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Brain-machine interface to control a prosthetic arm with monkey ECoGs during periodic movements
http://hdl.handle.net/10131/9039
http://hdl.handle.net/10131/9039d169a164-4508-4d44-8766-09f714bd273a
名前 / ファイル | ライセンス | アクション |
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fnins-08-00417.pdf (2.2 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2015-03-03 | |||||
タイトル | ||||||
タイトル | Brain-machine interface to control a prosthetic arm with monkey ECoGs during periodic movements | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題 | brain-machine interfaces, electrocorticography, electromyography, prosthetic arm, reaching task | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Morishita, Soichiro
× Morishita, Soichiro× Sato, Keita× Watanabe, Hidenori× Nishimura, Yukio× Isa, Tadashi× Kato, Ryu× Nakamura, Tatsuhiro× Yokoi, Hiroshi |
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著者(ヨミ) | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19261 | |||||
姓名 | モリシタ, ソウイチロウ | |||||
著者(ヨミ) | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19262 | |||||
姓名 | サトウ, ケイタ | |||||
著者(ヨミ) | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19263 | |||||
姓名 | ワタナベ, ヒデノリ | |||||
著者(ヨミ) | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19264 | |||||
姓名 | ニシムラ, ユキオ | |||||
著者(ヨミ) | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19265 | |||||
姓名 | イサ, タダシ | |||||
著者(ヨミ) | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19266 | |||||
姓名 | カトウ, リュウ | |||||
著者(ヨミ) | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19267 | |||||
姓名 | ナカムラ, タツヒロ | |||||
著者(ヨミ) | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19268 | |||||
姓名 | ヨコイ, ヒロシ | |||||
著者別名 | ||||||
識別子Scheme | WEKO | |||||
識別子 | 19269 | |||||
姓名 | 加藤, 龍 | |||||
著者所属 | ||||||
Brain Science Inspired Life Support Research Center, The University of Electro-Communications | ||||||
著者所属 | ||||||
Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications | ||||||
著者所属 | ||||||
Division of Behavioral Development, Department of Developmental Physiology, National Institute for Physiological Sciences | ||||||
著者所属 | ||||||
Division of Behavioral Development, Department of Developmental Physiology, National Institute for Physiological Sciences / Department of Physiological Sciences, School of Life Science, The Graduate University for Advanced Studies (SOKENDAI) / PRESTO, Japan Science and Technology Agency | ||||||
著者所属 | ||||||
Division of Behavioral Development, Department of Developmental Physiology, National Institute for Physiological Sciences / Department of Physiological Sciences, School of Life Science, The Graduate University for Advanced Studies (SOKENDAI) | ||||||
著者所属 | ||||||
Division of Systems Research, Department of Systems Design, Faculty of Engineering, The Yokohama National University | ||||||
著者所属 | ||||||
Integrative Brain Imaging Center, National Center of Neurology and Psychiatry | ||||||
著者所属 | ||||||
Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications | ||||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Brain?machine interfaces (BMIs) are promising technologies for rehabilitation of upperlimb functions in patients with severe paralysis. We previously developed a BMI prostheticarm for a monkey implanted with electrocorticography (ECoG) electrodes, and trainedit in a reaching task. The stability of the BMI prevented incorrect movements due tomisclassification of ECoG patterns. As a trade-off for the stability, however, the latency(the time gap between the monkey’s actual motion and the prosthetic arm movement)was about 200ms. Therefore, in this study, we aimed to improve the response time ofthe BMI prosthetic arm. We focused on the generation of a trigger event by decodingmuscle activity in order to predict integrated electromyograms (iEMGs) from the ECoGs.We verified the achievability of our method by conducting a performance test of theproposed method with actual achieved iEMGs instead of predicted iEMGs. Our resultsconfirmed that the proposed method with predicted iEMGs eliminated the time delay. Inaddition, we found that motor intention is better reflected by muscle activity estimatedfrom brain activity rather than actual muscle activity. Therefore, we propose that usingpredicted iEMGs to guide prosthetic arm movement results in minimal delay and excellentperformance. | |||||
書誌情報 |
Frontiers in Neuroscience 巻 8, 号 417, p. 1-9, 発行日 2014-12-12 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1662-4548 | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 |