis of the combination of the at least one visual behavior parameter, the at least one sleep quality history parameter and the real-time head movement data; and
adjusting the fatigue level based on the life habit data.

12. The real-time visual behavior measuring device of claim 11 , wherein the real-time visual behavior measuring device is a head mounted device arranged to be mounted on the head of the user.

13. A system for determining a fatigue level of a user, the system comprising:
memory storing sleep quality parameters indicative of a sleep quality of the user,
a user fatigue level analysis component comprising:
memory configured to store computer executable instructions; and
a processor for executing the computer executable instructions,
wherein the computer executable instructions comprise instructions for:
receiving at least a visual behavior parameter indicative of a real time visual behavior of the user in activity;
receiving real-time head movement data relating to real time movement of the head of the user;
receiving life habit data relating to at least one parameter of a life habit of the user, the life habit of the user including at least one of: food consumption habits of the user or physical activity habits of the user;
obtaining at least one sleep quality history parameter indicative of the sleep quality history of the user, the sleep quality history
being determined when the user is sleeping;
determining the fatigue level of the user based on the analysis of the combination of the at least one visual behavior parameter, the at least one sleep quality history parameter and the real-time head movement data; and
adjusting the fatigue level based on the life habit data; and

a real-time visual behavior measuring device comprising:
at least one sensor configured to measure in real time at least one visual behavior parameter indicative of the visual behavior of the user; and
a communication circuit configured to communicate a measured real time visual behavior parameter to the user fatigue level analysis component.

14. The system of claim 13 , wherein the computer executable instructions further comprise instructions for:
receiving real-time environment data relating to at least one real-time parameter of an environment of the user; and
determining the fatigue level considering the real-time environment data.

15. The system of claim 14 , wherein the computer executable instructions further comprise instructions for:
receiving real-time physiological data relating to at least one rea

Assignees

• Essilor Int

Inventors

• Lore Marie
• Barrau Coralie
• Villette Thierry

Classifications

• G08B21/06

  indicating a condition of sleep, e.g. anti-dozing alarms · CPC title

• A61B5/7282

  Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818) · CPC title

• A61B5/6803

  Head-worn items, e.g. helmets, masks, headphones or goggles · CPC title

• A61B5/165 Primary

  Evaluating the state of mind, e.g. depression, anxiety · CPC title

• A61B5/1103

  Detecting muscular movement of the eye, e.g. eyelid movement · CPC title