Real-Time and Automatic System for Performance Evaluation of Karate Skills Using Motion Capture Sensors and Continuous Wavelet Transform

Abstract

In sports science, the automation of performance analysis and assessment is urgently required to increase the evaluation accuracy and decrease the performance analysis time of a subject. Existing methods of performance analysis and assessment are either performed manually based on human experts’ opinions or using motion analysis software, i.e., biomechanical analysis software, to assess only one side of a subject. Therefore, we propose an automated system for performance analysis and assessment that can be used for any human movement. The performance of any skill can be described by a curve depicting the joint angle over the time required to perform a skill. In this study, we focus on only 14 body joints, and each joint comprises three angles. The proposed system comprises three main stages. In the first stage, data are obtained using motion capture inertial measurement unit sensors from top professional fighters/players while they are performing a certain skill. In the second stage, the collected sensor data obtained are input to the biomechanical software to extract the player’s joint angle curve. Finally, each joint angle curve is processed using a continuous wavelet transform to extract the main curve points (i.e., peaks and valleys). Finally, after extracting the joint curves from several top players, we summarize the players’ curves based on five statistical indicators, i.e., the minimum, maximum, mean, and mean ± standard deviation. These five summarized curves are regarded as standard performance curves for the joint angle. When a player’s joint curve is surrounded by the five summarized curves, the performance is considered acceptable. Otherwise, the performance is considered unsatisfactory. The proposed system is evaluated based on four different karate skills. The results of the proposed system are identical to the decisions of the expert panels and are thus suitable for real-time decisions.

Analyzing Handball Techniques Using A Biomechanical Approach: A Systematic Literature Review

“…Finding Method (Fathalla et al, 2023) Observasional Study Joint Angle (Müller et al, 2022) Observasional Study Distance traveled, velocity, and changes in direction. (Lijewski et al, 2021) Observasional Study Segmental bioelectrical impedance analysis (SBIA)/Angle (Wilczyński et al, 2022) Non RCT Trial Postural stability and angle (Russomanno et al, 2021) Observasional Study Movement (Guignard et al, 2022) Observasional Study Movement (van den Tillaar et al, 2021) Non RCT Trial Handball throws and predict ball velocity, offering a practical and automated method for quantifying throw counts and classifying approach and throw types.…”

“…Sports biomechanics examines athletic movements to enhance performance and reduce injury risk, with motion technologies being used in support of athletes (Aresta et al, 2023). Biomechanics in sports performance involves automating performance analysis and assessment by using motion capture sensors and biomechanical software to extract joint angle curves and summarize them into standard performance curves (Fathalla et al, 2023). Sports biomechanics aims to reduce injury risk and improve sports performance, with the Journal of Sports Sciences combining Sports Medicine and Biomechanics sections to form the current Sports Medicine and Biomechanics section (Wallace et al, 2022).…”