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

Read full text
Authors: Chang Liu, Xiaoyan Wang, Mostafa Orban, Alexander R. Vartanov, Mahmoud Elsamanty, Tingrui Pan, Kai Guo
Cited by: 1
References: 135

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.

Fields of Study & Subjects

Stroke Rehabilitation and Recovery Gaze Tracking and Assistive Technology Muscle activation and electromyography studies

Publication details

Journal / source
Bioengineering
Publisher
MDPI AG
Volume
13
Issue
6
Pages
627–627
Publication date
27 May 2026
Language
EN