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10:20   Motion analysis in wintersports Chair: Akihiro Matsuda 10:20 20 mins GETTING THE ANGLES STRAIGHT IN SPEED SKATING: A VALIDATION STUDY ON AN IMU FILTER DESIGN TO MEASURE THE LEAN ANGLE OF THE SKATE ON THE STRAIGHTS. Eline van der Kruk, Arend Schwab, Frans van der Helm, Dirkjan Veeger Abstract: To assist speed skaters in improving their skating performance, we would like to provide them with real time feedback on the orientation of the skate within a single stroke. While of course the forces generated by the skater on the ice determine the acceleration of the skater, the orientation of the skate determines in which direction this force, and thus acceleration, is headed. In this study we focus on the validation of the lean angle measurements of the skate, which distributes the push-off forces over the global vertical and transverse component. To measure this angle, an inertial measurement unit (IMU) would be a logical choice, but two aspects render measuring with commercially available IMUs and their filters on an ice rink rather difficult, first the ferromagnetic materials in the vicinity of the IMU and secondly the large linear accelerations. In this paper we therefore propose filters that bypass these problems. In total three complementary filters with adaptive gain were validated with a motion capture system. The filter based on the assumption that the lean angle can be reset to zero (upright) when there is no change in steer angle of the skate, showed the most accurate results (mean RMSE error of 5.30 and 3.60, for the left and right skate respectively). Integrated into the filter is an IMU based stroke detection, which as a stand-alone system could provide feedback on stroke frequency, stroke length, contact time or double stance phase time. It is concluded that an IMU used with this filter can provide individual elite speed skaters reliable feedback on their skate lean angle. 10:40 20 mins COMPARISON OF IMU MEASUREMENTS OF CURLING STONE DYNAMICS WITH A NEW NUMERICAL MODEL Edward Lozowski, Sean Maw, Bernard Kleiner, Krzysztof Szilder, Mark Shegelski, Dana Ferguson, Petr Musilek Abstract: Despite almost a century of research, the question of what causes a curling stone to curl (move perpendicular to its initial direction of motion) has no complete answer. Many hypotheses have been formulated, but none have been able to account quantitatively for the full magnitude of the observed curl. The objective of this research was to equip a curling stone with an inertial measurement unit (IMU) and measure its motion, in order to validate a new numerical model of curling stone dynamics (Lozowski et al., 2015). Low cost, small size, ease of programming and operation, wireless data communication and a data sampling rate near 1 kHz were important selection criteria and constraints for the instrument package. We chose the MicroStrain 3DM-GX4-25 System (MSS). MSS is a MEMS-based IMU with a triaxial gyroscope and a triaxial linear accelerometer. It was mounted and interfaced with a Bluetooth transmitter, on a curling stone handle. The data were streamed to a host laptop and displayed graphically in real time. Post-processing of the data included filtering and time-integration, in order to obtain linear and angular velocities and displacements. The instrumented stone was deployed for testing at the University of Alberta Saville Centre. Fifty throws were recorded, covering a range of initial linear and angular speeds. There was no sweeping. Initial results indicate some unexpected dynamic behaviour. In one case, angular velocity decreased linearly with time over the entire trajectory, except for the final few tenths of a second, when the stone’s rotation suddenly stopped. Longitudinal (down-ice) velocity exhibited analogous behaviour. The transverse (across-ice) velocity was initially small and then suddenly increased to about 10 cms-1. This was followed by a return to zero, at first slowly and then rapidly. We have compared our experimental results with trajectory data calculated using a new numerical model, based on a thermodynamic approach to ice friction. While the observed longitudinal and angular motions are captured reasonably well by the model, the observed lateral motion is not. We explore possible reasons for this discrepancy. We also speculate that the unique dynamics of a curling stone may arise from two distinct frictional mechanisms, one of which is intermittent. Lozowski, E.P., Szilder, K., Maw, S., Morris, A., Poirier, L. and Kleiner, B., 2015: Towards a first principles model of curling ice friction and curling stone dynamics. Proceedings 25th International Ocean and Polar Engineering Conference, Kona, Hawaii, June 21-26, 1730-1738. 11:00 20 mins DEVELOPMENT OF AN AUTOMATED MOTION EVALUATION SYSTEM FROM WEARABLE SENSOR DEVICES FOR SKI JUMPING Heike Brock, Yuji Ohgi, Kazuya Seo Abstract: Capturing human motion performances with wearable devices such as inertial measurement units constitutes the future of mobile sports analysis, but often requires sophisticated methods to extract relevant information out of the raw sensor data. In this work, we do not only use wearable sensors to analyze kinematic features and performance parameters, but develop a complete system for the automatic evaluation of ski jumps on the base of general machine learning principles. 27 inertial sensors have been used to capture the motion of 4 junior ski jumpers during the complete jump from the start of the inrun to the end of the outrun phase. Several capture sessions during summer jumping season led to a database with a total of 119 ski jumps which were equally separated into a training and a test database. We furthermore collected style points for all data takes from an experienced judge during the data acquisition under real judging conditions as ground truth and control data for the machine learning algorithms. By a combination of various processing methods to determine orientation of body segments, body joint positions and jump phases, kinematic factors that influence the performance and length of a jump are retrieved for all takes in the training database. They are then used as motion features in a next step for the learning of machine knowledge, and to automatically compute a score for the flight style of every single jump under consideration of the official scoring guidelines for ski jumping. In a last step, we compute the scores for every jump within the test database and compare the results to the ground truth style points. Results show that the computed scores largely correlate to the human-based judging scores and create a qualitative ranking for all performed jumps. We therefore assume that the system is robust enough to be applied in a mobile competition system in future, as it might be important for training and performance improvement or talent recruitment in the future and an important step towards better measurability and objectivity in performance-oriented sports independent of human judging.