Presentation Type
Event
Description
This research investigates fine motor control in virtual reality (VR) using a buzz-wire style precision task. Participants guide a loop along a wire while motion telemetry captures hand stability and movement patterns. Results show that individuals with combined VR, gaming, and athletic experience demonstrate smoother trajectories and reduced jitter, highlighting how prior expertise influences performance in immersive motor tasks.
Recommended Citation
Sunny, M. J. M. and Basu, Dr. Aryabrata, "Behavioral and Biomechanical Analysis of Hand Movement Stability in Virtual Reality" (2026). Research and Creative Works Expo. 1.
https://research.ualr.edu/expo/2026/presentations/1
DOI
https://doi.org/10.1109/VRW66409.2025.00287
Included in
Behavioral and Biomechanical Analysis of Hand Movement Stability in Virtual Reality
This research investigates fine motor control in virtual reality (VR) using a buzz-wire style precision task. Participants guide a loop along a wire while motion telemetry captures hand stability and movement patterns. Results show that individuals with combined VR, gaming, and athletic experience demonstrate smoother trajectories and reduced jitter, highlighting how prior expertise influences performance in immersive motor tasks.

Comments
This research is highly valuable because it connects VR interaction design with real human motor behavior. The buzz-wire task provides a clear and measurable way to study fine motor control, hand stability, movement smoothness, and precision in immersive environments. One important strength of this study is that it considers prior experience from multiple domains, including VR use, gaming, and athletic background, rather than treating all participants as having the same skill level. The finding that participants with combined VR, gaming, and athletic experience show smoother trajectories and reduced jitter suggests that real-world and virtual experience may transfer into better performance in VR-based precision tasks. This has meaningful implications for the design of adaptive VR training systems, especially in areas such as rehabilitation, surgical training, nursing education, industrial training, and skill-based simulation. In addition, this research could be useful for nursing and healthcare-related departments as a tool to evaluate hand stability, fine motor control, and possible hand instability. With further validation, VR-based precision tasks like this could support assessment or early screening of motor-control difficulties and help design targeted training or rehabilitation exercises. Overall, this work contributes to a better understanding of how user background affects performance in VR and supports the development of more personalized and effective immersive systems.