{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T18:42:51Z","timestamp":1792089771889,"version":"4.4.0"},"reference-count":53,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T00:00:00Z","timestamp":1737676800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Province Key R&amp;D Program of Guangxi","award":["AB22035006"],"award-info":[{"award-number":["AB22035006"]}]},{"name":"Province Key R&amp;D Program of Guangxi","award":["102118170090010009004"],"award-info":[{"award-number":["102118170090010009004"]}]},{"name":"Key Laboratory of Intelligent Control and Rehabilitation Technology of the Ministry of Civil Affairs","award":["AB22035006"],"award-info":[{"award-number":["AB22035006"]}]},{"name":"Key Laboratory of Intelligent Control and Rehabilitation Technology of the Ministry of Civil Affairs","award":["102118170090010009004"],"award-info":[{"award-number":["102118170090010009004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study presents a method for the active control of a follow-up lower extremity exoskeleton rehabilitation robot (LEERR) based on human motion intention recognition. Initially, to effectively support body weight and compensate for the vertical movement of the human center of mass, a vision-driven follow-and-track control strategy is proposed. Subsequently, an algorithm for recognizing human motion intentions based on machine learning is proposed for human-robot collaboration tasks. A muscle\u2013machine interface is constructed using a bi-directional long short-term memory (BiLSTM) network, which decodes multichannel surface electromyography (sEMG) signals into flexion and extension angles of the hip and knee joints in the sagittal plane. The hyperparameters of the BiLSTM network are optimized using the quantum-behaved particle swarm optimization (QPSO) algorithm, resulting in a QPSO-BiLSTM hybrid model that enables continuous real-time estimation of human motion intentions. Further, to address the uncertain nonlinear dynamics of the wearer-exoskeleton robot system, a dual radial basis function neural network adaptive sliding mode Controller (DRBFNNASMC) is designed to generate control torques, thereby enabling the precise tracking of motion trajectories generated by the muscle\u2013machine interface. Experimental results indicate that the follow-up-assisted frame can accurately track human motion trajectories. The QPSO-BiLSTM network outperforms traditional BiLSTM and PSO-BiLSTM networks in predicting continuous lower limb motion, while the DRBFNNASMC controller demonstrates superior gait tracking performance compared to the fuzzy compensated adaptive sliding mode control (FCASMC) algorithm and the traditional proportional\u2013integral\u2013derivative (PID) control algorithm.<\/jats:p>","DOI":"10.3390\/s25030713","type":"journal-article","created":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T09:40:39Z","timestamp":1737711639000},"page":"713","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["An Active Control Method for a Lower Limb Rehabilitation Robot with Human Motion Intention Recognition"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-3543-4682","authenticated-orcid":false,"given":"Zhuangqun","family":"Song","sequence":"first","affiliation":[{"name":"College of Mechanical and Marine Engineering, Beibu Gulf University, Qinzhou 535011, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueji","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Mechanical and Marine Engineering, Beibu Gulf University, Qinzhou 535011, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Control and Rehabilitation Technology of the Ministry of Civil Affairs, Beijing 100176, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueshan","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Mechanical and Marine Engineering, Beibu Gulf University, Qinzhou 535011, China"},{"name":"School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/S1474-4422(18)30500-3","article-title":"Stroke in china: Advances and challenges in epidemiology, pre-vention, and management","volume":"18","author":"Wu","year":"2019","journal-title":"Lancet Neurol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/S0140-6736(19)30427-1","article-title":"Mortality, morbidity, and risk factors in China and its provinces, 1990\u20132017: A systematic analysis for the Global Burden of Disease Study 2017","volume":"394","author":"Zhou","year":"2019","journal-title":"Lancet"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.21037\/atm-2020-cass-25","article-title":"Prevention and treatment of strokes associated with carotid artery stenosis: A research priority","volume":"8","author":"Paraskevas","year":"2020","journal-title":"Ann. 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