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May 22, 2026International Journal of Business Intelligence and Data Mining0 citationsOpen Access

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

XHXue HanFCFujiang CuiFWFeng Wang

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

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Han et al. (2026) studied this question.

synapsesocial.com/papers/6a0ff33bd674f7c03778bb66https://doi.org/10.1504/ijbidm.2026.10078554
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Sports training fatigue recognition using surface electromyography signals on wearable devices2026
  2. 2Automatic speech recognition method based on deep learning approaches for sports game review2026
  3. 3Basketball player tracking method based on multi-source data and attention mechanism2026
  4. 4Deep learning-based football training movement analysis and penalty feedback research2026
  5. 5Enhancing intrusion detection system performance under imbalanced data conditions using a hybrid deep learning framework2026