Multimodal Information Fusion for Control of Rehabilitation Robots in Motor Dysfunction: A Review

This paper reviews recent advances in assistive devices based on multimodal information fusion control, designed for individuals with motor dysfunction. The prevalence of motor dysfunction is increasingly concerning amidst global population aging. Information fusion technology, widely adopted in rehabilitation, enhances the efficacy and specificity of rehabilitation treatments. This paper introduces the concept of multimodal information fusion control into rehabilitation equipment design. It highlights the advantages and disadvantages of data-level, feature-level, and decision-level fusion, along with commonly employed fusion algorithms. By summarizing and analyzing the current state of research, this paper aims to provide a valuable reference for the further development and optimization of assistive devices for motor dysfunction.

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Publication Details

Journal
Bioengineering
Published
2026-05-27
DOI
https://doi.org/10.3390/bioengineering13060627
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
0.00

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article

Multimodal Information Fusion for Control of Rehabilitation Robots in Motor Dysfunction: A Review

Mostafa Orban, Tingrui Pan, Chang Liu, Mahmoud Elsamanty et al.
Bioengineering
Stroke Rehabilitation and Recovery
article

Multimodal Information Fusion for Control of Rehabilitation Robots in Motor Dysfunction: A Review

Mostafa Orban, Tingrui Pan, Chang Liu, Mahmoud Elsamanty, Alexander Vartanov, Kai Guo, Xiaoyan Wang
article en

Abstract

This paper reviews recent advances in assistive devices based on multimodal information fusion control, designed for individuals with motor dysfunction. The prevalence of motor dysfunction is increasingly concerning amidst global population aging. Information fusion technology, widely adopted in rehabilitation, enhances the efficacy and specificity of rehabilitation treatments. This paper introduces the concept of multimodal information fusion control into rehabilitation equipment design. It highlights the advantages and disadvantages of data-level, feature-level, and decision-level fusion, along with commonly employed fusion algorithms. By summarizing and analyzing the current state of research, this paper aims to provide a valuable reference for the further development and optimization of assistive devices for motor dysfunction.

BioengineeringVol. 13(6)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Lomonosov Moscow State University (RU), Benha University (EG), Suzhou University of Science and Technology (CN), Suzhou Institute of Biomedical Engineering and Technology (CN), Tsinghua–Berkeley Shenzhen Institute (CN), Chongqing Emergency Medical Center (CN), Tsinghua University (CN)
State Administration of Foreign Experts Affairs, Natural Science Foundation of Chongqing, Department of Science and Technology of Jilin Province
Openalex Percentile: Top 8%
Stroke Rehabilitation and Recovery
DOIOpen Access PDFOpenAlex
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