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Article: Robotic Leg Prosthesis: A Survey From Dynamic Model to Adaptive Control for Gait Coordination

TitleRobotic Leg Prosthesis: A Survey From Dynamic Model to Adaptive Control for Gait Coordination
Authors
Keywordsadaptive control
gait coordination
prosthesis-human system
Robotic leg prosthesis
stochastic system
Issue Date2024
Citation
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2024, v. 32, p. 607-624 How to Cite?
AbstractGait coordination (GC), meaning that one leg moves in the same pattern but with a specific phase lag to the other, is a spontaneous behavior in the walking of a healthy person. It is also crucial for unilateral amputees with the robotic leg prosthesis to perform ambulation cooperatively in the real world. However, achieving the GC for amputees poses significant challenges to the prostheses' dynamic modeling and control design. Still, there has not been a clear survey on the initiation and evolution of the detailed solutions, hindering the precise decision of future explorations. To this end, this paper comprehensively reviews GC-oriented dynamic modeling and adaptive control methods for robotic leg prostheses. Considering the two representative environments concerned with adaptive control, we first classify the dynamic models into the deterministic model for structured terrain and the constrained stochastic model for stochastically uneven terrain. Inspired by the concept of synchronization, we then emphasize three typical problems for the GC realization, i.e., complete coordination on structured terrain, stochastic coordination on stochastically uneven terrain, and finite-time delayed stochastic coordination. Finally, we conclude with a discussion on the remaining challenges and opportunities in controlling robotic leg prostheses.
Persistent Identifierhttp://hdl.handle.net/10722/365300
ISSN
2023 Impact Factor: 4.8
2023 SCImago Journal Rankings: 1.315

 

DC FieldValueLanguage
dc.contributor.authorMa, Xin-
dc.contributor.authorZhang, Xiaoxu-
dc.contributor.authorXu, Jian-
dc.date.accessioned2025-11-04T07:10:12Z-
dc.date.available2025-11-04T07:10:12Z-
dc.date.issued2024-
dc.identifier.citationIEEE Transactions on Neural Systems and Rehabilitation Engineering, 2024, v. 32, p. 607-624-
dc.identifier.issn1534-4320-
dc.identifier.urihttp://hdl.handle.net/10722/365300-
dc.description.abstractGait coordination (GC), meaning that one leg moves in the same pattern but with a specific phase lag to the other, is a spontaneous behavior in the walking of a healthy person. It is also crucial for unilateral amputees with the robotic leg prosthesis to perform ambulation cooperatively in the real world. However, achieving the GC for amputees poses significant challenges to the prostheses' dynamic modeling and control design. Still, there has not been a clear survey on the initiation and evolution of the detailed solutions, hindering the precise decision of future explorations. To this end, this paper comprehensively reviews GC-oriented dynamic modeling and adaptive control methods for robotic leg prostheses. Considering the two representative environments concerned with adaptive control, we first classify the dynamic models into the deterministic model for structured terrain and the constrained stochastic model for stochastically uneven terrain. Inspired by the concept of synchronization, we then emphasize three typical problems for the GC realization, i.e., complete coordination on structured terrain, stochastic coordination on stochastically uneven terrain, and finite-time delayed stochastic coordination. Finally, we conclude with a discussion on the remaining challenges and opportunities in controlling robotic leg prostheses.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Neural Systems and Rehabilitation Engineering-
dc.subjectadaptive control-
dc.subjectgait coordination-
dc.subjectprosthesis-human system-
dc.subjectRobotic leg prosthesis-
dc.subjectstochastic system-
dc.titleRobotic Leg Prosthesis: A Survey From Dynamic Model to Adaptive Control for Gait Coordination-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TNSRE.2024.3356561-
dc.identifier.pmid38252575-
dc.identifier.scopuseid_2-s2.0-85183607191-
dc.identifier.volume32-
dc.identifier.spage607-
dc.identifier.epage624-
dc.identifier.eissn1558-0210-

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