Digital Sports Teaching Methods Based on Intelligent Human-Computer Interaction Motion Capture Technology

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Lu Liu, Juntong Liu

Abstract

The convergence of digital technology and sports education has paved the way for innovative approaches to athletic skill development and performance enhancement. This study investigates the efficacy of digital sports teaching methods based on Intelligent Human-Computer Interaction (IHCI) motion capture technology in optimizing athlete performance across diverse sports disciplines. Through a comprehensive analysis of performance metrics, biomechanical parameters, and longitudinal skill development trajectories, the study evaluates the impact of IHCI technology on athlete learning outcomes and training effectiveness. Results demonstrate significant improvements—technique refinement following training interventions facilitated by IHCI motion capture systems. The integration of personalized feedback generated by the technology with traditional coaching practices enhances athlete engagement, skill acquisition, and long-term performance growth. While the findings underscore the transformative potential of technology-driven approaches in sports education, considerations for practical implementation, limitations, and avenues for future research are discussed. This study contributes to advancing our understanding of the role of IHCI motion capture technology in optimizing athletic performance and shaping the future of sports teaching and training methodologies.

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