| Item type |
デフォルトアイテムタイプ_（フル）(1) |
| 公開日 |
2023-03-18 |
| タイトル |
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|
タイトル |
A myoelectric prosthetic hand with muscle synergy–based motion determination and impedance model–based biomimetic control |
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言語 |
en |
| 作成者 |
Furui, Akira
Eto, Shintaro
Nakagaki, Kosuke
Shimada, Kyohei
Nakamura, Go
Masuda, Akito
Chin, Takaaki
Tsuji, Toshio
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| アクセス権 |
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|
アクセス権 |
open access |
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アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 権利情報 |
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|
権利情報 |
Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. |
| 権利情報 |
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|
権利情報 |
This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science Robotics on Vol. 4, Issue 31, 26 Jun 2019, DOI: 10.1126/scirobotics.aaw6339. |
| 権利情報 |
|
|
権利情報 |
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認、ご利用ください。 |
| 内容記述 |
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内容記述 |
Prosthetic hands are prescribed to patients who have suffered an amputation of the upper limb due to an accident or a disease. This is done to allow patients to regain functionality of their lost hands. Myoelectric prosthetic hands were found to have the possibility of implementing intuitive controls based on operator’s electromyogram (EMG) signals. These controls have been extensively studied and developed. In recent years, development costs and maintainability of prosthetic hands have been improved through three-dimensional (3D) printing technology. However, no previous studies have realized the advantages of EMG-based classification of multiple finger movements in conjunction with the introduction of advanced control mechanisms based on human motion. This paper proposes a 3D-printed myoelectric prosthetic hand and an accompanying control system. The muscle synergy–based motion-determination method and biomimetic impedance control are introduced in the proposed system, enabling the classification of unlearned combined motions and smooth and intuitive finger movements of the prosthetic hand. We evaluate the proposed system through operational experiments performed on six healthy participants and an upper-limb amputee participant. The experimental results demonstrate that our prosthetic hand system can successfully classify both learned single motions and unlearned combined motions from EMG signals with a high degree of accuracy. Furthermore, applications to real-world uses of prosthetic hands are demonstrated through control tasks conducted by the amputee participant. |
|
言語 |
en |
| 内容記述 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
This work was partially supported by JSPS KAKENHI Grants-in-Aid for Scientific Research C Number 26462242. |
| 出版者 |
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|
出版者 |
American Association for the Advancement of Science |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
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|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
AO |
|
出版タイプResource |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
| 関連情報 |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
10.1126/scirobotics.aaw6339 |
| 関連情報 |
|
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1126/scirobotics.aaw6339 |
| 収録物識別子 |
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収録物識別子タイプ |
ISSN |
|
収録物識別子 |
2470-9476 |
| 開始ページ |
|
|
開始ページ |
eaaw6339 |
| 書誌情報 |
Science Robotics
Science Robotics
巻 4,
号 31,
p. eaaw6339,
発行日 2019-06-26
|
| 旧ID |
48207 |
ScienceRobotics_4_eaaw6339_acceptedver.pdf (9.6 MB)
