Principal components analysis for the identification of sensitive variables in the execution of the motor gesture and the development of an artificial neural network as an auxiliary tool in the classification of sports performance in elite taekwondo athle
DOI:
https://doi.org/10.35366/112694Keywords:
taekwondo, motor gesture, sports classification, principal component analysis, artificial neural networkAbstract
Introduction: sports classification is a daily task in the athlete’s life. It is important to relate the results
of the tests performed on a taekwondoin with the efficiency of the execution of their fundamental motor
gesture, the kick, which represents 80% of the activity in competition. Objective: the aim is to have a
tool that allows to identify and classify the most sensitive variables (anthropometric and physiological)
and relate them to the sports efficiency of a sample of taekwondo athletes from Mexico City. Material
and methods: descriptive cross-sectional study for the analysis of 202 variables gathered from 74
evaluations towards the identification of those with the greatest variability, to stratify the population
using principal component analysis and to classify it into four levels of aptitude, using an artificial neural
network. Results: athletes characterization, identifying weaknesses and strengths, was performed
by the representation of more than 50% of the information contained in 19 parameters that are
obtained from the data to represent the study population and limit points with statistical significance.
Classification efficiency was 87.5%. Conclusion: the use of technology tools in the analysis of data
and classification based on artificial intelligence is a different proposal that seeks to emulate the work
done by coaches in the process of classifying athletes.
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Copyright (c) 2023 Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra
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© Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra under a Creative Commons Attribution 4.0 International (CC BY 4.0) license which allows to reproduce and modify the content if appropiate recognition to the original source is given.
