Abstract
Compared with conventional virtual rehabilitation programs, the self-adaptive virtual rehabilitation system has the advantage of dynamically adjusting the training difficulty according to the users’ real-time motion data collected, showing the potential to improve the rehabilitation experiences and assist the therapists with the flexibility provided. Movement enhancement, which visually amplifies the user’s motion, exhibits significant promise in rehabilitation to improve the user’s confidence and motivation. This study aims to propose a self-adaptive strategy in a virtual rehabilitation system based on movement enhancement and evaluate its effectiveness and improvements in user experience. This study will be beneficial for the future development of virtual rehabilitation programs that combine self-adaptive systems and movement modulation, consequently helping individuals involved in virtual rehabilitation with improved user experience.
Original language | English |
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Title of host publication | 16th International Conference on Human System Interaction (HSI 2024) |
Publisher | IEEE Computer Society |
Pages | 1-6 |
ISBN (Electronic) | 9798350362916 |
DOIs | |
Publication status | Published - 11 Jul 2024 |
Event | 16th International Conference on Human System Interaction, HSI 2024 - Paris, France Duration: 8 Jul 2024 → 11 Jul 2024 |
Publication series
Name | International Conference on Human System Interaction, HSI |
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ISSN (Print) | 2158-2246 |
ISSN (Electronic) | 2158-2254 |
Conference
Conference | 16th International Conference on Human System Interaction, HSI 2024 |
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Country/Territory | France |
City | Paris |
Period | 8/07/24 → 11/07/24 |
Keywords
- Virtual reality
- rehabilitation
- self-adaptive system
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Wang, L., Huang, M., Liu, J., Xiao, S., & Yang, R. (2024). Design and evaluation of a self-adaptive strategy for movement modulation in virtual rehabilitation. In 16th International Conference on Human System Interaction (HSI 2024) (pp. 1-6). (International Conference on Human System Interaction, HSI). IEEE Computer Society. https://doi.org/10.1109/HSI61632.2024.10613573