In this research, we propose a visual-feedback system and evaluate it based on motion-sensing and computational technologies. This system will help amateur athletes imitate the motor skills of professionals. Using a self-organizing map (SOM) to visualize high-dimensional time-series motion data, we recorded the cyclic motion information, including the muscle activities, of a male subject as he pedaled a bicycle ergometer. To clarify the difference between the subject’s motor skill and the target motor skill in a cyclic movement, we used the modified SOM algorithm; a visual-feedback system was developed, which displayed the target motion as a circular trajectory on a two-dimensional motor skills map. The subject trained by observing only the displayed static target trajectory; the subject’s real-time trajectory was constructed from the subject’s real-time motion. We validated our proposed framework for the visual-feedback system by evaluating the motion performance of a subject using feedback training.
Dynamic Gesture Recognition System with Gesture Spotting Based on Self-Organizing Maps