Application of chaotic dynamics in EEG to assessment of mental workload

A. Murata, H. Iwase

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


In this paper, an attempt was made to evaluate mental workload using chaotic analysis of EEG. EEG signals registered from Fz and Cz during a mental task (mental addition) were recorded and analyzed using attractor plots, fractal dimensions, and Lyapunov exponents in order to clarify chaotic dynamics and to investigate whether mental workload can be assessed using these chaotic measures. The largest Lyapunov exponent for all experimental conditions took positive values, which indicated chaotic dynamics in the EEG signals. However, we could not evaluate mental workload using the largest Lyapunov exponent or attractor plot. The fractal dimension, on the other hand, tended to increase with the work level. We concluded that the fractal dimension might be used to evaluate a mental state, especially a mental workload induced by mental task loading.

Original languageEnglish
Pages (from-to)1112-1119
Number of pages8
JournalIEICE Transactions on Information and Systems
Issue number8
Publication statusPublished - Aug 2001
Externally publishedYes


  • Attractor plot
  • EEG
  • Fractal dimension
  • Largest Lyapunov exponent
  • Mental workload

ASJC Scopus subject areas

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


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