System and Method For Mental Workload Measurement Based on Rapid Eye Movement

• US 20080188777A1
• Filed: 09/03/2004
• Published: 08/07/2008
• Est. Priority Date: 09/03/2004
• Status: Abandoned Application

• Current Assignee: Canadian Space Agency (Government of Canada)
• Original Assignee: Canadian Space Agency (Government of Canada)
• Inventors: Kostin, Anatoly, Golikov, Yurij, Bedziouk, Serguei
• Application Number:
  US11/574,525
• Publication Number:
  US 20080188777A1
• Time in Patent Office: Days
• US Class Current: 600/595
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/16 Devices for psychotechnics using teaching or educational appliances G09B1/00 - G09B7/00; Testing reaction times ; Devices for evaluating the psychological state
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change

Abstract

A system and method for mental workload measurement and analysis are disclosed, which measure time intervals between saccades in eye movements. These intervals, called Inter Saccadic Intervals (ISI), characterize different levels of mental workload during operator performance, such as for MRO (Operator of Robot Manipulator). The device can include sensors for measuring oculometric potentials from the human face, an amplifier for amplifying measured potentials, an analog-to-digital (A/D) converter for generating digital output signals relating to the measured potentials, and a digital computer for continually measuring the electrooculogramic potential, extracting the saccades, calculating ISIS, and then determining quantitative criteria of mental workload based on the ISIS. Human performance can be measured and analyzed for: a proficiency level evaluation in simulators and real conditions; estimation of automated control system'"'"'s interface and software usability; and human controlled procedures complexity evaluation.

Claims

1. A method of measuring a mental workload for a human based on rapid eye movements, comprising:

identifying saccades in received eye movement data;

computing inter-saccadic intervals for the received eye movement data; and

determining the mental workload based on the computed inter-saccadic intervals.

2. The method of claim 1 wherein the step of identifying includes an automatic saccade determination scheme.

3. The method of claim 2 wherein the automatic saccade determination scheme is a velocity detection method.

4. The method of claim 3 wherein the velocity detection method includes:

computing eye movement speed based on the eye movement data;

comparing computed speed to threshold level; and

determining presence of saccade if computed speed is above the threshold.

5. The method of claim 4 wherein the step of computing eye movement speed includes:

smoothing the eye movement data with a low-pass digital filter to remove noise; and

numerically differentiating the filter output.

6. The method of claim 1 wherein the step of computing inter-saccadic intervals includes:

identifying a boundary of a saccade;

computing an inter-saccadic interval between the boundary of the current saccade and a boundary of a next saccade; and

storing parameter values in a memory.

7. The method of claim 6 wherein the step of identifying the boundary of the saccade comprises identifying a start of the saccade in response to a measured speed of eye movement being more than a threshold.

8. The method of claim 6 wherein the step of identifying the boundary of the saccade comprises identifying an end of the saccade in response to a measured speed of eye movement being less than a threshold.

9. The method of claim 1 further comprising the step of receiving the eye movement data.

10. The method of claim 1 further comprising the step of using the determined mental workload as feedback for training.

11. The method of claim 1 further comprising the step of identifying a peak mental workload value for a period of time.

12. The method of claim 1 further comprising the step of determining a real-time mental workload value.

13. An apparatus for measuring a mental workload for a human based on rapid eye movements, comprising:

means for identifying saccades in eye movement data;

means for computing inter-saccadic intervals in the received eye movement data; and

an analysis module for determining the mental workload based on the computed intersaccadic intervals.

14. The apparatus of claim 13 further comprising an ocular sensor for obtaining the eye movement data.

15. The apparatus of claim 14 wherein the ocular sensor includes at least one video ocular sensor.

16. The apparatus of claim 15 wherein the video ocular sensor is a digital video camera.

17. The apparatus of claim 14 wherein the ocular sensor includes at least one electric ocular sensor.

18. The apparatus of claim 17 wherein the electric ocular sensor includes:

electrodes;

an amplifier; and

an analog/digital (A/D) converter.

19. The apparatus of claim 13 further comprising a feedback unit for modifying a training program based on the determined mental workload.

20. The apparatus of claim 19 wherein the feedback unit includes an evaluation module for evaluating the determined mental workload in relation to stored mental workload data.

21. The apparatus of claim 20 wherein the feedback unit includes a control means for controlling access to a device being operated by an operator, based on an output of the evaluation module.

22. The apparatus of claim 19 wherein the feedback unit includes a display means for displaying mental workload data based on the determined mental workload.

23. A computer-readable medium including statements and instructions which, when executed by a computer, cause the computer to perform the steps of:

identifying saccades in received eye movement data;

computing inter-saccadic intervals for the received eye movement data; and

determining the mental workload based on the computed inter-saccadic intervals.

24. A signal embodied on a carrier wave, the signal comprising:

a first data segment for identifying saccades in received eye movement data;

a second data segment for computing inter-saccadic intervals for the received eye movement data; and

a third data segment for determining the mental workload based on the computed inter-saccadic intervals.