Date of Award
3-2001
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Operational Sciences
First Advisor
Jeffrey W. Lanning, PhD
Abstract
The problem of classifying pilot mental workload is important to the United States Air Force. Pilots are more subject to errors and G-induced loss of consciousness during periods of mental overload and task saturation. Often the result is the loss of aircraft, and in extreme cases, the loss of the pilot's life. Current research efforts use different psychophysiological features to classify pilot mental workload. These include cardiac, ocular, respiratory, and brain activity measures. The focus of this effort is to apply statistical process control methodology on different psychophysiological features in an attempt to classify pilot mental workload. The control charts track these features throughout the flight, and classify a segment as high workload if the measurements of these feature, are greater than predefined control limits. We find that using certain control charts prove to be effective workload classifiers and maintain high classification accuracies when applied to other flight data.
AFIT Designator
AFIT-GOR-ENS-01M-10
DTIC Accession Number
ADA391262
Recommended Citation
Kudo, Terence Y., "Using Statistical Process Control Methods to Classify Pilot Mental Workload" (2001). Theses and Dissertations. 4649.
https://scholar.afit.edu/etd/4649