Alpine Ski Motion Characteristics in Slalom

Reid, Robert C.; Haugen, Per; Gilgien, Matthias; Kipp, Ronald W.; Smith, Gerald A.

doi:10.3389/fspor.2020.00025

Cited by 28 publications

(44 citation statements)

References 35 publications

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“…In Super-G, athletes are likely able carve the turn to larger extent and use less pivoting or skidding than in GS. This is supported by the finding that skidding in downhill and slalom causes a massive increase in ski-snow friction compared to carving 15,21,26 .…”

Section: Tablementioning

confidence: 70%

Injury prevention in Super-G alpine ski racing through course design

Gilgien

Crivelli²,

Kröll

et al. 2021

Sci Rep

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In Super-G alpine ski racing mean speed is nearly as high as in Downhill. Hence, the energy dissipated in typical impact accidents is similar. However, unlike Downhill, on Super-G courses no training runs are performed. Accordingly, speed control through course design is a challenging but important task to ensure safety in Super-G. In four male World Cup alpine Super-G races, terrain shape, course setting and the mechanics of a high-level athlete skiing the course were measured with differential global navigation satellite systems (dGNSS). The effects of course setting on skier mechanics were analysed using a linear mixed effects model. To reduce speed by 0.5 m/s throughout a turn, the gate offset needs to be increased by + 51%. This change simultaneously leads to a decrease in minimal turn radius (− 19%), an increase in impulse (+ 27%) and an increase in maximal ground reaction force (+ 6%). In contrast, the same reduction in speed can also be achieved by a − 13% change in vertical gate distance, which also leads to a small reduction in minimal turn radius (− 4%) impulse (− 2%), and no change in maximal ground reaction force; i.e. fewer adverse side effects in terms of safety. It appears that shortening the vertical gate distance is a better and safer way to reduce speed in Super-G than increasing the gate offset.

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Section: Tablementioning

confidence: 70%

Injury prevention in Super-G alpine ski racing through course design

Gilgien

Crivelli²,

Kröll

et al. 2021

Sci Rep

Self Cite

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“…With the development of shaped skis in the late 1990s, performing carved turns has become possible. A carved turn is defined by minimal or no lateral ski displacement relative to the track, and therefore, each point along the ski edge follows the path of the proceeding one [ 1 , 2 , 3 , 4 ]. In contrast, during a skidding turn, a point along the edge does not follow the path of the proceeding one but slides sideways along the slope [ 1 , 2 , 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

“…A carved turn is defined by minimal or no lateral ski displacement relative to the track, and therefore, each point along the ski edge follows the path of the proceeding one [ 1 , 2 , 3 , 4 ]. In contrast, during a skidding turn, a point along the edge does not follow the path of the proceeding one but slides sideways along the slope [ 1 , 2 , 3 , 4 ]. Skidded and carved turns differ not only in terms of ski trajectory but also regarding ski deflection.…”

Section: Introductionmentioning

confidence: 99%

A Novel Sensor Foil to Measure Ski Deflections: Development and Validation of a Curvature Model

Thorwartl

Kröll

Tschepp

et al. 2021

Sensors

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The ski deflection with the associated temporal and segmental curvature variation can be considered as a performance-relevant factor in alpine skiing. Although some work on recording ski deflection is available, the segmental curvature among the ski and temporal aspects have not yet been made an object of observation. Therefore, the goal of this study was to develop a novel ski demonstrator and to conceptualize and validate an empirical curvature model. Twenty-four PyzoFlex® technology-based sensor foils were attached to the upper surface of an alpine ski. A self-developed instrument simultaneously measuring sixteen sensors was used as a data acquisition device. After calibration with a standardized bending test, using an empirical curvature model, the sensors were applied to analyze the segmental curvature characteristic (m−1) of the ski in a quasi-static bending situation at five different load levels between 100 N and 230 N. The derived curvature data were compared with values obtained from a high-precision laser measurement system. For the reliability assessment, successive pairs of trials were evaluated at different load levels by calculating the change in mean (CIM), the coefficient of variation (CV) and the intraclass correlation coefficient (ICC 3.1) with a 95% confidence interval. A high reliability of CIM −1.41–0.50%, max CV 1.45%, and ICC 3.1 > 0.961 was found for the different load levels. Additionally, the criterion validity based on the Pearson correlation coefficient was R2 = 0.993 and the limits of agreement, expressed by the accuracy (systematic bias) and the precision (SD), was between +9.45 × 10−3 m−1 and −6.78 × 10−3 m−1 for all load levels. The new measuring system offers both good accuracy (1.33 × 10−3 m−1) and high precision (4.14 × 10−3 m−1). However, the results are based on quasi-static ski deformations, which means that a transfer into the field is only allowed to a limited extent since the scope of the curvature model has not yet been definitely determined. The high laboratory-related reliability and validity of our novel ski prototype featuring PyzoFlex® technology make it a potential candidate for on-snow application such as smart skiing equipment.

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“…Finally, carving refers to the parallel technique in which the ski’s tip creates a groove in the snow which is followed by the rest of the ski, resulting in a self-steering effect [ 9 ]. Carving is the more dynamic of the two parallel styles and, generally, this technique used by competitive skiers during racing [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Classification of Alpine Skiing Styles Using GNSS and Inertial Measurement Units

Neuwirth¹,

Snyder

Kremser³

et al. 2020

Sensors

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In alpine skiing, four commonly used turning styles are snowplow, snowplow-steering, drifting and carving. They differ significantly in speed, directional control and difficulty to execute. While they are visually distinguishable, data-driven classification is underexplored. The aim of this work is to classify alpine skiing styles based on a global navigation satellite system (GNSS) and inertial measurement units (IMU). Data of 2000 turns of 20 advanced or expert skiers were collected with two IMU sensors on the upper cuff of each ski boot and a mobile phone with GNSS. After feature extraction and feature selection, turn style classification was applied separately for parallel (drifted or carved) and non-parallel (snowplow or snowplow-steering) turns. The most important features for style classification were identified via recursive feature elimination. Three different classification methods were then tested and compared: Decision trees, random forests and gradient boosted decision trees. Classification accuracies were lowest for the decision tree and similar for the random forests and gradient boosted classification trees, which both achieved accuracies of more than 93% in the parallel classification task and 88% in the non-parallel case. While the accuracy might be improved by considering slope and weather conditions, these first results suggest that IMU data can classify alpine skiing styles reasonably well.

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Alpine Ski Motion Characteristics in Slalom

Cited by 28 publications

References 35 publications

Injury prevention in Super-G alpine ski racing through course design

Injury prevention in Super-G alpine ski racing through course design

A Novel Sensor Foil to Measure Ski Deflections: Development and Validation of a Curvature Model

Classification of Alpine Skiing Styles Using GNSS and Inertial Measurement Units

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