Citation

Lua, Zhiqiang and Lim, Tek Yong (2023) Development of a Data-driven Self-adaptive Upper Limb Virtual Rehabilitation System for Post Stroke Elderly. In: 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 25-29 March 2023, Shanghai, China.

Text 15.pdf - Published Version Restricted to Repository staff only Download (437kB)

Abstract

The study aims to develop a virtual rehabilitation system to assist upper limb motor training for older post-stroke patients. The system contains data-driven virtual exergames simulating the task-oriented training; receives the rehabilitation prescription and the online data collected from the multi-mode hand controller and the depth camera; assesses online patient's performance which in turn updates the data of virtual exergames to adapt to the patient's training progress. Its innovation is providing precision rehabilitation via gaining the personalized learning experience to improve the adherence to and effectiveness of virtual rehabilitation.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Virtual rehabilitation , precision rehabilitation , virtual exergame , machine learning , 1.3.7 [Three-Dimensional Graphics and Realism]: Virtual Reality
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	02 Jun 2023 01:19
Last Modified:	02 Jun 2023 01:19
URII:	http://shdl.mmu.edu.my/id/eprint/11446

Downloads

Edit (login required)