Internally funded project
Start date : 01.01.2015
Digitalization of sports is also taking place in table tennis. This is caused by body-worn Wearables. This project captures, analyzes and processes the motion and movement of players, ball characteristics and other interesting parameters during table tennis games and exercises. In contrast to common standard camera-based analysis within predefined laboratory environments used for most ball sports, only sensors mounted on the racket are included. All necessary electronics should ideally be hidden inside the racket, that the user does not feel affected. For motion analysis, mainly inertial sensors (accelerometers and gyroscopes) are used, as well as magnetometers for the absolute alignment in space and specific piezoelectric sensors for vibration detection. First, the acceleration, the angular velocity and absolute orientation of the racket are measured to classify the stroke type using pattern recognition algorithms. It is possible to differentiate between forehand and backhand stroke types and various spin types. In addition, the ball impact event is verified by the vibration sensors. Afterwards, the resulting ball speed and spin are estimated shortly after this impact. Finally, the point of impact on the racket is localized by triangulation methods, similar to epicenter localization during earthquakes. All data is calculated on the embedded microcontroller and transferred to a mobile device, such as an Android smartphone via Bluetooth. There, the data is provided to the player as feedback for training support or statistics.
Digitalization of sports is also taking place in table tennis. This is caused by body-worn Wearables. This project captures, analyzes and processes the motion and movement of players, ball characteristics and other interesting parameters during table tennis games and exercises. In contrast to common standard camera-based analysis within predefined laboratory environments used for most ball sports, only sensors mounted on the racket are included. All necessary electronics should ideally be hidden inside the racket, that the user does not feel affected. For motion analysis, mainly inertial sensors (accelerometers and gyroscopes) are used, as well as magnetometers for the absolute alignment in space and specific piezoelectric sensors for vibration detection. First, the acceleration, the angular velocity and absolute orientation of the racket are measured to classify the stroke type using pattern recognition algorithms. It is possible to differentiate between forehand and backhand stroke types and various spin types. In addition, the ball impact event is verified by the vibration sensors. Afterwards, the resulting ball speed and spin are estimated shortly after this impact. Finally, the point of impact on the racket is localized by triangulation methods, similar to epicenter localization during earthquakes. All data is calculated on the embedded microcontroller and transferred to a mobile device, such as an Android smartphone via Bluetooth. There, the data is provided to the player as feedback for training support or statistics.