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Open AccessArticle

Cross-Country Skiing Analysis and Ski Technique Detection by High-Precision Kinematic Global Navigation Satellite System

1
Faculty of Health and Sports Science, Doshisha University, Kyoto 610-0332, Japan
2
New Industry Creation Hatchery Center, Tohoku University, Sendai 980-8576, Japan
3
Faculty of Sport and Health Sciences, University of Jyväskylä, FI-40014 Jyväskylä, Finland
4
Department of Food and Nutrition and Sport Science, University of Gothenburg, SE-405 Gothenburg, Sweden
5
Department of Sport and Exercise Science, University of Salzburg, 5020 Salzburg, Austria
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(22), 4947; https://doi.org/10.3390/s19224947
Received: 13 September 2019 / Revised: 1 November 2019 / Accepted: 2 November 2019 / Published: 13 November 2019
(This article belongs to the Special Issue Sensors for Biomechanics Application)
Cross-country skiing (XCS) embraces a broad variety of techniques applied like a gear system according to external conditions, slope topography, and skier-related factors. The continuous detection of applied skiing techniques and cycle characteristics by application of unobtrusive sensor technology can provide useful information to enhance the quality of training and competition. (1) Background: We evaluated the possibility of using a high-precision kinematic global navigation satellite system (GNSS) to detect cross-country skiing classical style technique. (2) Methods: A world-class male XC skier was analyzed during a classical style 5.3-km time trial recorded with a high-precision kinematic GNSS attached to the skier’s head. A video camera was mounted on the lumbar region of the skier to detect the type and number of cycles of each technique used during the entire time trial. Based on the GNSS trajectory, distinct patterns of head displacement (up-down head motion) for each classical technique (e.g., diagonal stride (DIA), double poling (DP), kick double poling (KDP), herringbone (HB), and downhill) were defined. The applied skiing technique, skiing duration, skiing distance, skiing speed, and cycle time within a technique and the number of cycles were visually analyzed using both the GNSS signal and the video data by independent persons. Distinct patterns for each technique were counted by two methods: Head displacement with course inclination and without course inclination (net up-down head motion). (3) Results: Within the time trial, 49.6% (6 min, 46 s) was DP, 18.7% (2 min, 33 s) DIA, 6.1% (50 s) KDP, 3.3% (27 s) HB, and 22.3% (3 min, 03 s) downhill with respect to total skiing time (13 min, 09 s). The %Match for both methods 1 and 2 (net head motion) was high: 99.2% and 102.4%, respectively, for DP; 101.7% and 95.9%, respectively, for DIA; 89.4% and 100.0%, respectively, for KDP; 86.0% and 96.5%, respectively, in HB; and 98.6% and 99.6%, respectively, in total. (4) Conclusions: Based on the results of our study, it is suggested that a high-precision kinematic GNSS can be applied for precise detection of the type of technique, and the number of cycles used, duration, skiing speed, skiing distance, and cycle time for each technique, during a classical style XCS race. View Full-Text
Keywords: classical technique; cross-country skiing; kinematic GNSS; GPS classical technique; cross-country skiing; kinematic GNSS; GPS
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Takeda, M.; Miyamoto, N.; Endo, T.; Ohtonen, O.; Lindinger, S.; Linnamo, V.; Stöggl, T. Cross-Country Skiing Analysis and Ski Technique Detection by High-Precision Kinematic Global Navigation Satellite System. Sensors 2019, 19, 4947.

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