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Quantitative Evaluation of Mental Workload by Using Model of Involuntary Eye Movement

  • Goro Obinata
  • Satoru Tokuda
  • Katsuyuki Fukuda
  • Hiroto Hamada
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5639)

Abstract

This study considers a new method to quantify mental workloads (MWL) by using mathematical models for reflex movement of eye. Several mathematical models of reflex movements have been proposed and experimentally verified by physiologists. In those models, some models of vestibulo-ocular reflex (VOR) have sufficient accuracy to predict eye movements of individuals. The engagement of brain function to VOR is known in the learning process or in the adaptation process. This leads to the assumption that metal workloads appears in the change of characteristics of VOR. So as to confirm the assumption, we have designed an experimental setup and carried out several experiments. In the experiments, subject’s VOR responses have be accurately predicted by the mathematical model which is a dynamical model with the input of head movements and the output of eye movements. The model dynamics have changed while the subject was engaging in a higher cognitive activity. The coherence between the predicted VOR from the identified model of the particular subject and the observed VOR was as high as 0.92 when there was no additional mental demands. However, the changing MWL over five different n-back tasks revealed the clear correlation between the predicted VOR coherences and the MWL demands. This shows that MWL can be objectively quantified by measuring the error between observed VOR responses and the predicted VOR ones from the identified model.

Keywords

Mental Workload Mental Demand Reflex Movement Final Common Path Simple Reaction Task 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Goro Obinata
    • 1
  • Satoru Tokuda
    • 2
  • Katsuyuki Fukuda
    • 1
  • Hiroto Hamada
    • 3
  1. 1.EcoTopia Science InstituteNagoya UniversityNagoyaJapan
  2. 2.Wichita State UniversityKansasUSA
  3. 3.Toyota Motor Co. Ltd.ToyotaJapan

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