In elite sports real-time feedback of biomechanical parameters is indispensable to achieve performance enhancement. Wearables including embedded data analysis are a suitable tool for online monitoring of movement parameters and might enhance the quality of training significantly. However, due to limited compute capacities for complex data processing on the sensor device itself, analysis can typically only be done afterwards using high-performance tools. This lack of immediate feedback may lead to slower training progress. We present a flexible, wearable system for the analysis of different sports movement including online-monitoring. It includes a modular, platform-based framework with a sensor node, an embedded software stack, Bluetooth Low Energy communication and an Android application. Data is analyzed on the sensor itself via embedded real-time algorithms. Results indicate that the device provides reliable and accurate measurements of movement parameters. In combination with adaptable algorithms and the BLE transmission, it offers solutions for real-time monitoring of athletic performance.
Schmidt, M., Wille, S., Rheinländer, C., Wehn, N., & Jaitner, T. (2018). A wearable flexible sensor network platform for the analysis of different sport movements. In Advances in Intelligent Systems and Computing (Vol. 608, pp. 3–14). Springer Verlag. https://doi.org/10.1007/978-3-319-60639-2_1