Date of Award

12-26-2014

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Systems Engineering and Management

First Advisor

Michael E. Miller, PhD.

Abstract

Air Force missions continue to increase in complexity often imposing higher levels of task load from cognitive tasks on the operators. This increased task load manifests itself in increased cognitive workload and potentially derogated performance. While cognitive workload has been studied for decades, recent advances in objective workload models and physiology monitoring have the potential to provide a more robust understanding of workload, potentially allowing systems to adaptively employ automation to maintain operator peak performance. The current research sought to provide insight into the relationship between subjective workload, task performance, objective workload, and select physiology measures. Analysis of an existing data set was performed to determine if individuals exhibiting low performance and high workload were more likely to have physiology responses that increased with workload due to a stress response than other participants. This analysis provides an approach to investigating the relationships among the four classes of workload information. However, the results indicate that certain physiology measures are significantly correlated with objective workload, regardless of the performance and workload range of the participants. Unfortunately, relatively low correlations were observed among all dependent measures and therefore, further research is necessary to confidently address the hypothesis of the current research.

AFIT Designator

AFIT-ENV-MS-14-D-31

DTIC Accession Number

ADA614889

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