INTRODUCTION: Recent studies by Marsland et al. (2012) and Myklebust et al. (2014) highlighted the potential for micro-sensors in the identification and classification of cross-country skiing techniques. The advantage of micro-sensors for kinematic measurement is the possibility for continuous data collection during daily training and in competition. This study used micro-sensors to measure classical cross-country skiing macro kinematics in the field and determine their accuracy against simultaneously captured video footage. METHOD: Using micro-sensors the kinematics of cyclical classical cross-country skiing techniques double pole (DP), diagonal stride (DS) and kick double pole (KDP) were recorded during an onsnow training session. Seven national athletes (4f, 3m) skied a 480m course while wearing a single micro-sensor unit positioned in the centre of the upper back. Technique duration (T-time), cycle rates and cycle counts were determined from the micro-sensor data and compared to video data. RESULTS: The mean difference between cycle rates for the two analysis methods was trivial for DP (ES=0.02) and small for DS (ES=0.30) and KDP (ES=0.13). Mean T-time and cycle counts were under-reported for DS and KDP, while for DP the mean values were comparable but highly variable (Figure 1). Differences arose during turns and to a lesser extent during tucks and technique transitions. There were no significant differences in detection accuracy between males and females. DISCUSSION: Micro-sensor determined cycle rates were unaffected by missed technique cycles and the observed accuracy was very high. Combined with accurate GPS velocity this enables the precise measurement of each technique cycle length and velocity. Single micro-sensor use has great potential to provide detailed performance analysis in sections of the track with continuous technique use. Improved detection accuracy for turning, tucking and transitions would greatly enhance analysis of entire competitions or training sessions. CONCLUSION: Data presented highlights the potential of automated ski technique classification in cross-country skiing macro kinematic research, particularly during consistent use of a particular technique. Further system refinement will allow many applied questions associated with pacing, fatigue, and technique selection during training and competition to be answered. --- The hosting University of Jyväskylä is planning to publish conference proceedings "Science and Nordic Skiing III". In case you are interested in this publication please contact the editors (Anni Hakkarainen anni.s.j.hakkarainen@jyu.fi) to become registered for the book.
© Copyright 2015 3rd International Congress on Science and Nordic Skiing - ICSNS 2015. 5-8 June 2015, Vuokatti, Finland. Veröffentlicht von University of Jyväskylä; University of Salzburg. Alle Rechte vorbehalten. / Übersetzt mit https://www.DeepL.com/Translator