Design of Virtual Reality Exergames for Upper Limb Stroke Rehabilitation Following Iterative Design Methods: Usability Study
Bibliographic record
Abstract
BACKGROUND: Since the early 2000s, there has been a growing interest in using exercise video games (exergames) and virtual reality (VR)-based interventions as innovative methods to enhance physical rehabilitation for individuals with multiple disabilities. Over the past decade, researchers and exercise professionals have focused on developing specialized immersive exercise video games for various populations, including those who have experienced a stroke, revealing tangible benefits for upper limb rehabilitation. However, it is necessary to develop highly engaging, personalized games that can facilitate the creation of experiences aligned with the preferences, motivations, and challenges communicated by people who have had an episode of stroke. OBJECTIVE: This study seeks to explore the customization potential of an exergame for individuals who have undergone a stroke, concurrently evaluating its usability as a technological tool in the realm of physical therapy and rehabilitation. METHODS: We introduce a playtest methodology to enhance the design of a VR exergame developed using a user-centered approach for upper limb rehabilitation in stroke survivors. Over 4 playtesting sessions, stroke survivors interacted with initial game versions using VR headsets, providing essential feedback for refining game content and mechanics. Additionally, a pilot study involving 10 stroke survivors collected data through VR-related questionnaires to assess game design aspects such as mechanics, assistance, experience, motion sickness, and immersion. RESULTS: The playtest methodology was beneficial for improving the exergame to align with user needs, consistently incorporating their perspectives and achieving noteworthy results. The pilot study revealed that users had a positive response. In the first scenario, a carpenter presents a game based on the flexion-extension movement of the elbow; the second scenario includes a tejo game (a traditional Colombian throwing game) designed around game mechanics related to the flexion-extension movement of the shoulder; and in the third scenario, a farmer challenges the player to perform a movement combining elbow flexion and extension with internal and external rotation of the shoulder. These findings suggest the potential of the studied exergame as a tool for the upper limb rehabilitation of individuals who have experienced a stroke. CONCLUSIONS: The inclusion of exergames in rehabilitation for stroke-induced hemiparesis has significantly benefited the recovery process by focusing on essential shoulder and elbow movements. These interactive games play a crucial role in helping users regain mobility and restore practical use of affected limbs. They also serve as valuable data sources for researchers, improving the system's responsiveness. This iterative approach enhances game design and markedly boosts user satisfaction, suggesting exergames have promising potential as adjunctive elements in traditional therapeutic approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".