Performance Parameters in Competitive Alpine Skiing Disciplines of Slalom, Giant Slalom and Super-Giant Slalom

Alejo, Lidia B; Gil-Cabrera, Jaime; Montalvo-Pérez, Almudena; Barranco-Gil, David; Hortal-Fondón, Jaime; Navandar, Archit

doi:10.3390/ijerph18052628

Cited by 3 publications

(7 citation statements)

References 19 publications

(19 reference statements)

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“…In the segmentation of overlapping image [18,19], changes of the laser should be used to determine the number of overlapping images. All images are segmented into multiple modules along the direction of the initial image and establish the matrix H as…”

Section: Preprocessing Of Extracting the Starting Action Of Snowboardmentioning

confidence: 99%

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Feature Extraction Method of Snowboard Starting Action Using Vision Sensor Image Processing

Zhang

Li²,

Shin

et al. 2022

Mobile Information Systems

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There is a lot of noise in the snowboard starting action image, which leads to the low accuracy of snowboard starting action feature extraction. We propose a snowboard starting action feature extraction using visual sensor image processing. Firstly, the overlapping images are separated by laser fringe technology. After separation, the middle point of the image is taken as the feature point, and the interference factors are filtered by laser. Secondly, the three-dimensional model is established by using visual sensing image technology, the action feature images are input in the order of recognition, and all actions are reconstructed and assembled to complete the action feature extraction of snowboard. The interference factors are filtered by laser, the middle part of the action image is extracted according to the common features of multiple images, and its definition is described. The movement change and moving distance are used to count the most features and clarity. Finally, the edge recognition effect of snowboard starting action image and the action recognition effect under multiple complex images are taken as experimental indexes. The results show that the method has a good effect on image edge extraction, the extraction effect is as high as 95%, and the accuracy is as high as 2.1%. In addition, under multiple complex images, the action feature recognition rate is also high, which can prove that the method studied has better accuracy in snowboard starting action feature extraction.

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Section: Preprocessing Of Extracting the Starting Action Of Snowboardmentioning

confidence: 99%

“…Finally, after the clear edge contour is obtained, the typical feature information is analyzed as [18]:…”

Section: Action Feature Extraction Using Visual Sensing Image Processingmentioning

confidence: 99%

Feature Extraction Method of Snowboard Starting Action Using Vision Sensor Image Processing

Zhang

Li²,

Shin

et al. 2022

Mobile Information Systems

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“…스키의 경우에도 GPS(Global Positioning System: 범지구위치결 정시스템) (Neville, et al, 2010), GNSS(Global Navigation Satellite System: 위성항법시스템) (Alejo, et al, 2021) (Neville, et al, 2010;Silva, et al, 2017). 이러한 필요성에 의해서 훈련 현장에서 나타나는 활동의 빈도•강도•에너지소비량 등 객관적이고 정확한 활동 정보를 수 집하기 위하여 이중표집물(Double Labelled Water: DLW), 이동식 간접열량계 등의 측정 도구들이 사용 (Crouter, Churilla & Bassett, 2006;Troiano, et al, 2014) 되었으나 상대적으로 높은 측정비용과 장비의 착용 시 활동에 주는 제약이 많아 최근에는 가속도계를 기반으 로 한 측정 도구들이 활용되고 있다 (Neville, et al, 2010).…”

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“…가속도계 기반 신체활동 모니터는 작은 크기에도 불구하고 저장용량 의 확대와 길어진 배터리 수명 등의 기술적 발전으로 인해 상대적으로 저렴한 비용으로 장기적인 신체활동 정보를 수집할 수 있어 다양한 대 상의 신체활동 모니터링과 종단적 연구(cohort study)에 적용되고 있다 (Troiano, et al, 2014). 가속도계를 이용한 신체활동의 측정은 활동의 강도•빈도와 시간 그리고 측정 기간 중 나타나는 에너지소비에 대한 실 시간 정보를 대상자 개별적으로 수집할 수 있는 장점이 있으며 (Crouter, et al, 2006;Leinonen, et al, 2017;Shiroma, et al, 2016) 신체 착용 시 활동에 주는 부담이 적어 운동선수들의 훈련과 시합동안 나타 나는 여러 가지 활동 특성을 정량적으로 측정할 수 있는 대안으로 활용 할 수 있다 (Alejo et al, 2021;Mcnally, 2017;Neville, et al, 2010).…”

