{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T08:30:10Z","timestamp":1763454610020,"version":"3.45.0"},"reference-count":60,"publisher":"Cambridge University Press (CUP)","issue":"10","license":[{"start":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:00:00Z","timestamp":1758672000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotica"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Human\u2013machine compatibility and collaborative control for stroke patients utilizing lower limb rehabilitation robots have attracted considerable research attention. As a highly human\u2013machine-coupled system, ensuring adequate compliance and safety is fundamental to efficient and comfortable rehabilitation. Therefore, this paper first quantifies human\u2013machine contact interactions, proposes a human\u2013machine coupling dynamics modeling method, and identifies the robot\u2019s dynamic inertia parameters and human lower limb parameters. Second, a dual closed-loop controller for the rehabilitation robot is designed. Based on the bottom position control, an adaptive admittance control algorithm is proposed that employs the root-mean-square propagation (RMSprop) algorithm to tune the adaptive gain. In rehabilitation training, the controller can adaptively adjust the admittance parameters according to the human\u2013machine interaction force to achieve responsiveness to the dynamic changes of the human\u2013machine system. The experimental results of the control system show that the human\u2013machine cooperative control performance is significantly improved, the maximum joint angle error is reduced by more than 40.9%, and the maximum human\u2013machine interaction force is reduced by more than 19.4%.<\/jats:p>","DOI":"10.1017\/s0263574725102300","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T06:42:20Z","timestamp":1758696140000},"page":"3419-3441","source":"Crossref","is-referenced-by-count":0,"title":["Human\u2013machine coupling dynamics modeling and adaptive admittance control of lower limb rehabilitation robot"],"prefix":"10.1017","volume":"43","author":[{"given":"Chao","family":"Gao","sequence":"first","affiliation":[{"name":"Hebei University of Technology"}]},{"given":"Chang","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology Beijing"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5673-3301","authenticated-orcid":false,"given":"Hui","family":"Li","sequence":"additional","affiliation":[{"name":"University of Science and Technology Beijing"}]},{"given":"Jianhua","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Science and Technology Beijing"}]},{"given":"Xinpeng","family":"Du","sequence":"additional","affiliation":[{"name":"Hebei University of Technology"}]},{"given":"Jianjun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hebei University of Technology"}]}],"member":"56","published-online":{"date-parts":[[2025,9,24]]},"reference":[{"key":"S0263574725102300_ref39","doi-asserted-by":"crossref","unstructured":"[39] Maita, D. and Venture, G. . \u201cInfluence of the Model\u2019s Degree of Freedom on Human Body Dynamics Identification,\u201d In: Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2013) pp. 4609\u20134612.","DOI":"10.1109\/EMBC.2013.6610574"},{"key":"S0263574725102300_ref23","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574724000304"},{"key":"S0263574725102300_ref32","doi-asserted-by":"publisher","DOI":"10.1080\/09540098908915650"},{"key":"S0263574725102300_ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinbiomech.2009.10.010"},{"key":"S0263574725102300_ref2","first-page":"33","article-title":"China stroke surveillance report 2021","volume":"10","author":"Tu","year":"2023","journal-title":"Mil. 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