Abstract
The rotational motion of a rowing boat during single strokes has significant impact on the boat velocity and overall rowing performance. However, a method for automatic in-stroke field quantification remains challenging. In this work, we propose a robust stroke segmentation algorithm in combination with a 3D-rotation estimation during segmented strokes. Our method is designed to process unobtrusively obtained inertial sensor data of one sensor device attached to rowing boats. A template-based matching algorithm is implemented to detect all strokes in the collected sensor data. The segmented strokes are then analyzed for the corresponding in-stroke rotation. The evaluation of the stroke segmentation was performed with professional race and amateur training data. The resulting precision was 99.8 % for professional and 97.2 % for amateur data. The in-stroke rotation angle calculation was validated with amateur training data of four boat classes. The results were compared to corresponding measurements from the literature.
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Acknowledgments
The authors would like to thank the rowing club Rudergesellschaft Ghibellinia Waiblingen for their participation in the data acquisition.
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Groh, B.H., Schottenhamml, J., Eskofier, B.M., Drory, A. (2020). Unobtrusive Estimation of In-Stroke Boat Rotation in Rowing Using Wearable Sensors. In: Lames, M., Danilov, A., Timme, E., Vassilevski, Y. (eds) Proceedings of the 12th International Symposium on Computer Science in Sport (IACSS 2019). IACSS 2019. Advances in Intelligent Systems and Computing, vol 1028. Springer, Cham. https://doi.org/10.1007/978-3-030-35048-2_14
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DOI: https://doi.org/10.1007/978-3-030-35048-2_14
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