Introduction This study explores the potential of artificial intelligence (AI) to enhance the accuracy and efficiency of video review systems in Taekwondo, addressing limitations in current human-based judgment processes during competitions. Methods A total of 241 video review cases from the 2024 Paris Olympic Taekwondo competition were analyzed. AI-based judgments were generated using ChatGPT-4.5 and OpenPose deep learning models. The AI-generated penalty decisions were statistically compared to those made by international video review referees using Cohen's Kappa coefficient. Results The AI system demonstrated strong agreement with international referees ( κ = 0.897, p 0.001). Discrepancies occurred in only 9 out of 241 cases, primarily in scenarios involving head strikes with minimal contact or visual occlusion. Additionally, the AI system reduced average review time by approximately 81% by automatically identifying critical frames. Discussion While AI significantly improved efficiency and showed high consistency with expert judgments, human oversight remains crucial for ambiguous or complex cases. A hybrid model—AI-assisted pre-review followed by referee confirmation—is proposed to optimize decision-making. Future developments should focus on real-time detection, multi-angle video integration, and application to other sports such as baseball, basketball, boxing, and judo.
Zhang et al. (Mon,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: