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Designing and Analyzing In-Place Motor Tasks in Virtual Reality With Goal Functions
- Source :
- IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 2928-2938 (2024)
- Publication Year :
- 2024
- Publisher :
- IEEE, 2024.
-
Abstract
- Goal functions make virtual goal-oriented motor tasks easier to analyze and manipulate by explicitly linking movement to outcome. However, they have only been used to study constrained (e.g., planar) upper limb movements. We present a design framework for integrating goal functions with unconstrained postural and upper limb movements in a virtual reality (VR) device. VR tasks designed with the framework can mimic unconstrained natural motions and thus train a range of functional movements yet remain analytically tractable. We created three in-place VR motor tasks: a bow-and-arrow, a reach-and-strike, and a punching bag task. Each task was adjusted to subject-specific workspace limits and anthropometrics. We studied the effects of 3 days of practice and 3 reach/lean distances on task performance in 12 healthy adults. Subjects performed all tasks on day 1 with moderate proficiency and improved with practice at all reach/lean distances. Task-specific results showed that performance decreased and movement variability increased near the edge of the reaching workspace; viewing angles and the imperfect depth cues in VR likely led to biases in performance and practice could attenuate the former effect; in reach-and-strike, subjects learned movement patterns similar to those seen in a real-world striking sport. These results show that our framework can deliver tasks useful for analyzing and training motor performance and can guide future in-place motor training. Post-hoc, we demonstrated the feasibility of generalizable methods that adjust required movement speeds and task difficulty for impaired populations.
Details
- Language :
- English
- ISSN :
- 15344320 and 15580210
- Volume :
- 32
- Database :
- Directory of Open Access Journals
- Journal :
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.693a766def694bac95167546e9b4e027
- Document Type :
- article
- Full Text :
- https://doi.org/10.1109/TNSRE.2024.3439500