{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T23:50:40Z","timestamp":1790639440779,"version":"4.1.0"},"reference-count":38,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:00:00Z","timestamp":1741219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"2024 Guangxi Universities Enhancement of Research Capability for Young and Middle-aged Teachers Project","award":["2024KY0447"],"award-info":[{"award-number":["2024KY0447"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Population aging is an inevitable trend in contemporary society, and the application of technologies such as human\u2013machine interaction, assistive healthcare, and robotics in daily service sectors continues to increase. The lower limb exoskeleton rehabilitation robot has great potential in areas such as enhancing human physical functions, rehabilitation training, and assisting the elderly and disabled. This paper integrates the structural characteristics of the human lower limb, motion mechanics, and gait features to design a biomimetic exoskeleton structure and proposes a human\u2013machine integrated lower limb exoskeleton rehabilitation robot. Human gait data are collected using the Optitrack optical 3D motion capture system. SolidWorks 3D modeling software Version 2021 is used to create a virtual prototype of the exoskeleton, and kinematic analysis is performed using the standard Denavit\u2013Hartenberg (D-H) parameter method. Kinematic simulations are carried out using the Matlab Robotic Toolbox Version R2018a with the derived D-H parameters. A physical prototype was fabricated and tested to verify the validity of the structural design and gait parameters. A controller based on BP fuzzy neural network PID control is designed to ensure the stability of human walking. By comparing two sets of simulation results, it is shown that the BP fuzzy neural network PID control outperforms the other two control methods in terms of overshoot and settling time. The specific conclusions are as follows: after multiple walking gait tests, the robot\u2019s walking process proved to be relatively safe and stable; when using BP fuzzy neural network PID control, there is no significant oscillation, with an overshoot of 5.5% and a settling time of 0.49 s, but the speed was slow, with a walking speed of approximately 0.18 m\/s, a stride length of about 32 cm, and a gait cycle duration of approximately 1.8 s. The model proposed in this paper can effectively assist patients in recovering their ability to walk. However, the lower limb exoskeleton rehabilitation robot still faces challenges, such as a slow speed, large size, and heavy weight, which need to be optimized and improved in future research.<\/jats:p>","DOI":"10.3390\/s25051611","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T04:55:08Z","timestamp":1741236908000},"page":"1611","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Mechanical Structure Design and Motion Simulation Analysis of a Lower Limb Exoskeleton Rehabilitation Robot Based on Human\u2013Machine Integration"],"prefix":"10.3390","volume":"25","author":[{"given":"Chenglong","family":"Zhao","sequence":"first","affiliation":[{"name":"Guangxi Key Laboratory of Ocean Engineering Equipment and Technology, Beibu Gulf University, Qinzhou 535011, China"},{"name":"Department of Integrated Systems Engineering, Nagasaki Institute of Applied Science, Nagasaki 851-0193, Japan"},{"name":"Advanced Science and Technology Research Institute, Beibu Gulf University, Qinzhou 535001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Integrated Systems Engineering, Nagasaki Institute of Applied Science, Nagasaki 851-0193, Japan"},{"name":"School of Rehabilitation Medieine, Wenzhou Medical University, Wenzhou 325035, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuefa","family":"Ou","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory of Ocean Engineering Equipment and Technology, Beibu Gulf University, Qinzhou 535011, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liucun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Advanced Science and Technology Research Institute, Beibu Gulf University, Qinzhou 535001, China"},{"name":"School of Computer, Shandong Xiehe University, Jinan 250109, China"},{"name":"Institute of Informatics, Kanagawa University, Yokohama 221-8686, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1007\/s42235-022-00289-8","article-title":"Systematic review on wearable lower extremity robotic exoskeletons for assisted locomotion","volume":"20","author":"Qiu","year":"2023","journal-title":"J. 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