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Video Game-Based Trunk Exercises for Rehabilitation in Chronic Stroke Survivors: A Mixed-Methods Feasibility Study
- Source :
- Sensors, Vol 24, Iss 21, p 6830 (2024)
- Publication Year :
- 2024
- Publisher :
- MDPI AG, 2024.
-
Abstract
- Aim: To assess the feasibility of video game-based trunk exercises using the Valedo® system in a chronic stroke population. Method: Ten chronic stroke survivors (eight males and two females, mean age 63 ± 15 years) were asked to complete 18 intervention sessions, each lasting 45 min., over 6–8 weeks. Feasibility was evaluated quantitatively using the Psychosocial Impact of Assistive Devices Scale (PIADS) as well as through recruitment, retention, adherence, and safety measures. Qualitative data on feasibility were collected through post-intervention semi-structured interviews. Descriptive analysis was used to summarize participant characteristics, recruitment, retention, and adherence. Qualitative data were analyzed using thematic analysis of the interviews. Results: Twelve stroke survivors were recruited from Southampton (United Kingdom) and Riyadh (Kingdom of Saudi Arabia), with two participants dropping out after the baseline assessment session. The remaining ten participants completed the study with a mean adherence of 96.11% to the planned sessions. No serious adverse effects were reported, however, four participants did experience trunk muscle tightness and fatigue. Post-intervention interviews revealed that participants encountered some physical and cognitive challenges while playing the Valedo video games. However, they felt that the implementation of trunk exercises using video games was safe, as the exercises were performed in a secure environment and in safe positions. Conclusions: The findings suggest that the Valedo system is feasible for delivering trunk exercises to chronic stroke survivors. Several factors should be considered when implementing this type of intervention in the future.
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 24
- Issue :
- 21
- Database :
- Directory of Open Access Journals
- Journal :
- Sensors
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.8896bd1900b2461097df6c0c565eb574
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/s24216830