Key challenges remain, including data heterogeneity, limited generalizability, compliance issues, and privacy concerns. Future directions point toward personalized modeling, explainable systems, federated learning, and digital twin frameworks. Together, these advancements mark a shift toward proactive, intelligent injury prevention across athletic and clinical settings.
Dong et al. (2026) studied this question. Artificial intelligence and wearable sensors mark a shift toward proactive, intelligent injury prevention across athletic and clinical settings, despite ongoing data and privacy challenges.