{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T06:43:35Z","timestamp":1740120215327,"version":"3.37.3"},"reference-count":28,"publisher":"World Scientific Pub Co Pte Ltd","issue":"10","funder":[{"DOI":"10.13039\/501100002948","name":"Hubei University of Technology","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100002948","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2017,10]]},"abstract":"<jats:p>Nerve injury can cause lower limb paralysis and gait disorder. Currently lower limb rehabilitation exoskeleton robots used in the hospitals need more power to correct abnormal motor patterns of stroke patients\u2019 legs. These gait rehabilitation robots are powered by cumbersome and bulky electric motors, which provides a poor user experience. A newly developed gait rehabilitation exoskeleton robot actuated by low-cost and lightweight pneumatic artificial muscles (PAMs) is presented in this research. A model-free proxy-based sliding mode control (PSMC) strategy and a model-based chattering mitigation robust variable control (CRVC) strategy were developed and first applied in rehabilitation trainings, respectively. As the dynamic response of PAM due to the compressed air is low, an innovative intention identification control strategy was taken in active trainings by the use of the subject\u2019s intention indirectly through the estimation of the interaction force between the subject\u2019s leg and the exoskeleton. The proposed intention identification strategy was verified by treadmill-based gait training experiments.<\/jats:p>","DOI":"10.1142\/s0218001417590212","type":"journal-article","created":{"date-parts":[[2017,3,10]],"date-time":"2017-03-10T04:26:49Z","timestamp":1489120009000},"page":"1759021","source":"Crossref","is-referenced-by-count":5,"title":["Passive and Active Control Strategies of a Leg Rehabilitation Exoskeleton Powered by Pneumatic Artificial Muscles"],"prefix":"10.1142","volume":"31","author":[{"given":"Chen","family":"Su","sequence":"first","affiliation":[{"name":"School of Industrial Design, Hubei University of Technology, Wuhan 430068, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ao","family":"Chai","sequence":"additional","affiliation":[{"name":"School of Industrial Design, Hubei University of Technology, Wuhan 430068, P. R. 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