Title: Classifying muscle performance of junior endurance and power athletes using machine learning

Authors: Maisarah Sulaiman; Aizreena Azaman; Noor Aimie Salleh; Muhammad Amir As'ari; Izwyn Zulkapri

Addresses: Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia ' Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia ' Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia ' Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia ' Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia

Abstract: This paper aimed to characterise the muscle performance of endurance and power athletes using machine learning approach. In this regard, electromyography (EMG) features were extracted from the vastus lateralis muscle and used to feed the support vector machine (SVM) classifier. The performance of various EMG features was evaluated based on their classification accuracy, sensitivity, specificity, and F-score. The accuracy was the highest for the feature set selected using the feature selection approach compared to the single feature. Specifically, the performance of sequential backward selection (SBS) was superior to the sequential forward selection (SFS) approach. Meanwhile, based on the SVM classification result, the radial basis function (RBF) kernel performed better than the other investigated kernel types, such as linear, polynomial, and sigmoid kernel. This muscle characterisation of endurance and power athletes may be useful as a muscle-monitoring tool for future talent identification and talent development, particularly in young athletes.

Keywords: electromyography; EMG; muscle; athlete; endurance; power; distance runner; sprinter; classification; machine learning; support vector machine; SVM.

DOI: 10.1504/IJBET.2024.140560

International Journal of Biomedical Engineering and Technology, 2024 Vol.45 No.4, pp.337 - 353

Received: 04 Jul 2023
Accepted: 03 Dec 2023
Published online: 23 Aug 2024 *

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