Automatic front-crawl temporal phase detection using adaptive filtering of inertial signals

Détails

ID Serval
serval:BIB_0C0DF5132DAE
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Automatic front-crawl temporal phase detection using adaptive filtering of inertial signals
Périodique
Journal of Sports Sciences
Auteur⸱e⸱s
Dadashi F., Crettenand F., Millet G. P., Seifert L., Komar J., Aminian K.
ISSN
0264-0414
Statut éditorial
Publié
Date de publication
2013
Peer-reviewed
Oui
Volume
31
Numéro
11
Pages
1251-1260
Langue
anglais
Notes
Dadashi, Farzin Crettenand, Florent Millet, Gregoire P Seifert, Ludovic Komar, John Aminian, Kamiar England J Sports Sci. 2013;31(11):1251-60. doi: 10.1080/02640414.2013.778420. Epub 2013 Apr 5.
Résumé
This study introduces a novel approach for automatic temporal phase detection and inter-arm coordination estimation in front-crawl swimming using inertial measurement units (IMUs). We examined the validity of our method by comparison against a video-based system. Three waterproofed IMUs (composed of 3D accelerometer, 3D gyroscope) were placed on both forearms and the sacrum of the swimmer. We used two underwater video cameras in side and frontal views as our reference system. Two independent operators performed the video analysis. To test our methodology, seven well-trained swimmers performed three 300 m trials in a 50 m indoor pool. Each trial was in a different coordination mode quantified by the index of coordination. We detected different phases of the arm stroke by employing orientation estimation techniques and a new adaptive change detection algorithm on inertial signals. The difference of 0.2 +/- 3.9% between our estimation and video-based system in assessment of the index of coordination was comparable to experienced operators' difference (1.1 +/- 3.6%). The 95% limits of agreement of the difference between the two systems in estimation of the temporal phases were always less than 7.9% of the cycle duration. The inertial system offers an automatic easy-to-use system with timely feedback for the study of swimming.
Pubmed
Web of science
Création de la notice
14/08/2013 11:52
Dernière modification de la notice
20/08/2019 13:33
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