Chaos and Fractal Analysis of Electroencephalogram Signals during Different Imaginary Motor Movement Tasks(Cross-disciplinary physics and related areas of science and technology)
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概要
- 論文の詳細を見る
This paper presents the novel approach to evaluate the effects of different motor activation tasks of the human electroencephalogram (EEG). The applications of chaos and fractal properties that are the most important tools in nonlinear analysis are been presented for four tasks of EEG during the real and imaginary motor movement. Three subjects, aged 23-30 years, participated in the experiment. Correlation dimension (D_2), Lyapunov spectrum (λ_i), and Lyapunov dimension (D_L) are been estimated to characterize the movement related EEG signals. Experimental results show that these nonlinear measures are good discriminators of EEG signals. There are significant differences in all conditions of subjective task. The fractal dimension appeared to be higher in movement conditions compared to the baseline condition. It is concluded that chaos and fractal analysis could be powerful methods in investigating brain activities during motor movements.
- 社団法人日本物理学会の論文
- 2008-04-15
著者
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Soe Ni
Department Of Electrical Engineering Nagaoka University Of Technology
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Nakagawa Masahiro
Deparment Of Electrical Engineering Faculty Of Engineering Nagaoka University Of Technology
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