Preprint Technical Note Version 1 Preserved in Portico This version is not peer-reviewed

Inertial Sensors-Based Estimation of Temporal Events in Skating Sub-Techniques While In-Field Roller Skiing

Version 1 : Received: 23 November 2022 / Approved: 25 November 2022 / Online: 25 November 2022 (10:09:08 CET)

A peer-reviewed article of this Preprint also exists.

Meyer, F.; Lund-Hansen, M.; Kocbach, J.; Seeberg, T.M.; Sandbakk, Ø.B.; Austeng, A. Inertial Sensor-Based Estimation of Temporal Events in Skating Sub-Techniques While In-Field Roller Skiing. Journal of Applied Biomechanics 2023, 1–5, doi:10.1123/jab.2022-0073. Meyer, F.; Lund-Hansen, M.; Kocbach, J.; Seeberg, T.M.; Sandbakk, Ø.B.; Austeng, A. Inertial Sensor-Based Estimation of Temporal Events in Skating Sub-Techniques While In-Field Roller Skiing. Journal of Applied Biomechanics 2023, 1–5, doi:10.1123/jab.2022-0073.

Abstract

The aim of this study was to adapt a treadmill-developed method for determination of inner-cycle parameters in cross-country roller ski skating for a field application. The method is based on detecting initial and final ground-contact of poles and skis during cyclic movements. Eleven athletes skied four laps of 2.5 km at low and high endurance-intensity, using two types of skis with different rolling coefficients. Participants were equipped with inertial measurement units (IMUs) attached to their wrists and skis, while insoles with pressure sensors and poles with force measurements were used as reference systems. The method based on IMUs was able to detect more than 97% of the temporal events compared to the reference system. The inner-cycle temporal parameters had a precision ranging from 49 to 59 ms, corresponding to 3.9% to 13.7% of the corresponding inner-cycle duration. Overall, this study showed good reliability of using IMUs on athlete’s wrists and skis to determine temporal events, inner-cycle parameters and the performed sub-techniques in cross-country roller ski skating in field-conditions.

Keywords

cross-country skiing; temporal event detection; wearable sensors; field analysis

Subject

Biology and Life Sciences, Biophysics

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