Artificial Intelligence in Biomechanics: A Narrative Review of Current Applications in Diagnostic and Physical...

Artificial intelligence (AI) has impacted numerous scientific and clinical disciplines including biomechanics. Here, this review highlights how AI can be applied to human movement, injury prevention, rehabilitation, sports performance and prosthetic control. Crucial AI methods, such as machine learning (ML), deep learning, and computer vision (CV), facilitate the automated, accurate, and real-time analysis of complex biomechanical data derived from wearable sensors, videos and other modalities These technological developments have expanded the use of biomechanical assessment beyond its traditional laboratory limits, fueling the development of markerless motion capture, personalized rehabilitation, and immersive virtual training environments. Despite advances, there are still challenges in the generalization of models, interpretation of predictions, privacy of data, and ethical issues. Upcoming future steps require both software and datasets to be standardized, explainable AI (XAI) strategies for AI-driven biomechanics, interdisciplinary collaboration to fulfill the promise of AI-driven biomechanics, responsibility and equitability of AI-driven biomechanics.