A mobile system for real-time golf putt analysis and augmented feedback is of high interest for technique training and research. Recently, instrumented golf clubs comprising inertial measurement units were introduced as a suitable modality for mobile putt analysis. The high level of sensor integration and its mobile nature enable the unobtrusive and mobile collection of a high amount of data. We developed such a mobile analysis system with feedback capabilities using off-the-shelf components with a removable sensor. The main features are an automatic putt detection with machine learning methods and the real-time parameter calculation in the club coordinate system. In a validation study, the system detected more than 83 % of the putts for 8 out of 11 subjects while maintaining a false-positive rate of 2.4 %. Thus, it is a suitable tool to analyze putting strokes in real time and enables feedback intervention applications. As an application example for research, the collected kinematic data of eight players (1,946 putts) were used to analyze training progress. Compared to the common analysis of expert and novice differences, the presented results provide a first insight in the motor learning path of inexperienced golfers. In principle, the presented system can be used to realize mobile data analysis systems for various sports disciplines beyond golf putting. It furthermore provides an innovative tool to analyze motor learning processes in more detail.
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