Badminton Stroke Movement Comparison Using Kinect-Based Adaptive Range of Movement Index Technique

Objectives: In this paper, we extended our previous novel lossless compact view invariant compression technique, namely Range of Movement Index (RoMI) by fusing an adaptive module. Methods: An adaptive module is proposed to fuse with the RoMI to elevate the technique to become left-right handed invariant. The module will firstly identify the label of the normalized RoMI value from a particular range in order to determine left or right side. Subsequently, the adaptive mapping functions are utilized to perform left to right or right to left mappings using the identified label. Findings: Generally, badminton players can be categorized into three different handed: mainly right-handed players and left handed-players and rarely the ambidextrous players. In our previous technique, the RoMI can only benchmark or perform computerized badminton movement quality comparison based on the handedness of a badminton player. In specific, the benchmarking mechanism is left-right handed variant, i.e., left-handed player with left-handed player and right-handed player with right-handed player. This limitation will increase the effort to benchmark badminton players’ movement quality with different handedness of badminton player. The proposed adaptive module enables the comparison of computerized stroke movements between different players with different handedness. As such, this new method will identify the labels of the normalized RoMI and performs adaptive mapping to match with the reference handedness to produce a more consistent benchmarking of different handedness badminton players. Improvement: The ability to benchmark different handedness badminton players enables the system to be adopted by a larger range of badminton players and further simplify data collection and analysis procedures.