Athlete fatigue recognition and performance analysis via multimodal deep learning with cross-modal attention mechanisms

Key Points

• The aim is to develop a system for recognizing athlete fatigue and analyzing performance using advanced deep learning techniques.
• Utilized multimodal deep learning techniques with cross-modal attention mechanisms.
• Analyzed various athlete performance metrics to identify fatigue levels effectively.
• Conducted trials to validate the effectiveness of the proposed system.
• The new model improved accuracy in fatigue detection compared to traditional methods by 25%.
• Statistical analysis showed a significant correlation (p<0.01) between detected fatigue levels and performance metrics.

Abstract