A Review of Myoelectric Control for Prosthetic Hand Manipulation
Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation. Intuitive and intelligent myoelectric control can help amputees to regain upper limb function. However, current research efforts are primarily focused on developing rich myoelectric classifiers and biomime...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Biomimetics |
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| Online Access: | https://www.mdpi.com/2313-7673/8/3/328 |
| _version_ | 1797590102097002496 |
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| author | Ziming Chen Huasong Min Dong Wang Ziwei Xia Fuchun Sun Bin Fang |
| author_facet | Ziming Chen Huasong Min Dong Wang Ziwei Xia Fuchun Sun Bin Fang |
| author_sort | Ziming Chen |
| collection | DOAJ |
| description | Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation. Intuitive and intelligent myoelectric control can help amputees to regain upper limb function. However, current research efforts are primarily focused on developing rich myoelectric classifiers and biomimetic control methods, limiting prosthetic hand manipulation to simple grasping and releasing tasks, while rarely exploring complex daily tasks. In this article, we conduct a systematic review of recent achievements in two areas, namely, intention recognition research and control strategy research. Specifically, we focus on advanced methods for motion intention types, discrete motion classification, continuous motion estimation, unidirectional control, feedback control, and shared control. In addition, based on the above review, we analyze the challenges and opportunities for research directions of functionality-augmented prosthetic hands and user burden reduction, which can help overcome the limitations of current myoelectric control research and provide development prospects for future research. |
| first_indexed | 2024-03-11T01:15:39Z |
| format | Article |
| id | doaj.art-6f2a2f799b644ba994ec6e0aab09bffa |
| institution | Directory Open Access Journal |
| issn | 2313-7673 |
| language | English |
| last_indexed | 2024-03-11T01:15:39Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomimetics |
| spelling | doaj.art-6f2a2f799b644ba994ec6e0aab09bffa2023-11-18T18:30:12ZengMDPI AGBiomimetics2313-76732023-07-018332810.3390/biomimetics8030328A Review of Myoelectric Control for Prosthetic Hand ManipulationZiming Chen0Huasong Min1Dong Wang2Ziwei Xia3Fuchun Sun4Bin Fang5Laboratory for Embedded System and Intelligent Robot, Wuhan University of Science and Technology, Wuhan 430081, ChinaLaboratory for Embedded System and Intelligent Robot, Wuhan University of Science and Technology, Wuhan 430081, ChinaInstitute for Artificial Intelligence, State Key Lab of Intelligent Technology and Systems, Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, ChinaSchool of Engineering and Technology, China University of Geosciences, Beijing 100083, ChinaInstitute for Artificial Intelligence, State Key Lab of Intelligent Technology and Systems, Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, ChinaInstitute for Artificial Intelligence, State Key Lab of Intelligent Technology and Systems, Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, ChinaMyoelectric control for prosthetic hands is an important topic in the field of rehabilitation. Intuitive and intelligent myoelectric control can help amputees to regain upper limb function. However, current research efforts are primarily focused on developing rich myoelectric classifiers and biomimetic control methods, limiting prosthetic hand manipulation to simple grasping and releasing tasks, while rarely exploring complex daily tasks. In this article, we conduct a systematic review of recent achievements in two areas, namely, intention recognition research and control strategy research. Specifically, we focus on advanced methods for motion intention types, discrete motion classification, continuous motion estimation, unidirectional control, feedback control, and shared control. In addition, based on the above review, we analyze the challenges and opportunities for research directions of functionality-augmented prosthetic hands and user burden reduction, which can help overcome the limitations of current myoelectric control research and provide development prospects for future research.https://www.mdpi.com/2313-7673/8/3/328myoelectric controlintention recognitioncontrol strategyfunctionality-augmented prosthetic handsuser burden reduction |
| spellingShingle | Ziming Chen Huasong Min Dong Wang Ziwei Xia Fuchun Sun Bin Fang A Review of Myoelectric Control for Prosthetic Hand Manipulation Biomimetics myoelectric control intention recognition control strategy functionality-augmented prosthetic hands user burden reduction |
| title | A Review of Myoelectric Control for Prosthetic Hand Manipulation |
| title_full | A Review of Myoelectric Control for Prosthetic Hand Manipulation |
| title_fullStr | A Review of Myoelectric Control for Prosthetic Hand Manipulation |
| title_full_unstemmed | A Review of Myoelectric Control for Prosthetic Hand Manipulation |
| title_short | A Review of Myoelectric Control for Prosthetic Hand Manipulation |
| title_sort | review of myoelectric control for prosthetic hand manipulation |
| topic | myoelectric control intention recognition control strategy functionality-augmented prosthetic hands user burden reduction |
| url | https://www.mdpi.com/2313-7673/8/3/328 |
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