Background Alpine ski racing is a popular international winter sport that is complex and challenging from physical, technical, and tactical perspectives. Despite the vast amount of scientific literature focusing on this sport, including topical reviews on physiology, ski-snow friction, and injuries, no review has yet addressed the biomechanics of elite alpine ski racers and which factors influence performance. In World Cup events, winning margins are often mere fractions of a second and biomechanics may well be a determining factor in podium place finishes. Objective The aim of this paper was to systematically review the scientific literature to identify the biomechanical factors that influence the performance of elite alpine ski racers, with an emphasis on slalom, giant slalom, super-G, and downhill events. Methods Four electronic databases were searched using relevant medical subject headings and key words, with an additional manual search of reference lists, relevant journals, and key authors in the field. Articles were included if they addressed human biomechanics, elite alpine skiing, and performance. Only original research articles published in peer-reviewed journals and in the English language were reviewed. Articles that focused on skiing disciplines other than the four of primary interest were excluded (e.g., mogul, ski-cross and freestyle skiing). The articles subsequently included for review were quality assessed using a modified version of a validated quality assessment checklist. Data on the study population, design, location, and findings relating biomechanics to performance in alpine ski racers were extracted from each article using a standard data extraction form. Results A total of 12 articles met the inclusion criteria, were reviewed, and scored an average of 69-+13 % (range 40-89 %) upon quality assessment. Five of the studies focusedon giant slalom, four on slalom, and three on downhill disciplines, although these latter three articles were also relevant to super-G events. Investigations on speed skiing (i.e., downhill and super-G) primarily examined the effect of aerodynamic drag on performance, whereas the others examined turn characteristics, energetic principles, technical and tactical skills, and individual traits of high-performing skiers. The range of biomechanical factors reported to influence performance included energy dissipation and conservation, aerodynamic drag and frictional forces, ground reaction force, turn radius, and trajectory of the skis and/or centre of mass. The biomechanical differences between turn techniques, interdependency ofturns, and abilities of individuals were also identified as influential factors in skiing performance. In the case of slalom and giant slalom events, performance could be enhanced by steering the skis in such a manner to reduce the ski-snow friction and thereby energy dissipated. This was accomplished by earlier initiation of turns, longer path length and trajectory, earlier and smoother application of ground reaction forces, and carving (rather than skidding). During speed skiing, minimizing the exposed frontal area and positioning the arms close to the body were shown to reduce the energy loss due to aerodynamic drag and thereby decrease run times. In actual races, a consistently good performance (i.e., fast time) on different sections of the course, terrains, and snow conditions was a characteristic feature of winners during technical events because these skiers could maximize gains from their individual strengths and minimize losses from their respective weaknesses. Limitations Most of the articles reviewed were limited to investigating a relatively small sample size, which is a usual limitation in research on elite athletes. Of further concern was the low number of females studied, representing less than 4 % of all the subjects examined in the articles reviewed. In addition, although overall run time is the ultimate measure of performance in alpine ski
COBISS.SI-ID: 4450481
This investigation was designed to (a) develop an individualized mechanical model for measuring aerodynamic drag (Fd) while ski racing through multiple gates, (b) estimate energy dissipation (Ed) caused by Fd and compare this to the total energy loss (Et), and (c) investigate the relative contribution of Ed/Et to performance during giant slalom skiing (GS). Nine elite skiers were monitored in different positions and with different wind velocities in a wind tunnel, as well as during GS and straight downhill skiing employing a Global Navigation Satellite System. On the basis of the wind tunnel measurements, a linear regression model of drag coefficient multiplied by cross-sectional areaas a function of shoulder height was established for each skier (r)0.94,all P(0.001). Skiing velocity, Fd, Et, and Ed per GS turn were 15-21m/s, 20-60N, -11 to -5kJ, and -2.3 to -0.5kJ, respectively. Ed/Et ranged from ~5% to 28% and the relationship between Et/vin and Ed was r=-0.12 (all NS). In conclusion, (a) Fd during alpine skiing was calculated by mechanical modeling, (b) Ed made a relatively small contribution to Et, and(c) higher relative Ed was correlated to better performance in elite GS skiers, suggesting that reducing ski-snow friction can improve this performance.
COBISS.SI-ID: 4296113
High precision Global Navigation Satellite System (GNSS) measurements are becoming more and more popular in alpine skiing due to the relatively undemanding setup and excellent performance. However, GNSS provides only single-point measurements that are defined with the antenna placed typically behind the skier’s neck. A key issue is how to estimate other more relevant parameters of the skier’s body, like the center of mass (COM) and ski trajectories. Previously, these parameters were estimated by modeling the skier’s body with an inverted-pendulum model that oversimplified the skier’s body. In this study, we propose two machine learning methods that overcome this shortcoming and estimate COM and skis trajectories based on a more faithful approximation of the skier’s body with nine degrees-of-freedom. The first method utilizes a well-established approach of artificial neural networks, while the second method is based on a state-of-the-art statistical generalization method. Both methods were evaluated using the reference measurements obtained on a typical giant slalom course and compared with the inverted-pendulum method. Our results outperform the results of commonly used inverted-pendulum methods and demonstrate the applicability of machine learning techniques in biomechanical measurements of alpine skiing.
COBISS.SI-ID: 28015143
Time is a primary classification parameter in alpine skiing competitions. In this study a measuring procedure and methodology were developed how to accurately retrieve gate-to-gate times using a high-end navigation system (GNSS). This allows a direct insight into intercourse or gate-to-gate time difference. This knowledge was directly used in the project while determining the turn phases.
COBISS.SI-ID: 4109745
The aim of this study was to determine how an additional load influences the force-vs-time relationship of the countermovement vertical jump (CMVJ) , which have a similar eccentric concentric action as found in alpine skiing.. The participants were asked to perform a CMVJ without and with additional loads of 10%, 20%, and 30% of their body weight (BW). The vertical component of the ground reaction force (GRF) was used to calculate the durations of the preparatory, braking, and acceleration phases, the total duration of the jump, force impulses during the braking and acceleration phases, average forces during the braking and acceleration phases, and the maximum force of impact at landing. Increasing the additional load prolonged both the braking and acceleration phases of the jump. The magnitude of the force systematically and significantly increased with the additional load. The force impulse during the acceleration phase did not differ significantly between jumps performed with loads of 20% and 30% BW. The results suggest that the optimal additional load for developing explosive strength in vertical jumping ranges from 20% to 30% of BW, with this value varying between individual subjects.
COBISS.SI-ID: 4404913