Abstract—This paper proposes an electroencephalogram (EEG)-based method for identifying the mechanism underlying brain activity during a voluntary movement. Our final goal is to develop a rehabilitation assistance system that can be used on a daily basis by observing a patient’s degree of functional recovery. In order to assist in ambulation rehabilitation, the mechanism related to the voluntary movement need to be identified. As a first step, we elucidated the mechanism underlying brain activity. The proposed method involves EEG recording, blind source separation, noise reduction, and feature enhancement. The EEG device has dry-type sensors. Independent component analysis is used to delink the signal. Median morphological filters are used to reduce EEG noise and emphasize the feature signal. To demonstrate the effectiveness of the proposed method, we conducted experiments using real EEG data.

Index Terms—Electroencephalogram (EEG), voluntary movement, brain activity, independent component analysis, median morphological filters, decision making.

N. Kuramoto, S. Ito, K. Sato, and S. Fujisawa are with the Graduate School of Institute of Technology and Science, Information Solution, The University of Tokushima, 770-8506 2-1, Minami-josanjima, Tokushima, Japan (e-mail: kuramoto-nobuhisa@iss.tokushima-u.ac.jp, s.ito@eco.tokushima-u.ac.jp, katsuyas@eco.tokushima-u.ac.jp, s-fuji@eco.tokushima-u.ac.jp ).

 

Cite: Nobuhisa Kuramoto, Shin-Ichi Ito, Katsuya Sato, and Shoichiro Fujisawa, "Electroencephalogram Analysis of Mechanisms Underlying Brain Activity during Voluntary Movement," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 4, no. 1, pp. 49-56, 2014.