Mental Workload Assessment in the Cockpit: Feasibility of Using Electrophysiological Measurements. Phase 1

Abstract

Limitations in people's ability to process and respond to information have become a limiting factor in advanced military aircraft systems. Accordingly, the USAF OSR has been sponsoring research on measuring mental workload as a prerequisite to developing cockpit systems which take the pilot's mental state into account in optimizing overall system performance. During Phase I, we performed a feasibility study in which we analyzed physiological data from four USAF fighter test pilots in search of ways to distinguish between two laboratory tasks which had the same stimulus and response components but differed in level of mental workload. Several electrophysiological measures, alone and in combination, were investigated for their discriminating power including regional brain electrical activity, scalp muscle potentials, and hem and eye activity. Measures were restricted to those which could be recorded in the cockpit, and. in the case of brain signals, to those least likely to be contaminated by head, body and eye movement artifacts. Using a neural network algorithm, we achieved an average of 97% accuracy in classifying independent testing data for the four subjects as either high or low mental workload. Although the results should be interpreted cautiously because of the small number of subjects and the use of artificial laboratory tasks, they suggest that further research will make useful progress in developing a physiological metric of mental workload suitable for use in the cockpit.

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Document Details

Document Type
Technical Report
Publication Date
Apr 30, 1992
Accession Number
ADA254138

Entities

People

  • A. S. Gevins
  • H. M. Leong

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Aircrafts
  • Algorithms
  • Biophysics
  • Cognition
  • Cognitive Workload
  • Eye Movements
  • Flight Simulators
  • Measurement
  • Military Aircraft
  • Neural Networks
  • Pattern Recognition
  • Psychology
  • Psychophysiology
  • Signal Processing
  • Task Performance And Analysis

Readers

  • Aerospace Engineering
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience

Technology Areas

  • AI & ML