Applying Convolutional Neural Networks (CNNs): A Machine Learning Method in Modern Sports

This review paper aims to examine the applications of Convolutional Neural Network (CNN) in the field of sports biomechanics. CNN, which is a specific category of deep learning models, has exhibited considerable promise in the analysis of intricate data structures. As a result, they have become indispensable instruments in various domains. Machine learning has been utilized in the field of sports biomechanics to gain insights and improve athletic performance. CNN has been effectively employed in sports analytic studies, specifically in movement algorithm and sports video analysis. CNN has demonstrated its efficacy in the domain of sports rehabilitation, in terms of application and sensor-based sports injury rehabilitation. Notwithstanding these advancements, there remain gaps and prospects for additional research, particularly in the realm of integrating the various applications of CNN. This review aims to identify gaps in the existing literature and suggest potential areas for future research, specifically focusing on the application of CNN in the field of sports biomechanics.