Evaluation of mental workload by variability of pupil area

Atsuo Murata, Hirokazu Iwase

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

It is generally known that the autonomie nervous system regulates the pupil. In this study, we attempted to assess mental workload on the basis of the fluctuation rhythm in the pupil area. Controlling the respiration interval, we measured the pupil area during mental tasking for one minute. We simultaneously measured the respiration curve to monitor the respiration interval. We required the subject to perform two mental tasks. One was a mathematical division task, the difficulty of which was set to two, three, four, and five dividends. The other was a Sternberg memory search task, which had four work levels defined by the number of memory sets. In the Sternberg memory search, the number of memory set changed from five to eight. In such a way, we changed the mental workload induced by mental loading. As a result of calculating an autoregressive (AR) power spectrum, we could observe two peaks which corresponded to the blood pressure variation and respiratory sinus arrhythmia under a low workload. With an increased workload, the spectral peak related to the respiratory sinus arrhythmia disappeared. The ratio of the power at the low frequency band, from 0.05-0.15Hz, to the power at the respiration frequency band, from 0.35-0.4Hz, increased with the work level. In conclusion, the fluctuation of the pupil area is a promising means for the evaluation of mental workload or autonomie nervous function.

Original languageEnglish
Pages (from-to)1187-1190
Number of pages4
JournalIEICE Transactions on Information and Systems
VolumeE83-D
Issue number5
Publication statusPublished - Jan 1 2000
Externally publishedYes

Keywords

  • Autonomie nen-ous system
  • Blood pressure variation
  • Mental workload
  • Pupil area
  • Respiratory sinus arrhythmia

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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