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

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

Abstract readReview

In one paragraph

Review in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Linking Embodiment, Simulator Sickness, and EEG Activity During XR-BCI Use: A Single-Participant Case Study.Life (Basel, Switzerland) · 2026
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Chang LiuSchool of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230022, China.ORCID 0009-0006-5864-2550

Xiaoyan WangFaculty of Psychology, Lomonosov Moscow State University, Moscow 125009, Russia.ORCID 0009-0000-2985-9829

Mostafa OrbanSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.ORCID 0000-0002-8414-1171

Alexander VartanovFaculty of Psychology, Lomonosov Moscow State University, Moscow 125009, Russia.ORCID 0000-0001-8844-9643

Mahmoud ElsamantyMechanical Department, Faculty of Engineering at Shoubra, Benha University, Cairo 11629, Egypt.

Tingrui PanSuzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou 215123, China.ORCID 0000-0002-8851-0667

Kai GuoSchool of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230022, China.ORCID 0000-0003-2071-6869

Funding

Chinese Academy of Sciences International Talent Plan (PIFI) Project 2024VBB0010Jilin Province Science and Technology Department 20240305049YYNatural Science Foundation of Chongqing 2024NSCQ-MSX0007Natural Science Foundation Project of Shandong Province ZR2022QH214pilot projects for fundamental research in Suzhou SSD2023014State Administration of Foreign Experts Affairs H20240225Suzhou Institute of Biomedical Engineering and Technology, CAS

6 · The paper itself

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.

Indexed as

data-level fusiondecision-level fusionfeature-level fusioninformation fusionmotor dysfunctionrehabilitation robotics

Identifiers

PMID42351872

DOI10.3390/bioengineering13060627

PMCPMC13295490

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.