MB-01 Mental tasks discrimination by Neural networks with Wavelet transform
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概要
- 論文の詳細を見る
The study mainly focuses on the analysis of Electroencephalogram, to classify mental tasks by using features based on wavelet transform. We have used the daubechies family wavelets, level 6,to transform obtained signal from EEG signal. Local features can be described well with wavelets that have extent in EEG. This offers improved features to the neural networks obtaining several classified mental tasks. Through several processes, it led us more developed variety mental tasks classification results. We find that the neural networks perform over 75% success resulting with small number of electrodes better than a previous 70% resulting.
- 一般社団法人日本機械学会の論文
著者
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Sasaki Minoru
Department of Acoustic Design,Kyushu Institute of Design
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Choi Kyoung
Department Of Materials Science And Engineering. Pohang University Of Science And Technology Pohang
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Choi Kyoung
Department Of Mechanical Engineering Gifu University
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Sasaki Minoru
Department Of Acoustic Design Kyushu Institute Of Design
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Sasaki Minoru
Department Of Mechanical Engineering Gifu University
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