Experimental Validation of Real-Time Ski Jumping Tracking System Based on Wearable Sensors

Abstract

For sports scientists and coaches, its crucial to have reliable tracking systems to improve athletes. Therefore, this study aimed to examine the validity of a wearable real-time tracking system (WRRTS) for the quantification of ski jumping. The tracking system consists of wearable trackers attached to the ski bindings of the athletes and fixed antennas next to the jumping hill. To determine the accuracy and precision of the WRRTS, four athletes of the German A or B National Team performed 35 measured ski jumps. The WRRTS was used to measure the 3D positions and ski angles during the jump. The measurements are compared with camera measurements for the in-flight parameters and the official video distance for the jumping distance to assess their accuracy. We statistically evaluated the different methods using Bland–Altman plots. We thereby find a mean absolute error of 0.46 m for the jumping distance, 0.12 m for the in-flight positions, and 0.8°, and 3.4° for the camera projected pitch and V-style opening angle, respectively. We show the validity of the presented WRRTS to measure the investigated parameters. Thus, the system can be used as a tracking system during training and competitions for coaches and sports scientists. The real-time feature of the tracking system enables usage during live TV broadcasting.

xLength: Predicting Expected Ski Jump Length Shortly after Take-Off Using Deep Learning

“…The dataset covers a wide range of jump lengths and athletes, which leads to good prediction accuracy over jump lengths and generalization over athletes. Even though the dataset has the largest number of different ski jumping venues and athletes used in a tracking study [ 21 , 31 , 33 , 40 , 41 , 42 , 43 , 44 ], the number of venues is relatively small and unevenly distributed compared to the number of athletes. This could be improved in the future.…”

“…The jump length within our dataset, which is the regression goal, is determined with the WRTTS and not the manually labeled video distance as in official competitions. Nevertheless, in a previous study, we showed that the jump length determined by the WRTTS and the official video distance differ by [ 33 ].…”

“…The WRTTS combines an inertial measurement unit (IMU) with ultra-wideband positioning. Information about the working principle can be found in [ 31 , 32 , 33 ]. The accuracy of the tracking system has been validated in a previous study [ 33 ].…”

“…Information about the working principle can be found in [ 31 , 32 , 33 ]. The accuracy of the tracking system has been validated in a previous study [ 33 ].…”

Kinematic Determination of the Aerial Phase in Ski Jumping

“…Currently, researchers have used computational fluid dynamic simulations and wind tunnel measurements, and there have been a small number of studies using video analysis to examine how the glide posture can influence glide parameters, such as the aerodynamic relationship between the lift (F L ) and drag forces (F D ), i.e., LD-ratio [9,[13][14][15][16][17][18][19]. In recent years, wearable sensors as inertial measurement units (IMUs) have shown promising results when measuring kinematics and kinetics from the start of the inrun to the landing [20][21][22][23][24][25][26][27][28]. A suitable method used to provide accurate field data from the steady glide phase is differential global navigation satellite system (dGNSS) technology.…”