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May 29, 2026BioengineeringOpen Access

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

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Authors

CLChang LiuUniversity of Science and Technology of ChinaXWXiaoyan WangLomonosov Moscow State UniversityMOMostafa OrbanChinese Academy of Sciences

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Implication

Review highlights advances in multimodal information fusion for enhancing rehabilitation in motor dysfunction, suggesting implications for device optimization.

Key Points

  • This review explores multimodal information fusion control techniques in assistive devices aimed at improving rehabilitation for motor dysfunction.
  • Reviewed recent literature on multimodal information fusion in rehabilitation robots.
  • Analyzed advantages and disadvantages of various fusion levels: data-level, feature-level, and decision-level.
  • Evaluated commonly used fusion algorithms in the context of rehabilitation equipment design.
  • Presented insights into how information fusion enhances rehabilitation efficacy and specificity.
  • Identified key challenges and benefits associated with different levels of data fusion.
  • Provided a comprehensive overview of the current state of research in assistive devices for motor dysfunction.

Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/6a192d4afab5b468c441613dhttps://doi.org/10.3390/bioengineering13060627
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