• Lower limb intelligent rehabil...

*Result*: Lower limb intelligent rehabilitation robot based on human-gait coupling, spatiotemporal gait sensing, and fuzzy PID control.

Title:
Lower limb intelligent rehabilitation robot based on human-gait coupling, spatiotemporal gait sensing, and fuzzy PID control.
Authors:
Zhao J; The Faculty of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China.; Engineering Research Center of Integration and Application of Digital Learning Technology, Weigongcun campus of the Open University of China, Beijing, 100081, China., Zou G; The Faculty of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China., Zhao Q; Department of Traditional Chinese Medicine (acupuncture), First Medical Center of the Chinese People's Liberation Army General Hospital, Beijing, China., Bao M; Shandong Guoxing Intelligent Technology Co., Ltd, Yantai, Shandong, China. Terrybao@suprobot.com., Ju X; The Institute of Sports Medicine, Peking University Third Hospital, Beijing, China., Luo Y; Department of Orthopaedics, First Medical Center of the Chinese People's Liberation Army General Hospital, Beijing, China.
Source:
Scientific reports [Sci Rep] 2025 Dec 09; Vol. 16 (1), pp. 1926. Date of Electronic Publication: 2025 Dec 09.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Imprint Name(s):
Original Publication: London : Nature Publishing Group, copyright 2011-
MeSH Terms:
Robotics*/methods , Robotics*/instrumentation , Gait*/physiology , Lower Extremity*/physiology , Lower Extremity*/physiopathology , Exoskeleton Device*, Walking/physiology ; Knee Joint/physiology ; Hip Joint/physiology ; Humans ; Fuzzy Logic ; Biomechanical Phenomena
References:
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PLoS Comput Biol. 2018 Jul 26;14(7):e1006223. (PMID: 30048444)
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Grant Information:
BIA200191 General Project of Education of National Social Science Foundation of China and in part by the Research on Educational Robots and Their Teaching System
Contributed Indexing:
Keywords: Assistive rehabilitation robotics; Film pressure gait sensor; Fuzzy PID; Gait kinematics analysis; Gait simulation; OpenSim
Entry Date(s):
Date Created: 20251209 Date Completed: 20260114 Latest Revision: 20260117
Update Code:
20260130
PubMed Central ID:
PMC12804698
DOI:
10.1038/s41598-025-31657-z
PMID:
41365975
Database:
MEDLINE

*Further Information*

*For individuals with dyskinesia, postoperative walking rehabilitation is crucial, and lower limb exoskeletons provide effective training assistance. This paper proposes a method for designing a lower limb exoskeleton based on sensor feedback and human-robot gait simulation. Firstly, a mathematical model of lower limb motion and an exoskeleton robot model are designed based on hip/knee joint motion and gait mechanisms. Secondly, gait simulation is performed via human-robot coupling, with a comparative analysis of lower limb muscle dynamics during walking. Hip/knee motion data is converted into motion function curves for dynamic simulation verification. Subsequently, a brushless motor drive control system for the lower limb exoskeleton is developed using Simulink, and simulation experiments are conducted for position, speed, and torque control. Finally, patient walking experiments using membrane pressure and pose sensors analyze hip/knee and plantar pressure data, enabling output adjustment feedback and closed-loop torque control of the exoskeleton.
(© 2025. The Author(s).)*

*Declarations. Competing interests: The authors declare no competing interests. Ethical statement: The gait analysis data used in this study were obtained from the Gaitboter system (provided by Beijing Zhongke Huicheng Technology Co., LTD) and PeKing University Third Hospital. All data were fully anonymized prior to analysis, ensuring no identifiable personal information was retained. Since this study did not involve direct interaction with human participants and utilized only pre-existing de-identified data, it does not require ethical approval under applicable regulations (e.g., Declaration of Helsinki or China’s Ethical Guidelines for Biomedical Research). Informed consent: All original data collection procedures involving human participants were conducted in compliance with ethical standards, and written informed consent was obtained from all individuals prior to data acquisition. However, this secondary analysis did not involve new data collection or individual-level identification, thus falling outside the scope of additional ethical review.*