ArticleSensors (Basel, Switzerland)2019
Development of an Automatic Alpine Skiing Turn Detection Algorithm Based on a Simple Sensor Setup.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Smart technology and multibody simulation for skier safety: a structured narrative review and research roadmap.Frontiers in sports and active living · 2026Review
- Joint kinematic responses of Olympic medallist skiers to repeated slalom runs.Experimental physiology · 2025Article
- Motion Analysis in Alpine Skiing: Sensor Placement and Orientation-Invariant Sensing.Sensors (Basel, Switzerland) · 2025Article
- SnowMotion: A Wearable Sensor-Based Mobile Platform for Alpine Skiing Technique Assistance.Sensors (Basel, Switzerland) · 2024Article
- Skiing quality analysis of recreational skiers based on IMU data and self-assessment.Frontiers in sports and active living · 2024Article
- Evaluating wrapping alpine ski boots during on-snow carving.Frontiers in sports and active living · 2023Article
- Alpine Skiing Activity Recognition Using Smartphone's IMUs.Sensors (Basel, Switzerland) · 2022Article
- Proposal of an Alpine Skiing Kinematic Analysis with the Aid of Miniaturized Monitoring Sensors, a Pilot Study.Sensors (Basel, Switzerland) · 2022Article
- Recognizing Solo Jazz Dance Moves Using a Single Leg-Attached Inertial Wearable Device.Sensors (Basel, Switzerland) · 2022Article
- Influence of Turn Cycle Structure on Performance of Elite Alpine Skiers Assessed through an IMU in Different Slalom Course Settings.Sensors (Basel, Switzerland) · 2022Article
- Carved Turn Control with Gate Vision Recognition of a Humanoid Robot for Giant Slalom Skiing on Ski Slopes.Sensors (Basel, Switzerland) · 2022Article
- Effects of physical stress in alpine skiing on psychological, physiological, and biomechanical parameters: An individual approach.Frontiers in sports and active living · 2022Article
- Connected Skiing: Motion Quality Quantification in Alpine Skiing.Sensors (Basel, Switzerland) · 2021Article
- A Comprehensive Comparison and Validation of Published Methods to Detect Turn Switch during Alpine Skiing.Sensors (Basel, Switzerland) · 2021Article
- Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance.Sensors (Basel, Switzerland) · 2021Article
- Studying Force Patterns in an Alpine Ski Boot and Their Relation to Riding Styles and Falling Mechanisms.Frontiers in sports and active living · 2021Article
- Classification of Alpine Skiing Styles Using GNSS and Inertial Measurement Units.Sensors (Basel, Switzerland) · 2020Article
- Application of Inertial Motion Unit-Based Kinematics to Assess the Effect of Boot Modifications on Ski Jump Landings-A Methodological Study.Sensors (Basel, Switzerland) · 2020Article
- Computationally Efficient 3D Orientation Tracking Using Gyroscope Measurements.Sensors (Basel, Switzerland) · 2020Article
- Comparison of the Turn Switch Time Points Measured by Portable Force Platforms and Pressure Insoles.Frontiers in sports and active living · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.