IMMU-based Orientation Determination in Sports Analytics

Sports analytics research has major impact on the development of innovative training methods and the broadcast of sports events. This dissertation provides algorithms for both kinematic analysis and performance interpretation based on unobtrusively obtained measurements from wearable sensors. Its main focus is set on the processing of 3D-orientation features and the exploration of their potential for sports analytics. The proposed algorithms are described and evaluated in five exemplary sports. In scuba diving, rowing and ski jumping, the 3D-orientation of the body/boat/skis is determined and further processed to analyze and visualize the motion behavior. In snowboarding and skateboarding, the board orientation is calculated and processed for motion visualization and machine learning. Board sport tricks are automatically detected and subsequently classified for trick category and type. The methods of this work were already partially applied for TV broadcast of international competitions (e.g., Olympics 2018). Additionally, they can support sports science research for establishing thorough investigations and innovative training methods.