IEICE TRANSACTIONS on Information
Application of Chaotic Dynamics in EEG to Assessment of Mental Workload
Summary :
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.
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- IEICE TRANSACTIONS on Information Vol.E84-D No.8 pp.1112-1119
- Publication Date
- 2001/08/01
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- PAPER
- Category
- Medical Engineering
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Atsuo MURATA, Hirokazu IWASE, "Application of Chaotic Dynamics in EEG to Assessment of Mental Workload" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 8, pp. 1112-1119, August 2001, doi: .
Abstract: 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.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_8_1112/_p
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@ARTICLE{e84-d_8_1112,
author={Atsuo MURATA, Hirokazu IWASE, },
journal={IEICE TRANSACTIONS on Information},
title={Application of Chaotic Dynamics in EEG to Assessment of Mental Workload},
year={2001},
volume={E84-D},
number={8},
pages={1112-1119},
abstract={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.},
keywords={},
doi={},
ISSN={},
month={August},}
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TY - JOUR
TI - Application of Chaotic Dynamics in EEG to Assessment of Mental Workload
T2 - IEICE TRANSACTIONS on Information
SP - 1112
EP - 1119
AU - Atsuo MURATA
AU - Hirokazu IWASE
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2001
AB - 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.
ER -
English
