Affiliations: [a] Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| [b] Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
| [c] Key Laboratory of Neural-functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai, China
| [d] Department of Orthopaedics, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China
Correspondence:
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Address for correspondence: Hongliu Yu, Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, No. 516, Jungong Road, Yangpu District, Shanghai, China. Tel.: +86 13162655096; E-mail: [email protected].
Abstract: BACKGROUND:As an emerging exoskeleton robot technology, flexible lower limb exoskeleton (FLLE) integrates flexible drive and wearable mechanism, effectively solving many problems of traditional rigid lower limb exoskeleton (RLLE) such as higher quality, poorer compliance and relatively poor portability, and has become one of the important development directions in the field of active rehabilitation. OBJECTIVE:This review focused on the development and innovation process in the field of FLLE in the past decade. METHOD:Related literature published from 2010 to 2021 were searched in EI, IEEE Xplore, PubMed and Web of Science databases. Seventy target research articles were further screened and sorted through inclusion and exclusion criteria. RESULTS:FLLE is classified according to different driving modes, and the advantages and disadvantages of passive flexible lower limb exoskeletons and active flexible lower limb exoskeletons are comprehensively summarized. CONCLUSION:At present, FLLE’s research is mainly based on cable drive, bionic pneumatic muscles followed and matured, and new exoskeleton designs based on smart material innovations also trend to diversify. In the future, the development direction of FLLE will be lightweight and drive compliance, and the multi-mode sensory feedback control theory, motion intention recognition theory and human-machine interaction theory will be combined to reduce the metabolic energy consumption of walking.
