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Biobased Self-Driven Triboelectric Sensor for Multimodal Analysis of Exercise Fatigue. | LitMetric

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Article 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 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.

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http://dx.doi.org/10.1021/acssensors.5c01574DOI Listing

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