Physiological Correlates of Performance in a Long Duration Repetitive Visual Task.

Abstract

This study examined the effectiveness of heart activity (HR), respiration (RESP), muscle activity (EMG), skin conductance (SCL), and brain wave activity (EEG) as discriminators of correct vs. incorrect performance in a repetitive visual task of approximately 2 hours' duration. Separate analyses were made of the data to distinguish the operation of task difficulty from performance accuracy. In addition, both of the analyses were repeated using standard score transforms of the raw data to compensate for individual differences. An interactive statistical design was employed to assess the differential changes of the physiological variables with accuracy over time. This design proved to be of crucial importance in assessing this relationship since the accuracy main effect of RESP, EMG, and HR was nonsignificant in all four data treatments. The accuracy-by-time interactions were significant in a number of instances and established the efficacy of these parameters as discriminators of performance adequacy. Additionally, the standard score transforms proved essential to establishing these relationships when the variance in task difficulty was eliminated. The implication of these findings for the development of an alertness indicator is also discussed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1977
Accession Number
ADA043047

Entities

People

  • Nicholas John Carriero

Organizations

  • Human Engineering Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Counter IED

DTIC Thesaurus Topics

  • Accuracy
  • Brain Waves
  • Computer Programming
  • Computers
  • Data Analysis
  • Discriminators
  • Electrodes
  • Engineering
  • Frequency
  • Human Factors Engineering
  • Magnetic Tape
  • Measurement
  • Phase
  • Respiration
  • Standards
  • Tapes
  • Waves

Fields of Study

  • Psychology

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience