Abstract
Archery is one of these sports in which the athletes repeat the same body postures over and over again. This means that tiny wrong habits could cause serious long-term health injuries. Consequently, learning a correct shooting technique is very important for both beginner archers and elite athletes. In this work, we present a system that uses machine learning to automatically detect anomalous postures and return to the archer a shooting score, that works by giving the archer a feedback on his own body configuration. We use a neural network to analyze images of archers during the firing and return the place of their different body joints. With this information, the system can detect wrong postures which might lead to injuries. This feedback is very important to the archer when learning the shooting technique. In addition, the system is not intrusive for the archer, so she/he can fire arrows freely. Preliminary results show the usefulness of the system, which is able to detect 4 spine misalignment and 4 raised elbow analyzing only 9 shots.
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Notes
- 1.
World Archery website: https://worldarchery.org/.
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Acknowledgements
This research has been partially funded by the Spanish MINECO and FEDER projects TIN2017-88213-R, UMA18-FEDERJA-003. University of Malaga project E3/03/19, and Andalucia TECH. C. Cintrano is supported by a FPI grant (BES-2015-074805) from Spanish MINECO. J. Ferrer thanks University of Malaga for his postdoc fellowship.
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Cintrano, C., Ferrer, J., Alba, E. (2020). Intelligent System for the Reduction of Injuries in Archery. In: Dorronsoro, B., Ruiz, P., de la Torre, J., Urda, D., Talbi, EG. (eds) Optimization and Learning. OLA 2020. Communications in Computer and Information Science, vol 1173. Springer, Cham. https://doi.org/10.1007/978-3-030-41913-4_11
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