Next Article in Journal
Design of a Plantar Pressure Insole Measuring System Based on Modular Photoelectric Pressure Sensor Unit
Next Article in Special Issue
Wearable IMU-Based Human Activity Recognition Algorithm for Clinical Balance Assessment Using 1D-CNN and GRU Ensemble Model
Previous Article in Journal
Research Trends and Future Perspectives in Marine Biomimicking Robotics
Previous Article in Special Issue
Detection of Movement Events of Long-Track Speed Skating Using Wearable Inertial Sensors

Connected Skiing: Motion Quality Quantification in Alpine Skiing

Department of Sport and Exercise Science, University of Salzburg, Schlossallee 49, 5400 Hallein/Rif, Austria
Athlete Performance Center, Red Bull Sports, Brunnbachweg 71, 5303 Thalgau, Austria
Atomic Austria GmbH, Atomic Strasse 1, 5541 Altenmarkt, Austria
Author to whom correspondence should be addressed.
Academic Editors: Fabien Buisseret, Frédéric Dierick and Liesbet Van der Perre
Sensors 2021, 21(11), 3779;
Received: 16 April 2021 / Revised: 26 May 2021 / Accepted: 28 May 2021 / Published: 29 May 2021
(This article belongs to the Special Issue Wearable Sensors Applied in Movement Analysis)
Recent developments in sensing technology have made wearable computing smaller and cheaper. While many wearable technologies aim to quantify motion, there are few which aim to qualify motion. (2) To develop a wearable system to quantify motion quality during alpine skiing, IMUs were affixed to the ski boots of nineteen expert alpine skiers while they completed a set protocol of skiing styles, included carving and drifting in long, medium, and short radii. The IMU data were processed according to the previously published skiing activity recognition chain algorithms for turn segmentation, enrichment, and turn style classification Principal component models were learned on the time series variables edge angle, symmetry, radial force, and speed to identify the sources of variability in a subset of reference skiers. The remaining data were scored by comparing the PC score distributions of variables to the reference dataset. (3) The algorithm was able to differentiate between an expert and beginner skier, but not between an expert and a ski instructor, or a ski instructor and a beginner. (4) The scoring algorithm is a novel concept to quantify motion quality but is limited by the accuracy and relevance of the input data. View Full-Text
Keywords: IMU; principal component analysis; wearable; scoring; carving IMU; principal component analysis; wearable; scoring; carving
Show Figures

Figure 1

MDPI and ACS Style

Snyder, C.; Martínez, A.; Jahnel, R.; Roe, J.; Stöggl, T. Connected Skiing: Motion Quality Quantification in Alpine Skiing. Sensors 2021, 21, 3779.

AMA Style

Snyder C, Martínez A, Jahnel R, Roe J, Stöggl T. Connected Skiing: Motion Quality Quantification in Alpine Skiing. Sensors. 2021; 21(11):3779.

Chicago/Turabian Style

Snyder, Cory, Aaron Martínez, Rüdiger Jahnel, Jason Roe, and Thomas Stöggl. 2021. "Connected Skiing: Motion Quality Quantification in Alpine Skiing" Sensors 21, no. 11: 3779.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop