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Execution and perception of upper limb exoskeleton for stroke patients: a systematic review

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Abstract

Due to the lack of therapists and the demand for objective rehabilitation training indicators, the upper limb rehabilitation exoskeleton (ULR-EXO) has attracted more and more concentration. Execution and perception are the two most important technologies of ULR-EXO. A unified analysis of their essential anatomical characteristics and rehabilitation training needs will help to understand the future development trend of the ULR-EXO. According to the anatomical and kinematic features of the upper limb, combined with human-robot compatibility, this paper introduces the structural design of the ULR-EXO, the classification of execution, and the existing problems, summarizes the status quo of perceptual information, and classifies signal sources according to the signals generated by stroke patients in human-robot interaction. This paper also briefly summarizes the control methods of the ULR-EXO in different rehabilitation stages. Finally, based on the two stages of hospital treatment and family rehabilitation, the design requirements of the ULR-EXO and the selection of sensors based on different mechanism forms are discussed, which provides some reference values for researchers in this field.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

SMA:

Shape memory alloy

EAP:

Electroactive polymer

EEG:

Electroencephalogram

ECG:

Electrocardiogram

EMG:

Electromyography

sEMG:

Surface electromyography

EOG:

Electrooculogram

IMU:

Inertial measurement units

BMS:

Brunnstrom motor stage

HRIF:

Human-robot interaction force

PAM:

Pneumatic artificial muscles

sEMG:

Surface electromyograph

BCI:

Brain-computer interface

SSVEPs:

Steady-state visual evoked potentials

MI:

Motor imaging

FMG:

Force myography

MMG:

Mechanical myography

PID:

Proportion Integration Differentiation

ICR:

Instantaneous centers of rotation

GSR:

Galvanic skin response

UL-EXO:

Upper limb exoskeleton

VR:

Virtual reality

FFA:

Flexible fluidic actuators

FSR:

Force-sensitive resistor

R-EXO:

Rigid exoskeleton

F-EXO:

Flexible exoskeleton

OT:

Occupational therapy

HRI:

Human-robot interaction

MC:

Muscle-tendon complex

DOF:

Degrees of freedom

ET-ULRR:

End-type upper limb rehabilitation robot

SMP:

Skinned multi-person

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Acknowledgments

We thank Mr. Zhaoqi Guo, Mr. Bowen Zheng and Mr. Shuoyu Li for their valuable comments in this manuscript and provide some professional knowledge.

Funding

This work was supported in part by the National Natural Science Foundation of China (Grant No. 52075177), the National Key Research and Development Program of China (Grant Nos. 2021YFB3301400), Research Foundation of Guangdong Province (Grant Nos. 2019A050505001 and 2018KZDXM002), Guangzhou Research Foundation (Grant Nos. 202002030324 and 201903010028), Zhongshan Research Foundation (Grant Nos.2020B2020 and 2021B2022).

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Authors and Affiliations

  1. Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, 510640, China

    Pengpeng Xu, Juncheng Li & Longhan Xie

  2. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, 510640, China

    Dan Xia

  3. Department of Rehabilitation Medicine, Maoming people’s Hospital, Maoming, 525000, China

    Jiaming Zhou

  4. Zhongshan Institute of Modern Industrial Technology, South China University of Technology, Zhongshan, 528400, China

    Longhan Xie

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PX mainly summarizes the current key issues in the development of upper extremity exoskeleton system for patients with hemiplegia, put forward the future development trends and hot spots, and drafted the manuscript. DX, JL, JZ, LX assisted in graph analysis and revised the manuscript. All the authors read and approved the final manuscript.

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Correspondence to Longhan Xie.

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Xu, P., Xia, D., Li, J. et al. Execution and perception of upper limb exoskeleton for stroke patients: a systematic review. Intel Serv Robotics 15, 557–578 (2022). https://doi.org/10.1007/s11370-022-00435-5

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