Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup
In order to gain insight into skiing performance, it is necessary to determine the point where each turn begins. Recent developments in sensor technology have made it possible to develop simpler automatic turn detection methodologies, however they are not feasible for regular use. The aim of this st...
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doaj-efc9f4e464bb4198b762ffdab8afa4e72020-11-25T00:02:55ZengMDPI AGSensors1424-82202019-02-0119490210.3390/s19040902s19040902Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor SetupAaron Martínez0Rüdiger Jahnel1Michael Buchecker2Cory Snyder3Richard Brunauer4Thomas Stöggl5Department of Sport and Exercise Science, University of Salzburg, Schlossallee 49, 5400 Hallein/Rif, AustriaDepartment of Sport and Exercise Science, University of Salzburg, Schlossallee 49, 5400 Hallein/Rif, AustriaDepartment of Sport and Exercise Science, University of Salzburg, Schlossallee 49, 5400 Hallein/Rif, AustriaDepartment of Sport and Exercise Science, University of Salzburg, Schlossallee 49, 5400 Hallein/Rif, AustriaSalzburg Research Forschungsgesellschaft m.b.H., Techno-Z III, Jakob-Haringer-Straße 5, 5020 Salzburg, AustriaDepartment of Sport and Exercise Science, University of Salzburg, Schlossallee 49, 5400 Hallein/Rif, AustriaIn order to gain insight into skiing performance, it is necessary to determine the point where each turn begins. Recent developments in sensor technology have made it possible to develop simpler automatic turn detection methodologies, however they are not feasible for regular use. The aim of this study was to develop a sensor set up and an algorithm to precisely detect turns during alpine ski, which is feasible for a daily use. An IMU was attached to the posterior upper cuff of each ski boot. Turn movements were reproduced on a ski-ergometer at different turn durations and slopes. Algorithms were developed to analyze vertical, medio-lateral, anterior-posterior axes, and resultant accelerometer and gyroscope signals. Raw signals, and signals filtered with 3, 6, 9, and 12 Hz cut-offs were used to identify turn switch points. Video recordings were assessed to establish a reference turn-switch and precision (mean bias = 5.2, LoA = 51.4 ms). Precision was adjusted based on reference and the best signals were selected. The <i>z</i>-axis and resultant gyroscope signals, filtered at 3Hz are the most precise signals (0.056 and 0.063 s, respectively) to automatically detect turn switches during alpine skiing using this simple system.https://www.mdpi.com/1424-8220/19/4/902accelerometergyroscopeIMUprecisionski |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Aaron Martínez Rüdiger Jahnel Michael Buchecker Cory Snyder Richard Brunauer Thomas Stöggl |
spellingShingle |
Aaron Martínez Rüdiger Jahnel Michael Buchecker Cory Snyder Richard Brunauer Thomas Stöggl Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup Sensors accelerometer gyroscope IMU precision ski |
author_facet |
Aaron Martínez Rüdiger Jahnel Michael Buchecker Cory Snyder Richard Brunauer Thomas Stöggl |
author_sort |
Aaron Martínez |
title |
Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup |
title_short |
Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup |
title_full |
Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup |
title_fullStr |
Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup |
title_full_unstemmed |
Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup |
title_sort |
development of an automatic alpine skiing turn detection algorithm based on a simple sensor setup |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2019-02-01 |
description |
In order to gain insight into skiing performance, it is necessary to determine the point where each turn begins. Recent developments in sensor technology have made it possible to develop simpler automatic turn detection methodologies, however they are not feasible for regular use. The aim of this study was to develop a sensor set up and an algorithm to precisely detect turns during alpine ski, which is feasible for a daily use. An IMU was attached to the posterior upper cuff of each ski boot. Turn movements were reproduced on a ski-ergometer at different turn durations and slopes. Algorithms were developed to analyze vertical, medio-lateral, anterior-posterior axes, and resultant accelerometer and gyroscope signals. Raw signals, and signals filtered with 3, 6, 9, and 12 Hz cut-offs were used to identify turn switch points. Video recordings were assessed to establish a reference turn-switch and precision (mean bias = 5.2, LoA = 51.4 ms). Precision was adjusted based on reference and the best signals were selected. The <i>z</i>-axis and resultant gyroscope signals, filtered at 3Hz are the most precise signals (0.056 and 0.063 s, respectively) to automatically detect turn switches during alpine skiing using this simple system. |
topic |
accelerometer gyroscope IMU precision ski |
url |
https://www.mdpi.com/1424-8220/19/4/902 |
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