Abstract
We propose a learning support system with extremely low latency and low cognitive load to correct the user’s motion. In previous studies, visual and haptic feedback has been mainly used to support motion learning, but there is a delay between the presentation of the stimulus and the modification of the action. However, this delay is due to reaction time and cognitive load and is difficult to shorten. This study proposed a system for solving this problem by combining Electrical Muscle Stimulation (EMS) and prediction of the user’s motion. In order to improve the control ability of the underhand throwing, we used the system to tell the subject the release point during the underhand throwing motion and verified the learning effect. This experiment revealed that EMS tended to be effective in teaching the ball’s release point, although it did not improve the control ability of the underhand throwing motion. In addition, although the effectiveness of EMS for motion learning was not yet fully evaluated, this study showed the possibility of applying EMS to support learning of motion.
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NatnetSDK: https://optitrack.com/software/natnet-sdk.
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Niwa, R., Izumi, K., Suzuki, S., Ochiai, Y. (2022). EMS-Supported Throwing: Preliminary Investigation on EMS-Supported Training of Movement Form. In: Antona, M., Stephanidis, C. (eds) Universal Access in Human-Computer Interaction. Novel Design Approaches and Technologies. HCII 2022. Lecture Notes in Computer Science, vol 13308. Springer, Cham. https://doi.org/10.1007/978-3-031-05028-2_31
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