Mostafa Orban
Lecturer
Multimodal Information Fusion for Control of Rehabilitation Robots in Motor Dysfunction: A Review
Bioengineering • 2026
Publication Information
Authors
Liu, Chang, Xiaoyan Wang, Mostafa Orban, Alexander Vartanov, Mahmoud Elsamanty, Tingrui Pan, and Kai Guo
Keywords
information fusion; rehabilitation robotics; motor dysfunction; data-level fusion; feature-level fusion; decision-level fusion
Journal
Bioengineering
Publisher
MDPI
Volume
Not Available
Issue
Not Available
Pages
Not Available
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
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.
