Method for Characterizing and Identifying Task Evoked Pupillary Responses During Varying Workload Levels

Abstract

Understanding when operators are experiencing high workload is important in the design and implementation of Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) systems. Fortunately physiological metrics, such as pupillary reflexes, have been shown to correlate with increases in mental workload. This paper proposes an automated method for characterizing and identifying task evoked pupillary responses (TEPR) during various workload levels. This method captures findings and observations from previous TEPR studies in an automated algorithm. This algorithm characterizes the rate of pupil dilation and constriction into a TEPR area metric, which is then used to identify times of increased operator workload. Independent trial analysis shows the benefits of using the TEPR area for distinguishing different workload responses but additional investigation is needed to make the algorithm more robust to individual variability.

Get full access to this article

View all access options for this article.

References

Ahern

Beatty

Pupillary Responses During Information Processing Vary with Scholastic Aptitude Test Scores. Science, 205 (1979), 1289-1292.

Geacintov

Peavler

W. S.

Pupillography in industrial fatigue assessment. Journal of Applied Psychology, 59, 2 (1974), 213-216.

Iqbal

S.T.

Zheng

X.S.

Bailey

B.P.

Task-Evoked Pupillary Response to Mental Workload in Human-Computer Interaction. In Proc. CHI 2004, ACM Press (2004), 1477-1480.

Klingner

Kumar

Hanrahan

Measuring the Task-Evoked Pupillary Response with a Remote Eye Tracker. Proc. Symposium of Eye-Tracking Research and Applications 2008, ACM Press (2008), 69-72.

LeDuc

P. A.

Greig

J. L.

Dumond

S. L.

Involuntary Eye Responses as Measures of Fatigue in U.S. Army Apache Aviators. Aviation, Space, and Environmental Medicine, 76 (2005), C86-C91.

Marshall

S.P.

The Index of Cognitive Activity: Measuring Cognitive Workload. Proc. Human Factors, IEEE (2002), 5-9.

Marshall

S. P.

Identifying Cognitive State from Eye Metrics. Aviation, Space, Environmental Medicine. 78, (2007), B165-B175.

Moresi

Adam

J. J.

Rijcken

Van Gerven

P. W. M.

Kuipers

Jolles

Pupil dilation in response preparation. International Journal of Psychophysiology 67, 2 (2008). 124-130.

Nakayama

Shimizu

Frequency Analysis of Task Evoked Pupillary Response and Eye-movement. Proc. Symposium of Eye-Tracking Research and Applications 2004, ACM Press (2004), 71-76.

10.

Palinko

Kun

A.L.

Shyrokov

Heeman

Estimating Cognitive Load Using Remote Eye Tracking in a Driving Simulator. Proc. Symposium of Eye-Tracking Research and Applications 2010, ACM Press (2010), 141-144.

11.

Sweller

Discussion of Emerging Topics in Cognitive Load Research: Using Learner and Information Characteristics in the Design of Powerful Learning Environment. Applied Cognitive Psychology, 20 (2006), 353-357.

12.

Van Orden

K. F.

Limbert

Makeig

Jung

T.P.

Eye Activity Correlates of Workload during a Visuospatial Memory Task. Human Factors 43, 1 (2001), 111-121.

13.

Wilson

G.F.

Estepp

Davis

A Comparison of Performance and Psychophysiological Classification of Complex Task Performance. Proc. Human Factors and Ergonomics Society 2009, 141-145.

14.

Wilson

G. F.

Russell

C. A.

Real-Time Assessment of Mental Workload Using Psychophysiological Measures and Artificial Neural Networks. Human Factors 45, 4 (2003), 635-643.

15.

Wilson

G. F.

Russell

C. A.

Performance Enhancement in an Uninhabited Air Vehicle Task Using Psychophysiologically Determined Adaptive Aiding. Human Factors 49, 6 (2007), 1005-1018.