A wearable system for the estimation of performance-related metrics during running and jumping tasks
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Published version
Date
2021-06-05
Authors
Tedesco, Salvatore
Alfieri, Davide
Perez-Valero, Eduardo
Komaris, Dimitrios-Sokratis
Jordan, Luke
Belcastro, Marco
Barton, John
Hennessy, Liam
O'Flynn, Brendan
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Published Version
Abstract
Athletic performance, technique assessment, and injury prevention are all important aspects in sports for both professional and amateur athletes. Wearable technology is attracting the research community’s interest because of its capability to provide real-time biofeedback to coaches and athletes when on the field and outside of more restrictive laboratory conditions. In this paper, a novel wearable motion sensor-based system has been designed and developed for athletic performance assessment during running and jumping tasks. The system consists of a number of components involving embedded systems (hardware and software), back-end analytics, information and communications technology (ICT) platforms, and a graphical user interface for data visualization by the coach. The system is able to provide automatic activity recognition, estimation of running and jumping metrics, as well as vertical ground reaction force (GRF) predictions, with sufficient accuracy to provide valuable information as regards training outcomes. The developed system is low-power, sufficiently small for real-world scenarios, easy to use, and achieves the specified communication range. The system’s high sampling rate, levels of accuracy and performance enables it as a performance evaluation tool able to support coaches and athletes in their real-world practice.
Description
Keywords
Accelerometer , GRF , Ground reaction force , IMU , Inertial measurement unit , Jumping , Performance , Running , Sport , Wearables
Citation
Tedesco, S., Alfieri, D., Perez-Valero, E., Komaris, D.-S., Jordan, L., Belcastro, M., Barton, J., Hennessy, L. and O’Flynn, B. (2021) 'A Wearable System for the Estimation of Performance-Related Metrics during Running and Jumping Tasks', Applied Sciences, 11(11), 5258 (23 pp). doi: 10.3390/app11115258