Biobased Self-Driven Triboelectric Sensor for Multimodal Analysis of Exercise Fatigue
Dongsheng Liu, Zihao Gao, Yunlu Wang, Zihang Cheng, Bo Wang, Qingyang Feng, Yuzhang Wen, Zhuo Lu, Yupeng Mao, Haidong Yang
Abstract
Traditional exercise fatigue monitoring technologies have faced challenges, including high costs, operational complexity, and invasiveness, which limit their practicality for daily training and health management. A biobased pulp wool triboelectric nanogenerator (PW-TENG) has been developed and integrated with a heart rate strap (HRS) and inertial measurement unit (IMU) to establish a multimodal fatigue monitoring system. Doping BaTiO 3 particles, spraying conductive graphite, and bidirectional W-shape encapsulation have enhanced its output performance by 100%, tripled the contact-separation efficiency, and achieved ultrafast response and recovery times (8.4 and 4.6 ms) with 6200 cycles stability. In speed experiments, nine metrics collected by PW-TENG and IMU at six speeds were analyzed using principal component analysis (PCA), which showed that PC1 and PC2 contributed 76.4 and 13.4% of the variance to the speed, respectively. In fatigue experiments, the trend of human fatigue-induced changes in locomotor characteristics is verified, indicating that PC1, PC2, and PC3 contributed 29.1, 21.5, and 14.4% to the three phases of fatigue, respectively. In contrast, the PC1 contribution of the PW-TENG alone is as high as 53%, demonstrating excellent fatigue sensitivity. This noninvasive, robust system has provided a practical solution for optimizing training and personalized health management, showing significant potential in sports science and medical applications.