講演名 | 2012-11-17 Prediction of Joint angle from Muscle Activities decoded from Electrocorticograms in Primary Motor Cortex , |
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抄録(和) | |
抄録(英) | Electrocorticography (ECoG) has drawn attention as an effective recording approach for less invasive brain-machine interfaces (BMI). Previous studies succeeded in classifying the movement direction and predicting hand trajectories from ECoGs. Despite such successful studies, there still remain considerable works for the purpose of realizing an ECoG-based BMI robot. We developed a method to predict multiple muscle activities from ECoG measurements. We also verified that ECoG signals could be effective for predicting muscle activities in time varying series for preforming sequential movements. Each ECoG signal was filtered by different bandpass filters for sensorimotor rhythms, normalized by the standard z-score, and smoothed by a Gaussian filter. We used sparse linear regression to find the best fit between frequency bands of ECoG and electromyogram (EMG). We also predicted angle of 4 DOF robot arm from the decoded EMG using 3-layer neural network. Consequently, this study shows that it could derive online prediction of angle of robot arm from ECoG signals. |
キーワード(和) | |
キーワード(英) | ECoG / BMI / EMG / prediction |
資料番号 | MBE2012-57,NC2012-62 |
発行日 |
研究会情報 | |
研究会 | MBE |
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開催期間 | 2012/11/9(から1日開催) |
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委員長氏名(和) | |
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幹事氏名(和) | |
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幹事補佐氏名(和) | |
幹事補佐氏名(英) |
講演論文情報詳細 | |
申込み研究会 | ME and Bio Cybernetics (MBE) |
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本文の言語 | ENG |
タイトル(和) | |
サブタイトル(和) | |
タイトル(英) | Prediction of Joint angle from Muscle Activities decoded from Electrocorticograms in Primary Motor Cortex |
サブタイトル(和) | |
キーワード(1)(和/英) | / ECoG |
第 1 著者 氏名(和/英) | / Duk SHIN |
第 1 著者 所属(和/英) | Precision and Intelligence Laboratory, Tokyo Institute of Technology |
発表年月日 | 2012-11-17 |
資料番号 | MBE2012-57,NC2012-62 |
巻番号(vol) | vol.112 |
号番号(no) | 297 |
ページ範囲 | pp.- |
ページ数 | 4 |
発行日 |