A Theoretical Framework of Extrinsic Feedback Evaluation in Football Training Based on Motion Templates Using Motion Capture

Abstract: Motion capture technology (MoCap) has emerged as a pivotal innovation, significantly impacting various sectors, including sports. In football training, MoCap is especially crucial for analyzing player movements with precision. Despite its potential, there remains a notable gap in the utilization of MoCap to create motion templates (MTs) that generate extrinsic feedback, particularly in football. This article proposes a comprehensive theoretical framework for evaluating extrinsic feedback in football training through MTs created using MoCap technology and Reverse-Gesture Description Language (R-GDL). The development of this framework involves several key steps: a literature review, acquaintance meetings, interviews, procedural approvals, experimentation, data conversion, MTs creation, and data evaluation. The framework integrates elements such as football players, MoCap systems, raw and processed data, MTs, evaluation processes, and extrinsic feedback models. The main purpose is to harness the full potential of MoCap technology, enhancing the evaluation and improvement of football training activities. By implementing this framework, we aim to revolutionize how football training is analyzed and optimized, providing coaches and players with invaluable insights and feedback.

Amir Irfan Mazian, Wan Rizhan, Normala Rahim, Muhammad D. Zakaria, Mohd Sufian Mat Deris, Fadzli Syed Abdullah and Ahmad Rafi. “A Theoretical Framework of Extrinsic Feedback Evaluation in Football Training Based on Motion Templates Using Motion Capture”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.11 (2024). http://dx.doi.org/10.14569/IJACSA.2024.0151129

@article{Mazian2024,
title = {A Theoretical Framework of Extrinsic Feedback Evaluation in Football Training Based on Motion Templates Using Motion Capture},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151129},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151129},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {11},
author = {Amir Irfan Mazian and Wan Rizhan and Normala Rahim and Muhammad D. Zakaria and Mohd Sufian Mat Deris and Fadzli Syed Abdullah and Ahmad Rafi}
}