Kinetic Analysis Using Computer Vision Technology in the Execution of the Badminton Smash Skill by an Iraqi National Team Player

Abstract

The importance of the current study lies in the employment of one of AI advance technology (Computer Vision) in kinematic analysis in sports. These techniques allow to follow the player's movement, and extract accurate quantitative metrics from video such as joint positions, motion paths, velocities, and time-series variations in performance. This is considered as a new tendency in sport measurement. This approach minimizes dependence on subjective observation and visual estimation, offering coaches and athletes objective, quantifiable data amenable to both statistical and mechanical analysis. Such data can subsequently be leveraged to enhance achievement (performance). Moreover, it emphasizes kinetic variables as fundamental parameters that explain force, power, torque, momentum, and energy generation during execution, moving beyond a mere qualitative description of the movement's external appearance. This is because the skillful performance in badminton does not only depend on joint position and angles of movement, but also it affected by how power is produced, distributed, and transferred through the kinetic chain, and how the player's changes the muscular strength (biomechanics) to high speed for racket and shuttlecock.
The aim of the research is to find out new means in analyzing the performance, particularly for those games with high speed sport likes badminton. This is because smash skill is one of the most important attack skills which determines match points and demands a high degree of coordination among kinematic sequencing, reactive speed, and projection angle, in order to guarantee maximal post-impact shuttlecock velocity. Mostly, the local and traditional studies depend on visual observations or traditional programs in dynamic analysis of body movement during the performance. The Computer Vision technology having proven its capability in athletic movement analysis via body landmark detection and kinematic parameter estimation from video.
The research problem delimited the population to all recorded attempts of the Iraqi national number one (Rami Wissam Salah), as he is the player who settles outcomes and earns medal-winning results across both singles and doubles champions. concerning the samples of the study, the researcher takes (50) try only and extracts its data. These observations are considered as samples because the samples are the taken observation wither from one person or group of people. The researcher used appropriate equipment and devices for his research. The most significant of them is AI technology (Computer Vision) which is a framework of algorithms and mathematical models that processes digital visual data (images/video) for the purposes of object detection, recognition, classification, and temporal tracking, in addition to motion analysis and 3D scene reconstruction. The study's results showed that the kinetic energy variable had the highest contribution rate to the proficiency test score, and the Computer Vision analysis was highly accurate in detecting subtle motion details.