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A scalable, hyperstable intelligent fibre velocimeter for dynamic digitization of resistance training
Jingyu Ouyang1,2, Pan Li3, Yuqi Zou3
1Research Center for Intelligent Fiber Devices and Equipment, State Key Laboratory of New Textile Materials and Advanced Processing, School of Physical Education, Wuhan National Laboratory for Optoelectronics, School of Materials Science and Engineering, Department of Geriatrics, Department of Orthopedics, and Key Laboratory of Vascular Aging, Ministry of Education, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430074, China.
Abstract:
Real-time accuracy and continuous dynamic monitoring capability of devices are crucial for the scientific configuration and dynamic modulation of resistance training, such as strength training, rehabilitation and in-orbit training for astronauts. However, developing monitoring devices capable of providing real-time, accurate and dynamic quantification for high-velocity resistance training remains a notable challenge. Here, we present a scalable and hyperstable intelligent fibre velocimeter designed for the digital, real-time and dynamic monitoring of resistance training. By incorporating the fibre velocimeter as a core component, the intelligent resistance band system demonstrates cyclic stability exceeding 120 000 cycles and torsional insensitivity, facilitating hyperstable velocimetry within the 0-2.5 m/s range with an accuracy exceeding 95%. This system is capable of capturing instantaneous training parameters, including velocity, tension and power during cyclic resistance training, as well as performing dynamic evaluations and providing early warnings for overspeed or fatigue. A comparative experiment with and without feedback guidance from the intelligent resistance band system verified that its precise feedback significantly elevates training intensity, explosive performance and movement compliance while reducing injury risk. Given its compact design, real-time sensing and evaluation of highly accurate multidimensional training parameters, and hyperstability, this system potentially advances training digitization and sports intelligence.
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