Abstract
In javelin throw, a discipline of athletics, the analysis and correction of throwing technique are essential components of training and competition and fundamentally contribute to the performance improvement of athletes. Motion analysis tools are sometimes used to support coaches, who may easily miss crucial details of the throwing movement due to high speeds. Existing tools for this purpose require a complex and location-bound experimental setup and do not operate in real-time due to their complexity. For this reason, they are often not practical in the context of training and competition. This paper presents a mobile system for real-time analysis and assessment of javelin throws utilizing body-worn sensors. The aim is to offer athletes and coaches a simple and location-independent method of evaluating relevant movement sequences in real-time. The system is based on key throwing movement parameters determined in collaboration with athletic coaches. It consists of four body-worn sensors at specific locations connected to a mobile device using Bluetooth Low Energy. The analysis of a throwing movement happens immediately after its completion on the mobile device and provides feedback on potential execution errors. The developed system is evaluated in a study of 28 participants divided into four performance classes and three different recording conditions. During each recording session, a professional coach was present to assess the accuracy of generated feedback. Our results suggest that the developed system provides helpful feedback on the javelin throw movement for all performance classes except beginners, in some cases even surpassing the accuracy of licensed coaches.
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Acknowledgments
This research has been investigated by the Serious Games research group at TU Darmstadt and was partially funded by the German Federal Ministry of Education and Research under the research for civil security program (Grant Number 13N15547).
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Müller, P.N., Fenn, S., Göbel, S. (2023). Javelin Throw Analysis and Assessment with Body-Worn Sensors. In: Haahr, M., Rojas-Salazar, A., Göbel, S. (eds) Serious Games. JCSG 2023. Lecture Notes in Computer Science, vol 14309. Springer, Cham. https://doi.org/10.1007/978-3-031-44751-8_3
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