The application of deep learning human pose estimation in sport: a systematic review - Aulton, C.; Wakili, L.; Strafford, B. W.; Davids, K.; Chiu, C.-Y. (Sports Medicine - Open, 2025)
Background Human Pose Estimation (HPE) has gained increasing attention in sports research due to advancements in Deep Learning (DL) movement skills, which enable precise joint localization in 2D and 3D visual data. DL-based HPE facilitates non-invasive analysis of movement patterns in real-world settings, providing actionable insights for training, performance optimisation, and injury prevention. This systematic review examines the application of DL-based HPE in sports, focusing on the availability and accessibility of training datasets, reproducibility for practitioners, and the influence of human factors. The review also offers recommendations to guide future research and applications.