MECHANICAL VISION USING ARTIFICIAL INTELLIGENCE TECHNIQUES TO IMPROVE AND DEVELOP SKILL PERFORMANCE DURING JUMPS IN KARATE

Abstract

Mariam Ahmad Abu Alim, MazIn Hadi Kzir and Mohammed Asim Ghazi*

This study investigates the application of mechanical vision and artificial intelligence (AI) techniques to enhance skill performance during jumps in karate. By leveraging these technologies, practitioners can receive real-time feedback on their jumps, leading to faster skill acquisition and mastery. The research methodology involves collecting data from karate practitioners, analyzing their movements using 3D motion capture systems and high-resolution cameras, and developing an AI model to identify effective jumping mechanics. The study concludes that integrating AI tools can provide real-time feedback, improve technique, analyze movements, and optimize training plans, leading to significant improvements in jump mechanics and overall performance in karate.