SPinPong - Virtual reality table tennis skill acquisition using visual, haptic and temporal cues - Wu, E.; Piekenbrock, M.; Nakumura, T.; Koike, H. (IEEE Transactions on visualization and computer graphics, 2021)
Learning an advanced skill in sports requires a huge amount of practice and players also have to overcome both physical difficulties and the dullness of repetitive training. Returning a fast spin shot in table tennis could be taken as an example, as athletes need to judge the spin type and decide the racket pose within a second, which is difficult for beginners. Therefore, in this paper, we show how to design an intuitive training system to acquire this specific skill using different cues in Virtual Reality (VR). Using VR, we can easily provide visual information, attach haptic devices, and distort the speed of time, however, it is difficult to decide which types of information could benefit the training. In an initial study, by comparing real world training with VR training, we showed the effect of VR training and obtained some insights about augmentation for training spin shots. The training system was then improved by adding three new conditions using different visualizations and temporal distortions, as well as a haptic racket for creating realistic feedback. Finally, we performed a detailed experiment, which suggest a significant improvement of skill for each condition compared to the baseline, while a qualitative evaluation indicates that both users' motivation and their understanding of spin are increased by using our system.