Combined Eye Activity Measures Accurately Estimate Changes in Sustained Visual Task Performance
Abstract
Five concurrent eye activity measures were used to model fatigue-related changes in performance during a visual compensatory tracking task. Nine participants demonstrated considerable variations in performance level during two 53-min testing sessions in which continuous video-based eye activity measures were obtained. Using a trackball, participants were required to maneuver a target disk (destabilized by pseudorandom wind forces) within the center of an annulus on a CRT display. Mean tracking performance as a function of time across 18 sessions demonstrated a monotonic increase in error from 0 to 11 min, and a performance plateau thereafter. Individual performance fluctuated widely around this trend with an average root mean square (RMS) error of 2.3 disk radii. For each participant, moving estimates of blink duration and frequency, fixation dwell time and frequency, and mean pupil diameter were analyzed using non-linear regression and artificial neural network techniques. Individual models were derived using eye and performance data from one session and cross-validated on data from a second session run on a different day. Results suggest that information from multiple eye measures may be combined to produce accurate individualized real-time estimates of sub-minute scale performance changes during sustained tasks.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2000
- Accession Number
- ADA458647
Entities
People
- Karl F. Van Orden
- Scott Makeig
- Tzyy-Ping Jung
Organizations
- Naval Health Research Center