2020
Cintrano, Christian; Ferrer, Javier; Alba, Enrique
Intelligent system for the reduction of injuries in archery Inproceedings
In: Communications in Computer and Information Science, pp. 128–137, 2020, ISSN: 18650937.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Body posture analysis, Improved sports performance, Injury reduction, Machine learning
@inproceedings{Cintrano2020,
title = {Intelligent system for the reduction of injuries in archery},
author = {Christian Cintrano and Javier Ferrer and Enrique Alba},
doi = {10.1007/978-3-030-41913-4_11},
issn = {18650937},
year = {2020},
date = {2020-01-01},
booktitle = {Communications in Computer and Information Science},
volume = {1173 CCIS},
pages = {128--137},
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.},
keywords = {Artificial intelligence, Body posture analysis, Improved sports performance, Injury reduction, Machine learning},
pubstate = {published},
tppubtype = {inproceedings}
}
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.