Evaluation of mental fatigue in human-computer interaction - Analysis using feature parameters extracted from event-related potential

Atsuo Murata, Atsushi Uetake

Research output: Contribution to conferencePaper

8 Citations (Scopus)

Abstract

This study made an attempt to evaluate mental fatigue induced during a VDT task using feature parameters extracted from event-related potential (P300). Since the peak of the grand averaged P300 waveform is not clear, it is sometimes difficult to detect the amplitude and the latency. The removal of the noisy EEG waveform based on the cross correlation between the grand average waveform and each waveform was found to be effective for making the waveform clear. The parameter extraction methods using a principal component analysis or temporal changes of cross correlation between the grand average and each waveform were used to evaluate mental fatigue. As a result, P300b component and the standard deviation of the time lag that corresponded to the maximum cross correlation between the grand averaged waveform and each waveform were found to reflect some aspects of mental fatigue (the decrease of the cognitive information processing function).

Original languageEnglish
Pages630-635
Number of pages6
Publication statusPublished - Dec 1 2001
Externally publishedYes
Event10th IEEE International Workshop on Robot and Human Communication - Bordeaux-Paris, France
Duration: Sep 18 2001Sep 21 2001

Other

Other10th IEEE International Workshop on Robot and Human Communication
CountryFrance
CityBordeaux-Paris
Period9/18/019/21/01

Keywords

  • Amplitude
  • Cross correlation
  • ERP
  • Fatigue
  • Latency
  • Mental task
  • P300 components
  • Principal component analysis

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software

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