Article: Design of athlete physical training system based on a smart wearable device Journal: International Journal of Computational Systems Engineering (IJCSYSE) 2026 Vol.10 No.1/2/3/4 pp.306 - 317 Abstract: Smart wearables are any object that incorporates electronic technology or a gadget worn close to the body. Information may be tracked in real-time with the help of these athletes' progress; coaches no longer need to depend just on timings and splits on precise measurements of position, distance, velocity, and acceleration. The challenging characteristic of such physical training is the athlete's irregular optimality, scalability and generalisability. The gathering and quality of data is a significant obstacle to sports analytics. Even though there is a mountain of data, gathering and cleansing it is not always easy. Data quality is another potential issue; incomplete or erroneous data is a real possibility. Hence, in this research, smart sensors enabled intelligent physical monitoring systems on IoT platform (SS-IoT) technologies, which have been improved for sports monitoring systems with the athlete's physical training. The BP neural network establishes the athletes' physical training for data processing and monitoring in that physical control mechanism. Accurately predicting an athlete's physical state via simulation is a cutting-edge scientific method for increasing the efficiency of physical training. The experimental results show the SS-IoT achieves an accuracy ratio of 90%, efficiency ratio of 90.6%, prediction ratio of 91%, performance ratio of 95%, and error rate of 8.56% compared to other methods. Inderscience Publishers - linking academia, business and industry through research

Title: Design of athlete physical training system based on a smart wearable device

Authors: Shikai Cai

Addresses: College of Physical Education, Huainan Normal University, Huainan 232038, Anhui, China

Abstract: Smart wearables are any object that incorporates electronic technology or a gadget worn close to the body. Information may be tracked in real-time with the help of these athletes' progress; coaches no longer need to depend just on timings and splits on precise measurements of position, distance, velocity, and acceleration. The challenging characteristic of such physical training is the athlete's irregular optimality, scalability and generalisability. The gathering and quality of data is a significant obstacle to sports analytics. Even though there is a mountain of data, gathering and cleansing it is not always easy. Data quality is another potential issue; incomplete or erroneous data is a real possibility. Hence, in this research, smart sensors enabled intelligent physical monitoring systems on IoT platform (SS-IoT) technologies, which have been improved for sports monitoring systems with the athlete's physical training. The BP neural network establishes the athletes' physical training for data processing and monitoring in that physical control mechanism. Accurately predicting an athlete's physical state via simulation is a cutting-edge scientific method for increasing the efficiency of physical training. The experimental results show the SS-IoT achieves an accuracy ratio of 90%, efficiency ratio of 90.6%, prediction ratio of 91%, performance ratio of 95%, and error rate of 8.56% compared to other methods.

Keywords: physical training; athlete; smart sensor; internet of things; BP neural network; data processing.

DOI: 10.1504/IJCSYSE.2026.151359

International Journal of Computational Systems Engineering, 2026 Vol.10 No.1/2/3/4, pp.306 - 317

Received: 09 Dec 2023
Accepted: 18 Jan 2024
Published online: 26 Jan 2026 *

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Title: Design of athlete physical training system based on a smart wearable device

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