Smart Swimming Training: Wearable Body Sensor Networks Empower Technical Evaluation of Competitive Swimming
Document Type
Article
Publication Date
2-1-2025
Abstract
The combination of wearable sensors and competitive sports provides quantitative information for scientific training, effectively assisting athletes in improving their athletic performance. This study presents a technical framework for athletic sports assessment in competitive swimming based on body-area sensor networks. In our approach, wearable inertial sensor nodes are placed on specific body parts of the athletes to capture motion data during different competitive swimming strokes. Multiwearable inertial sensor nodes are worn on specific body parts of athletes for real-time monitoring motion data during training sessions. A motion intensity detection-based error-state-Kalman-filter algorithm is proposed for multisensor data fusion. Additionally, through kinematic statistical analysis, the characteristics of joint motion during training are clearly explained. Furthermore, a deep learning network that fuses sensor time series and human skeleton graphs is proposed for different stroke phase segmentation, enabling quantitative measurement of motion phases, and several baseline classifiers are chosen for comparison to validate the robustness of our phase segmentation method. We also investigate the sensor combination selection issue during the phase segmentation process to determine the optimal sensor configuration. Our approach provides a scientific solution for the integration of wearable sensors and competitive sports, contributing to the high-quality development of the next generation of smart sports.
Keywords
Body sensor network (BSN), competitive swimming, motion capture, motion capture, multisensor data fusion, multisensor data fusion, phase segmentation, phase segmentation, phase segmentation
Divisions
ai
Funders
National Natural Science Foundation of China (NSFC) (62203150) ; (62276090),National Key Research & Development Program of China (2022YFC2405600),Jiangsu Key Research and Development Plan (BE2022160),Frontier-Leading Technology Basic Research Special Project in Jiangsu Province (BK20192004),International (Regional) Cooperation Projects in Jiangsu Province (BZ2024061),Changzhou SciTech Program (CJ20220051)
Publication Title
IEEE Internet of Things Journal
Volume
12
Issue
4
Publisher
IEEE-Inst Electrical Electronics Engineers Inc
Publisher Location
445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA