Research on Human-Machine Interaction Control Technology for Lower Limb Exoskeleton Rehabilitation Robots

In response to the health assurance challenges faced by the elderly population in Chinas aging society and to mitigate the shortage of medical resources while improving the rehabilitation rate of patients with central nervous system injuries, research on lower limb exoskeleton rehabilitation robots has been widely conducted. Since the 1960s, countries such as Switzerland, the United States, the Netherlands, Germany, Japan, and China have successively developed relatively mature standing and recumbent lower limb exoskeleton systems. This paper builds the kinematic and dynamic models of a lower limb exoskeleton rehabilitation robot based on a two-link mechanism, laying the theoretical foundation and implementation approach for processing position, velocity, and torque sensor signals in human-machine interaction control. Based on domestic and international progress as well as kinematic and dynamic analysis, four types of human-machine interaction control technologiestrajectory tracking control, force-position hybrid control, impedance control, and bioelectrical signal controlare thoroughly analyzed, providing a technical framework for engineering implementation. In the future, lower limb exoskeleton rehabilitation robots will integrate lightweight materials and structural design, intelligent adaptive algorithms, and environmental perception technologies, utilizing low-cost open-source platforms to optimize human-machine interaction control technology for more efficient, safe, and personalized rehabilitation training

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Publication Details

Journal
Applied and Computational Engineering
Published
2025-01-10
DOI
https://doi.org/10.54254/2755-2721/2025.20102
Citations
1
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
1.03
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article

Research on Human-Machine Interaction Control Technology for Lower Limb Exoskeleton Rehabilitation Robots

Chengxu Yuan
1 citations
Applied and Computational Engineering
Stroke Rehabilitation and Recovery
1.03
article

Research on Human-Machine Interaction Control Technology for Lower Limb Exoskeleton Rehabilitation Robots

Chengxu Yuan
article en
1 citations

Abstract

In response to the health assurance challenges faced by the elderly population in Chinas aging society and to mitigate the shortage of medical resources while improving the rehabilitation rate of patients with central nervous system injuries, research on lower limb exoskeleton rehabilitation robots has been widely conducted. Since the 1960s, countries such as Switzerland, the United States, the Netherlands, Germany, Japan, and China have successively developed relatively mature standing and recumbent lower limb exoskeleton systems. This paper builds the kinematic and dynamic models of a lower limb exoskeleton rehabilitation robot based on a two-link mechanism, laying the theoretical foundation and implementation approach for processing position, velocity, and torque sensor signals in human-machine interaction control. Based on domestic and international progress as well as kinematic and dynamic analysis, four types of human-machine interaction control technologiestrajectory tracking control, force-position hybrid control, impedance control, and bioelectrical signal controlare thoroughly analyzed, providing a technical framework for engineering implementation. In the future, lower limb exoskeleton rehabilitation robots will integrate lightweight materials and structural design, intelligent adaptive algorithms, and environmental perception technologies, utilizing low-cost open-source platforms to optimize human-machine interaction control technology for more efficient, safe, and personalized rehabilitation training

Applied and Computational EngineeringVol. 125(1)
Central South University (CN)
Partnerships for the goals
Openalex Percentile: Top 26%
Stroke Rehabilitation and Recovery
1.03
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Research on Human-Machine Interaction Control Technology for Lower Limb Exoskeleton Rehabilitation Robots — Chengxu Yuan · Applied and Computational Engineering (2025) | TGRS Research Map | TGRS