The Effect of Biokinematic Variables Using Artificial Intelligence Techniques on the Performance of the Badminton Smash Skill in an Iraqi National Team Player

Abstract

The significance of the present study lies in the application of an advanced artificial intelligence technique, namely Computer Vision, to sports kinematic analysis. This approach enhances measurement accuracy compared with traditional methods and provides coaches and athletes with quantitative data that can be utilized to improve performance outcomes. Biomechanical components, including joint angles, distances, temporal variables, velocities, and forces, offer critical indicators of the variables that determine performance level. Such indicators enable the identification of strengths and weaknesses, which can subsequently be addressed by coaches and specialists. Furthermore, the use of these technologies contributes to saving time, effort, and financial resources when conducting similar studies, The research problem centers on the need to establish a modern method for performance analysis, particularly in fast-paced sports such as badminton. The smash skill is considered one of the most decisive offensive techniques, often determining match outcomes. Its successful execution requires a high level of integration between the kinetic chain, reaction speed, and projection angle to ensure maximum shuttlecock velocity following impact. However, many local studies still rely on visual observation or conventional software for dynamic analysis, which may lack precision in capturing detailed body movement during skill execution. In contrast, Computer Vision has demonstrated effectiveness in sports motion analysis through the detection of body features and the extraction of kinematic parameters from video data.The research population was defined as all observable attempts performed by the top-ranked Iraqi badminton player, Rami Wissam Salah, due to his consistent achievement of decisive match results and medal-winning performances in both singles and doubles competitions, The study sample consisted of fifty (50) recorded observations, from which the required data were extracted. These observations are treated as representative samples, as samples in this context refer to recorded performance instances obtained from either a single individual or multiple participants, To achieve the research objectives, the researcher employed appropriate tools and instruments, most notably Computer Vision technology. This technology comprises a system of algorithms and mathematical models designed to process digital visual data (images and video) for the purposes of object detection, recognition, classification, and temporal tracking, in addition to motion analysis and three-dimensional scene reconstruction.