Estimating Operator Workload from Small Participant Samples

Abstract

Get full access to this article

View all access options for this article.

References

Bierbaum

C. R.

Szabo

S. M.

Aldrich

T. B.

(1989). Task analysis of the UH-60 mission and decision rules for developing a UH-60 workload prediction model: Volume 1. Summary report. US Army Research Institute.

Breiman

(2001). Random Forests. Machine Learning, 45(1), 5–32.

Byrne

Parasuraman

(1996). Psychophysiology and adaptive automation. Biological Psychology, 42, 249–268. Retrieved from http://www.sciencedirect.com/science/article/pii/0301051195051619

Mitchell

D. K.

(2003). Advanced Improved Performance Researach Integration Tool (IMPRINT) Vetronics Technology Test Bed Model Development.

Rusnock

Borghetti

B. J.

McQuaid

(2015). Objective-Analytical Measures of Workload–the Third Pillar of Workload Triangulation? In Schmorrow

D. D.

Fidopiastis

C. M.

(Eds.), Foundations of Augmented Cognition (pp. 124–135). Springer International Publishing. http://doi.org/10.1007/978-3-319-20816-9_13

Smith

A. M.

Borghetti

B. J.

Rusnock

C. F.

(2015). Improving Model Cross-Applicability for Operator Workload Estimation. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 59(1), 681–685. http://doi.org/10.1177/1541931215591148