Bio-based self-powered triboelectric sensor for intelligent early-warning monitoring in rhythmic gymnastics

Abstract

Rhythmic gymnastics is characterized by high flexibility, explosive power, and multi-joint coordination; during vertical jumps (VG), kick leg (KL), split leap (SL), and landing, the lower limbs are readily exposed to complex mechanical loads and injury. To address the limitations of current motion-capture systems, force platforms, and inertial sensing technologies in portability, continuous monitoring, and power supply, this study develops a bio-based fiber/graphene-enhanced triboelectric nanogenerator (BG-TENG). The graphene conductive network, in concert with a Kapton elastic layer, Cu electrode, and PTFE negative tribolayer, forms a flexible contact-separation sensor. The device achieves optimal output at 3 wt. % graphene loading and exhibits stable voltage responses and favorable cycling performance under varied velocities, loads, and bending angles. When deployed on the plantar region, ankle joint, and knee joint and validated in conjunction with an IMU, the BG-TENG effectively characterizes ankle acceleration, knee flexion-extension angle, and plantar deformation. Using multichannel signals, a recognition model was established for correct and injury-state movements involving VG, KL, and SL, enabling accurate classification of six action categories and real-time visualized early warning through an upper computer system. This system offers a green, flexible, and wearable intelligent-monitoring strategy for early warning of sports injuries, movement-quality assessment, and personalized training feedback.