Local Euler angle pattern recognition for smash and backhand in badminton based on arm position

摘要

Badminton is the most favourite sport in Indonesia. Since elementary school or earlier, children play badminton in a formal class or informal games. So, there are so many kind of styles in playing badminton. In this research, the pattern of arm kinesiology while playing badminton was studied, especially smash and backhand. The right arm of human was segmented into four parts: shoulder, elbow, wrist and back of hand. The 3-dimension local Euler angle of each parts was recorded by using gyro sensor made by Motion Node. The pattern of the segment position was investigated to distinguish smash and backhand. The result shows that there was a clear pattern caused by the movement of four parts of arm while performing smash and backhand. This pattern can be used to evaluate a process of arm moving while performing smash or backhand in badminton.