System and method for identifying fatigue sources

• US 9,848,828 B2
• Filed: 04/23/2014
• Issued: 12/26/2017
• Est. Priority Date: 10/24/2013
• Status: Active Grant

• Current Assignee: Logitech Europe S A (Logitech International SA)
• Original Assignee: Logitech Europe S A (Logitech International SA)
• Inventors: Wisbey, Ben, Shepherd, David, Diesterbeck, Hagen, Armstrong, Judd
• Primary Examiner(s): PHAM, QUANG
• Application Number:
  US14/259,725
• Publication Number:
  US 20150120203A1
• Time in Patent Office: 1,343 Days
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/4815 Sleep quality
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6826 Finger
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/63 for local operation

Abstract

A system for identifying fatigue sources includes a processor and at least one computer program residing on the processor. The computer program is stored on a non-transitory computer readable medium having computer executable code embodied thereon. The computer executable code is configured to detect a fatigue level. The computer executable code is further configured to receive fatigue contribution data. In addition, the computer executable code is configured to identify a fatigue source based on the fatigue level and the fatigue contribution data.

Claims

1. A system for identifying fatigue sources for a user, comprising:

a processor;

a first sensor and one or more second sensors, wherein at least one of the one or more second sensors is a movement monitoring device configured to detect movement of the user'"'"'s body; and

at least one computer program residing on the processor,

wherein the at least one computer program is stored on a non-transitory computer readable medium having computer executable program code embodied thereon, the computer executable program code executed by the processor and configured to;

detect a fatigue level for the user from the first sensor when the first sensor is worn by the user;

receive fatigue contribution data for the user from the one or more second sensors when the one or more second sensors are worn by the user, wherein the fatigue contribution data comprises data of fatigue contribution parameters, and wherein the fatigue contribution data comprises activity data from one or more hours prior to the detection of the fatigue level of the user;

determine a relative contribution of each of a plurality of fatigue sources to the fatigue level of the user based on the received fatigue contribution data, wherein the relative contribution of at least one fatigue source is derived from the fatigue contribution data received from the movement monitoring device;

identify a primary fatigue source for the user out of the plurality of fatigue sources based on the relative contribution of each of the plurality of fatigue sources to the fatigue level of the user, wherein the identify the primary fatigue source for the user out of the plurality of fatigue source comprises ranking the plurality of fatigue sources, wherein the processor is configured to maintain historical information about the fatigue levels, the fatigue contribution parameters, and the fatigue sources to create and update a fatigue profile for the user based on the historical information; and

display the primary fatigue source for the user on a screen,

wherein the display includes a feature for allowing a user to confirm the identified primary fatigue source.

2. The system of claim 1, wherein the activity data is associated with at least one of an activity type, an activity intensity, an activity duration, and an activity periodicity.

3. The system of claim 1, wherein the fatigue contribution data comprises sleep data, and wherein the sleep data is associated with at least one of a sleep duration, a sleep timing, a sleep quality, and an ambient light.

4. The system of claim 1, wherein the fatigue contribution data comprises location data.

5. The system of claim 4, wherein the location data is associated with at least one of a GPS location, an altitude, and an ambient temperature.

6. The system of claim 1, wherein the fatigue contribution data comprises calendar data.

7. The system of claim 1, wherein the fatigue source comprises at least one of an activity type, an activity intensity, an activity duration, and an activity periodicity.

8. The system of claim 1, wherein

the identifying the primary fatigue source for the user further comprises determining deviations of different fatigue contribution parameters from typical ranges for the different respective fatigue contribution parameters based on the fatigue profile for the user.

9. A method for identifying fatigue sources for a user using an identifying fatigue source system comprising a processor and at least one computer program residing on the processor, wherein the at least one computer program is stored on a non-transitory computer readable medium having computer executable program code embodied thereon, the computer executable program code executed by the processor to perform method steps, comprising:

detecting a fatigue level for the user from a first sensor when the first sensor is worn by the user;

receiving fatigue contribution data for the user from one or more second sensors when the one or more second sensors are worn by the user, wherein at least one of the one or more second sensors is a movement monitoring device configured to detect movement of the user'"'"'s body, wherein the fatigue contribution data comprises data of fatigue contribution parameters; and

wherein the fatigue contribution data comprises activity data from one or more hours prior to the detecting the fatigue level for the user;

determining a relative contribution of each of a plurality of fatigue sources to the fatigue level of the user based on the received fatigue contribution data, wherein the relative contribution of at least one fatigue source is derived from the fatigue contribution data received from the movement monitoring device;

identifying a primary fatigue source for the user out of the plurality of fatigue sources based on the relative contribution of each of the plurality of fatigue sources to the fatigue level of the user, wherein the identifying the primary fatigue source for the user out of the plurality of fatigue source comprises ranking the plurality of fatigue sources, wherein the processor is configured to maintain historical information about the fatigue levels, the fatigue contribution parameters, and the fatigue sources to create and update a fatigue profile for the user based on the historical information;

displaying the primary fatigue source for the user on a screen,

wherein the display includes a feature for allowing a user to confirm the identified primary fatigue source; and

adjusting a lifestyle of the user based on the identified primary fatigue source.

10. The method of claim 9,

wherein the identifying the primary fatigue source for the user further comprises determining deviations of different fatigue contribution parameters from typical ranges for the different respective fatigue contribution parameters based on the fatigue profile for the user.