Automatic classification of take-off type in figure skating jumps using a wearable sensor
Athletes in numerous sports face a potential conflict between performance improvement and injury prevention, with short term injury perceptions often superseding concerns of distant injury risks. Although it is generally acknowledged that repetitive landing impacts play a role in chronic injury development in figure skating [1], coaches and skaters do not generally track jump training volume. Activity tracking using wearable inertial measurement units (IMUs) may allow tracking of training volume but non-cyclic and continuous motion in figure skating presents numerous challenges to automatic jump detection using IMU data. In addition to tracking the number of jumps performed, tracking jump type is essential in order to effectively regulate training volume.
© Copyright 2022 ISEA Engineering of Sport 14 Conference. All rights reserved.
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| Notations: | technical sports technical and natural sciences biological and medical sciences training science |
| Published in: | ISEA Engineering of Sport 14 Conference |
| Language: | English |
| Published: |
2022
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| Online Access: | https://doi.org/10.5703/1288284317496 |
| Document types: | research paper |
| Level: | advanced |