Recognition of EMG signal patterns by neural networks

Yuji Matsumura, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu, Fumiaki Takeda

研究成果: Conference article査読

1 被引用数 (Scopus)


This paper tries to recognize EMG signals by using neural networks. The electrodes under the dry state are attached to wrists and then EMG is measured. These EMG signals are classified into seven categories, such as neutral, up and down, right and left, wrist to inside, wrist to outside by using a neural network. The NN learns FFT spectra to classify them. Moreover, we structuralized NN for improvement of the network. It is shown that our approach is effective to classify the EMG signals by means of computer simulations.

ジャーナルLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
2773 PART 1
出版ステータスPublished - 2003 1 1
イベント7th International Conference, KES 2003 - Oxford, United Kingdom
継続期間: 2003 9 32003 9 5

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)


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