Mental alertness level determination

• US 7,344,251 B2
• Filed: 02/23/2006
• Issued: 03/18/2008
• Est. Priority Date: 02/23/2005
• Status: Active Grant

• Current Assignee: EyeTracking, Inc.
• Original Assignee: EyeTracking, Inc.
• Inventors: Marshall, Sandra Peery
• Primary Examiner(s): HASAN, MOHAMMED A
• Application Number:
  US11/361,923
• Publication Number:
  US 20060203197A1
• Time in Patent Office: 754 Days
• Field of Search: 351/200, 351/203, 351/205, 351/209, 351/210, 351/246, 702/108, 702/182, 702/183, 702/187, 707/101, 707/104.1, 715/700, 600/544, 600/545, 600/5, 600/558
• US Class Current: 351/246
• CPC Class Codes: A61B 3/112 for measuring diameter of pupils
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• CPC Class Codes: A61B 5/18 for vehicle drivers or machine operators
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G06V 20/597 Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G06V 40/19 Sensors therefor

Abstract

A method for determining mental alertness level by monitoring point of gaze, pupillary movement, pupillary response, and other parameters in a subject performing a task, collecting the data in a database, analyzing the data in the database, and assigning the subject to a score indicating the subject'"'"'s particular mental alertness level in real time.

Claims

1. A method comprising:

obtaining eye-tracking data characterizing pupil dilation and point of gaze for an individual;

associating the eye-tracking data with one or more of a plurality of predefined mental alertness levels, the predefined mental alertness levels being generated by providing a setting characterized by one or more mental alertness levels, subjecting one or more than one test individuals engaged in a task to the setting, obtaining eye-tracking data from the test individuals, performing calculations on the eye-tracking data, and modeling the eye-tracking data to describe the one or more mental alertness levels; and

identifying the associated predefined mental alertness level.

2. The method of claim 1 wherein the plurality of predefined mental alertness levels is generated by:

providing a controlled setting characterized by one or more mental alertness levels;

subjecting one or more than one test individuals engaged in a task to the controlled setting;

obtaining eye-tracking data from the test individuals;

performing calculations on the eye-tracking data; and

modeling the eye-tracking data to describe the one or more mental alertness levels.

3. The method of claim 1, further comprising:

performing a discriminant function analysis of the eye-tracking data.

4. The method of claim 1, further comprising:

performing a nonlinear classification analysis of the eye-tracking data.

5. The method of claim 1, further comprising:

selecting a defined job, task, or activity for the individual to participate in.

6. The method of claim 5 wherein the defined job, task, or activity is selected from a group comprising:

driving a vehicle;

using a vehicle driving simulator;

undertaking problem solving;

or performing a visual search task.

7. The method of claim 1, wherein the eye-tracking data is selected from a group comprising pupil size, eyelid opening and closing speed, vertical eyelid separation distance, vertical location of the pupil, or horizontal location of the pupil.

8. The method of claim 1, wherein

the eye-tracking data are subjected to an analysis comprising one or more of:

calculating an Index of Cognitive Activity (ICA);

calculating a blink rate;

calculating a movement of the pupil in a horizontal and in a vertical plane; and

calculating a divergence of the horizontal location of the pupil.

9. The method of claim 1, wherein

the mental alertness level is selected from a group comprising:

fatigued/drowsy, bored, engaged, distracted, overloaded/stressed, and impaired.

10. The method of claim 1, wherein the data collection and analysis occur in real time.

11. The method of claim 1, wherein the data analysis is performed on pre-existing data.

12. The method of claim 1, wherein the monitoring of pupils occurs at a frequency of up to about 1000 observations per second.

13. The method of claim 1 further comprising:

monitoring eyes of one or more individuals.

14. The method of claim 1 further comprising:

recording the eye-tracking data.

15. The method of claim 1 further comprising:

storing the eye-tracking data.

16. The method of claim 1 further comprising:

reporting the mental alertness level of the one or more individuals.

17. The method of claim 16, further comprising:

alerting a third party to the mental alertness level of the individual.

18. The method of claim 16, further comprising:

providing the individual with feedback identifying the mental alertness level.

19. A method comprising:

obtaining eye-tracking data characterizing pupil dilation and point of gaze for an individual;

subjecting the eye-tracking data to an analysis comprising;

calculating an Index of Cognitive Activity (ICA);

calculating a blink rate;

calculating a movement of the pupil in a horizontal and in a vertical plane; and

calculating a divergence of the horizontal location of the pupil;

associating the analyzed eye-tacking data with one or more of a plurality of predefined mental alertness levels; and

identifying the associated predefined mental alertness level.

20. The method of claim 19 wherein the plurality of predefined mental alertness levels is generated by:

providing a controlled setting characterized by one or more mental alertness levels;

subjecting one or more than one test individuals engaged in a task to the controlled setting;

obtaining eye-tracking data from the test individuals;

performing calculations on the eye-tracking data; and

modeling the eye-tracking data to describe the one or more mental alertness levels.

21. The method of claim 19, further comprising:

performing a discriminant function analysis of the eye-tracking data.

22. The method of claim 19, further comprising:

performing a nonlinear classification analysis of the eye-tracking data.

23. The method of claim 19, wherein the eye-tracking data is selected from a group comprising pupil size, eyelid opening and dosing speed, vertical eyelid separation distance, vertical location of the pupil, or horizontal location of the pupil.

24. An apparatus comprising:

means for obtaining eye-tracking data characterizing pupil dilation and point of gaze for an individual;

means for associating the eye-tracking data with one or more of a plurality of predefined mental alertness levels, the predefined mental alertness levels being generated by providing a setting characterized by one or more mental alertness levels, subjecting one or more than one test individuals engaged in a task to the setting, obtaining eye-tracking data from the test individuals, performing calculations on the eye-tracking data, and modeling the eye-tracking data to describe the one or more mental alertness levels; and

means for identifying the associated predefined mental alertness level.

25. An apparatus comprising:

means for obtaining eye-tracking data characterizing pupil dilation and point of gaze for an individual;

means for subjecting the eye-tracking data to an analysis comprising;

calculating an Index of Cognitive Activity (ICA);

calculating a blink rate;

calculating a movement of the pupil in a horizontal and in a vertical plane; and

calculating a divergence of the horizontal location of the pupil;

means for associating the analyzed eye-tracking data with one or more of a plurality of predefined mental alertness levels; and

means for identifying the associated predefined mental alertness level.