Development of Neurophysiological and Behavioral Metrics of Human Performance.

Abstract

The purpose of this program is to develop metrics derived from multidimensional behavioral and neurophysiological indices which may ultimately be applied across a wide range of tasks to describe and predict human performance. This year's effort represented two different approaches to this problem: the development of a methodology for examining clutter factors that affect target identification, and the evaluation of Catastrophe Theory as a potential metric for describing discontinuities in human behavior. Initial analysis of the behavioral data has been computed and is reported here. It is clear that the system provides a powerful, flexible tool for study of visual clutter. A large representative bibliography of application of Catastrophe Theory has been compiled and is part of this report. Evaluation of the usefulness of Catastrophe Theory as a metric for predicting human performance is clear at this time. The theory allows qualitative construction of models which reflect the behavior of systems in which discontinuities are observed, but at present does not allow quantative, predictive modeling of such systems. At present, then, Catastrophe Theory would not seem to be suitable for generating predictive metrics of human performance.

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Document Details

Document Type
Technical Report
Publication Date
Nov 30, 1977
Accession Number
ADA053018

Entities

People

  • Samuel L. Moise Jr.

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Biological Sciences
  • Biology
  • Brain
  • Chemical Reactions
  • Computational Science
  • Control Surfaces
  • Data Analysis
  • Developmental Biology
  • Differential Equations
  • Equations
  • Lepidoptera
  • Medical Personnel
  • Phase Transformations
  • Social Problems
  • Social Sciences
  • Two Dimensional

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Software Engineering.
  • Theoretical Analysis.