Toward intelligent wearables: engineering self-powered triboelectric nanofiber sensors for the classification of risky ankle postures

sufficient to charge capacitors and power small electronics. Integrated into an ankle-worn platform, the fiber-based TENG device generated high-fidelity biomechanical signals. When analyzed using machine learning algorithms, the system achieves up to 99% accuracy across 700 datasets in detecting risky motions preceding sprains. This intelligence shifts the system from passive monitoring to proactive prevention, providing actionable feedback before injury onset. Beyond ankle injuries, this convergence of self-powered materials and artificial intelligence establishes a new class of intelligent wearables and paves the way for advanced musculoskeletal health monitoring and preventive medicine.