Ben Van Herbruggen, Jaron Fontaine, Jonas Simoen, Lennert De Mey, Daniel Peralta, Adnan Shahid, Eli De Poorter
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引用次数: 0
Abstract
Badminton is a fast-paced sport that requires a high level of skill and coordination. To improve their skills, players can use activity trackers to monitor different shots and activities. These trackers utilize inertial measurement units (IMUs), which measures acceleration and angular velocity on the rackets, and the ultra-wideband (UWB) sensors, which measure the location of the player. This study first analyzes the use of UWB localization for tracking badminton players on the court and analyzes the location where shots are played. Furthermore, this study focuses on using both IMU at the racket and wrist and UWB sensors to recognize strategies utilized in badminton matches, employing convolutional neural network (CNN) and Long-Short-Term Memory (LSTM) models. The goal is to classify thirteen badminton shots, as well as an extra class that contains non-shot activities. The output of this shot classifier is provided to the strategy recognition model, which can identify four main strategies, with eleven variations in total, alongside an additional class designated for non-strategy instances such as movement or rest intervals. We trained and tested the models on data from six skilled badminton players. The best results were achieved by using both IMU and UWB data. The proposed 2D-CNN achieved a shot classification accuracy of 90.9%, while the proposed LSTM achieved a strategy recognition accuracy of 80%. The results of this study suggest that neural networks can be used to effectively classify badminton shots and strategies to improve the training of badminton players, as well as to analyze match data.
期刊介绍:
Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT.
The journal will place a high priority on timely publication, and provide a home for high quality.
Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.