Ski Position during the Flight and Landing Preparation Phases in Ski Jumping Detected with Inertial Sensors

Optimisation of stable flight posture of ski jumping based on computational fluid dynamics simulation technology

The stable flight posture that affects sports performance during flight is usually formed by the multiple angles of the athlete-ski posture. At present, research on the flight phase is mainly based on the single-factor impact analysis based on computational fluid dynamics simulation technology, but studies on the multi-factor coupling relationship of two or more factors is less. This study aims to determine the best optimal-level combination based on the simulation model of this work through comprehensive evaluation from the optimisation perspective of multi-factor coupling. Here, a refined model of the athlete-ski system with the characteristics of ski jumping was established. Reynolds time-averaged method was used for the simulation. A three-factor and five-level simulation test was conducted on the relative inclination between skis, the angle between the body and the ski and the ski V-angle through orthogonal experiment design. Our results show that the optimal-level combination of the relative inclination between skis of 120°, the angle between the body and the ski of 20°, and the ski V-angle of 30° is relatively best in terms of aerodynamic characteristics. Simulation results were similar to the results of the winter field data from video analysis, and the results were effective.

Pose estimation and motion analysis of ski jumpers based on ECA-HRNet

Ski jumping is a high-speed sport, which makes it difficult to accurately analyze the technical motion in a subjective way. To solve this problem, we propose an image-based pose estimation method for analyzing the motion of ski jumpers. First, an image keypoint dataset of ski jumpers (KDSJ) was constructed. Next, in order to improve the precision of ski jumper pose estimation, an efficient channel attention (ECA) module was embedded in the residual structures of a high-resolution network (HRNet) to fuse more useful feature information. At the training stage, we used a transfer learning method which involved pre-training on the Common Objection in Context (COCO2017) to obtain feature knowledge from the COCO2017 for using in the task of ski jumper pose estimation. Finally, the detected keypoints of the ski jumpers were used to analyze the motion characteristics, using hip and knee angles over time (frames) as an example. Our experimental results showed that the proposed ECA-HRNet achieved the average precision of 73.4% on the COCO2017 test-dev set and the average precision of 86.4% on the KDSJ test set using the ground truth bounding boxes. These research results can provide guidance for auxiliary training and motion evaluation of ski jumpers.

Key transition technology of ski jumping based on inertial motion unit, kinematics and dynamics

BACKGROUND

The development and innovation of biomechanical measurement methods provide a solution to the problems in ski jumping research. At present, research on ski jumping mostly focuses on the local technical characteristics of different phases, but studies on the technology transition process are less.

OBJECTIVES

This study aims to evaluate a measurement system (i.e. the merging of 2D video recording, inertial measurement unit and wireless pressure insole) that can capture a wide range of sport performance and focus on the key transition technical characteristics.

METHODS

The application validity of the Xsens motion capture system in ski jumping was verified under field conditions by comparing the lower limb joint angles of eight professional ski jumpers during the takeoff phase collected by different motion capture systems (Xsens and Simi high-speed camera). Subsequently, the key transition technical characteristics of eight ski jumpers were captured on the basis of the aforementioned measurement system.

RESULTS

Validation results indicated that the joint angle point-by-point curve during the takeoff phase was highly correlated and had excellent agreement (0.966 ≤ r ≤ 0.998, P < 0.001). Joint root-mean-square error (RMSE) differences between model calculations were 5.967° for hip, 6.856° for knee and 4.009° for ankle.

CONCLUSIONS

Compared with 2D video recording, the Xsens system shows excellent agreement to ski jumping. Furthermore, the established measurement system can effectively capture the key transition technical characteristics of athletes, particularly in the dynamic changes of straight turn into arc in inrun, the adjustment of body posture and ski movement during early flight and landing preparation.

Developing a method for quantifying hip joint angles and moments during walking using neural networks and wearables

Quantifying hip angles/moments during gait is critical for improving hip pathology diagnostic and treatment methods. Recent work has validated approaches combining wearables with artificial neural networks (ANNs) for cheaper, portable hip joint angle/moment computation. This study developed a Wearable-ANN approach for calculating hip joint angles/moments during walking in the sagittal/frontal planes with data from 17 healthy subjects, leveraging one shin-mounted inertial measurement unit (IMU) and a force-measuring insole for data capture. Compared to the benchmark approach, a two hidden layer ANN (n = 5 nodes per layer) achieved an average rRMSE = 15% and R²=0.85 across outputs, subjects and training rounds.

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

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.

The Use of Wearable Sensor Technology to Detect Shock Impacts in Sports and Occupational Settings: A Scoping Review

Shock impacts during activity may cause damage to the joints, muscles, bones, or inner organs. To define thresholds for tolerable impacts, there is a need for methods that can accurately monitor shock impacts in real-life settings. Therefore, the main aim of this scoping review was to present an overview of existing methods for assessments of shock impacts using wearable sensor technology within two domains: sports and occupational settings. Online databases were used to identify papers published in 2010-2020, from which we selected 34 papers that used wearable sensor technology to measure shock impacts. No studies were found on occupational settings. For the sports domain, accelerometry was the dominant type of wearable sensor technology utilized, interpreting peak acceleration as a proxy for impact. Of the included studies, 28 assessed foot strike in running, head impacts in invasion and team sports, or different forms of jump landings or plyometric movements. The included studies revealed a lack of consensus regarding sensor placement and interpretation of the results. Furthermore, the identified high proportion of validation studies support previous concerns that wearable sensors at present are inadequate as a stand-alone method for valid and accurate data on shock impacts in the field.