Hybrid upper limb rehabilitation system to stimulate neural plasticity through augmented illusion training

Abstract

Physical rehabilitation is the process of training to recover or improve lost motor functions due to neurological deficits. In recent years, various upper limb rehabilitation paradigms have been proposed to provide relearning of motor skills through motor rehabilitation training. However, several aspects, including cost, motivation, real-time biofeedback enhancements, and effective stimulation of neural plasticity, remain major issues. In this paper, a new hybrid upper limb rehabilitation system named the Augmented Reality-based Illusion System (ARIS) is developed to solve the aforementioned issues. The system enhances the user’s motivation via augmented reality (AR)-based therapeutic exercises, real-time biofeedback monitoring, and, most specifically, introduces the ownership illusion to stimulate the user’s neural plasticity. The ownership illusion is developed by creating a Virtual Human Arm (VHA) model, which is driven by the user’s Surface Electromyogram (sEMG) signal. The evaluation of the developed system is conducted in terms of data analysis, performance analysis, and questionnaires with 15 healthy subjects, and results are discussed. Additionally, several demonstrations have been performed for clinical professionals at Port Kembla Hospital, Australia. The evaluation results and feedback from clinical professionals indicate satisfaction and acceptance of the ARIS system in the clinical setting.

Document Type

Book Chapter

Date of Publication

1-1-2025

Publication Title

Sustainable and Eco Friendly Process Management: Advancing Cleaner Technologies

Publisher

Taylor & Francis

School

School of Science

Comments

Al-Jumaily, A., Aung, Y. M., Sulthan, S. M., Yeo, K. S. K., Gapar, K. G. A., & Elaklouk, A. (2025). Hybrid upper limb rehabilitation system to stimulate neural plasticity through augmented illusion training. In Sustainable and eco friendly process management: Advancing cleaner technologies (pp. 265–282). Taylor & Francis. https://doi.org/10.1201/9781779643179-23

Copyright

subscription content

First Page

265

Last Page

282

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Link to publisher version (DOI)

10.1201/9781779643179-23