Abstract
A thorough analysis of sports is becoming increasingly important during the training process of badminton players at both the recreational and professional level. Nowadays, game situations are usually filmed and reviewed afterwards in order to analyze the game situation, but these video set-ups tend to be difficult to analyze, expensive, and intrusive to set up. In contrast, we classified badminton movements using off-the-shelf accelerometer and gyroscope data. To this end, we organized a data capturing campaign and designed a novel neural network using different frame sizes as input. This paper shows that with only accelerometer data, our novel convolutional neural network is able to distinguish nine activities with 86% precision when using a sampling frequency of 50 Hz. Adding the gyroscope data causes an increase of up to 99% precision, as compared to, respectively, 79% and 88% when using a traditional convolutional neural network. In addition, our paper analyses the impact of different sensor placement options and discusses the impact of different sampling frequenciess of the sensors. As such, our approach provides a low cost solution that is easy to use and can collect useful information for the analysis of a badminton game.
Highlights
Badminton is an Olympic discipline and it is one of the most popular racket sports worldwide.Both at the recreational and professional level, an analysis of the movements can be of great added value during the training process [1]
We have demonstrated that accurate fine-grained activity recognition of typical badminton strokes can be performed while using off-the-shelf sensors
Accurate estimations can be made with a simple Convolutional Neural Network after fine-tuning the parameters
Summary
Badminton is an Olympic discipline and it is one of the most popular racket sports worldwide. Both at the recreational and professional level, an analysis of the movements can be of great added value during the training process [1]. Technologies that can help to optimize training are constantly being sought in order to improve the personal performance of badminton players. This includes determining the movements of the player during training and game situations. Badminton is a sport in which tactics, technique, and the precise execution of the movements are of great importance. Players and coaches are interested in affordable and compact sensor hardware that have the ability to capture the necessary measurements to obtain relevant, useful information
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