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Field Training Monitoring of Alpine Ski Athletes Using a Triaxial Accelerometers

Suk¹,

Kang²,

Lee³

et al. 2021

Korean J Sport Sci

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PURPOSE This study was designed to propose a quantitative base training evaluation method through alpine ski training monitoring using a triaxial accelerometer.METHODS Twelve Korean alpine ski athletes, six each in France and New Zealand, participated in this study. Activity data during training and daily living were collected for 7 days via the Actigraph GT9X. The collected data were downloaded through ActiLife Ver 6.13.1. Energy expenditure was calculated with Freedson (2011), and the resting metabolic rate was corrected using the Harris & Benedict (1918) formula. Further, the physical activity intensity classification criteria and METs formula of Freedson (1998) were used to classify hourly activity intensity. The collected data were organized by date, time, intensity, and energy expenditure using Microsoft Excel 2016. Differences between weekdays vs. weekends and skiing vs. physical training were analyzed through a paired sample t-test using Windows SPSS 23 with a significance level of a=.05.RESULTS First, both groups showed repetitive on and off high-intensity activities during scheduled ski training and competition. Second, moderate-intensity activities accounted for an average of 6-10%, and the weekly total time and intensity of MVPA was very high. Finally, the group from France showed differences in total energy expenditure during weekdays vs. weekends (p<.05) and the energy expenditure of both ski training and physical training during weekdays vs. weekends (p<.05). The New Zealand group showed a difference in total energy consumption during weekdays vs. weekends (p<.05).CONCLUSIONS A systematic training program based on quantitative training evaluation should be developed for alpine ski athletes to maintain proper rest and exercise intensity levels.

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How Does the Starting Order in the First and Second Run Affect the Final Rank in the FIS World Cup Giant Slalom?

Björklund

Swarén

2022

Front. Sports Act. Living

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The aim of this study was to determine the impact of runs 1 and 2 on overall rank in Giant Slalom. Data from 15 seasons (2005/2006–2019/2020) including and unique starts for women (n = 2,294) and men (n = 2,328) were analyzed. Skiers were grouped based on final ranks 1–3 (G3), 4–10 (G10), and 11–20 (G20) and separately analyzed for women and men. A Wilcoxon-signed rank test was used for comparisons between runs 1 and 2, while a multi-nominal logistic regression was used to identify odds ratios (OR) associated with group rank. Women had similar run times for runs 1 and 2 (p = 0.734), while men had faster times on run 2 (p < 0.001). The strongest association to G3 was during run 1 for run time (men: OR 1.06–1.12; women: OR 1.06–1.11, all p < 0.01) and gate-to-gate times (men: OR 33–475; women: OR 81–2,301, all p < 0.001). Overall, this study demonstrates the importance of a fast first run for improving the final ranking group and the need to increase the tempo going from the first to the second run for men.

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Performance Parameters in Competitive Alpine Skiing Disciplines of Slalom, Giant Slalom and Super-Giant Slalom

Cited by 3 publications

References 19 publications

Feature Extraction Method of Snowboard Starting Action Using Vision Sensor Image Processing

Feature Extraction Method of Snowboard Starting Action Using Vision Sensor Image Processing

Field Training Monitoring of Alpine Ski Athletes Using a Triaxial Accelerometers

How Does the Starting Order in the First and Second Run Affect the Final Rank in the FIS World Cup Giant Slalom?

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