Eye-hand coordination training in virtual reality

Reaction time training systems are being used to improve athlete performance for different sports, including boxing, football, and even the Formula 1. Until now, such setups used physical, flat surfaces, such as a 2D touch screen or buttons mounted on a wall or frame. Here, we investigate a Virtual Reality version of such an eye-hand coordination training system and also show that Fitts' law can be used to assess user performance more accurately. We conducted three user studies to investigate different aspects of such VR-based training environments for sports training. In the first one, we explored different target arrangements and showed that user performance is maximized with the dominant hand and a vertical target plane. In the second, we studied different combinations of visual and haptic feedback and how they affect user performance for different target and cursor sizes. Results illustrated that haptic feedback does not increase user performance when it is added to visual feedback. We also used the effective throughput measure of Fitts' law and the associated throughput measure to show that user performance in eye-hand coordination tasks can be accurately assessed with this method, independent of user behaviors. In the third experiment, 12 participants performed an eye-hand coordination reaction test in three conditions: in mid-air with or without a VR controller as well as with passive haptic feedback through hitting a soft-surface wall. We also altered target and cursor sizes and analyzed user performance again with the throughput measure. According to the results, subjects were slower and their throughput was lower when they hit a solid surface to interact with virtual targets. Our results show that Fitts' model can be applied to VR-based eye-hand coordination training systems to measure and assess participant's performance. We believe that our work will inform system development for professional and amateur athletes' performance assessment systems.