Bulletin of the Faculty of Education, Yamaguchi University

Faculty of Education, Yamaguchi University

PISSN : 2433-3670
NCID : AA12810513

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Bulletin of the Faculty of Education, Yamaguchi University Volume 72
published_at 2023-01-31

On the identification of hand movements by deep learning using myoelectric potentials

筋電位を利用した深層学習による手の動作識別について
Ito Masataka
Kitamoto Takuya
fulltext
9.38 MB
山口大学教育学部研究論叢_72_026.pdf
About This Article
近年の計算機の性能向上やフレームワークの発展により、深層学習が手軽に行えるようになってきた。従来、計算コストの問題や数値化するのが難しかった事象でも、高い精度で回帰や分類などが行えるようになってきている。本稿では、筋電位に注目し手の動作の識別について、深層学習で分類する。実験初期段階では手動で分類していたが、現段階では精度に問題はあるが、リアルタイムで分類することも可能となった。データ取得方法として、ワンボードマイコンの一種であるArduino Unoと簡易筋電センサーのMyo Ware筋電センサーを用いる。
このように、生体信号の一つである筋電位を用いて動作する義手を筋電義手と言い、多方面に渡る応用が期待される分野の一つである。また、筋電位を詳しく理解することによって心拍、脳波、脈拍などの他の信号の理解の助けになると考えられる。
Creator Keywords
深層学習
Arduino
Myo Ware筋電センサー
筋電位
動作識別
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Practice and consideration on online PCAGIP
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Consideration on the globalization of Japanese art and art education after the Meiji Period
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A study of teachers’ verbalization on early childhood care and education based on children in their classes
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On the identification of hand movements by deep learning using myoelectric potentials
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