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dc.contributor.authorTakeda, Masaki
dc.contributor.authorMiyamoto, Naoto
dc.contributor.authorEndo, Takaaki
dc.contributor.authorOhtonen, Olli
dc.contributor.authorLindinger, Stefan
dc.contributor.authorLinnamo, Vesa
dc.contributor.authorStöggl, Thomas
dc.identifier.citationTakeda, M., Miyamoto, N., Endo, T., Ohtonen, O., Lindinger, S., Linnamo, V., & Stöggl, T. (2019). Cross-Country Skiing Analysis and Ski Technique Detection by High-Precision Kinematic Global Navigation Satellite System. <i>Sensors</i>, <i>19</i>(22), Article 4947. <a href="" target="_blank"></a>
dc.description.abstractCross-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.en
dc.publisherMDPI AG
dc.rightsCC BY 4.0
dc.subject.otherclassical technique
dc.subject.othercross-country skiing
dc.subject.otherkinematic GNSS
dc.titleCross-Country Skiing Analysis and Ski Technique Detection by High-Precision Kinematic Global Navigation Satellite System
dc.contributor.laitosLiikuntatieteellinen tiedekuntafi
dc.contributor.laitosFaculty of Sport and Health Sciencesen
dc.rights.copyright© 2019 by the authors.
jyx.fundinginformationFunding was provided based on the two Salzburg “Trans-4-Tech” projects “Ski Sense” and “Sport Sense” and by the Austrian Ministry for Transport, Innovation and Technology, the Federal Ministry for Digital and Economic Affairs, and the federal state of Salzburg under the research program COMET—Competence Centers for Excellent Technologies—in the project Digital Motion in Sports, Fitness and Well-being (DiMo).

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