Gaussian process framework for pervasive estimation of swimming velocity with body-worn IMU

Détails

ID Serval
serval:BIB_8EADE8D8C02E
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Gaussian process framework for pervasive estimation of swimming velocity with body-worn IMU
Périodique
Electronics Letters
Auteur(s)
Dadashi F., Millet G. P., Aminian K.
ISSN
0013-5194
ISSN-L
0013-5194
Statut éditorial
Publié
Date de publication
2013
Peer-reviewed
Oui
Volume
49
Numéro
1
Pages
44-46
Langue
anglais
Résumé
Presented is an accurate swimming velocity estimation method using an inertial measurement unit (IMU) by employing a simple biomechanical constraint of motion along with Gaussian process regression to deal with sensor inherent errors. Experimental validation shows a velocity RMS error of 9.0 cm/s and high linear correlation when compared with a commercial tethered reference system. The results confirm the practicality of the presented method to estimate swimming velocity using a single low-cost, body-worn IMU.
Mots-clé
Gaussian processes, biomechanics, estimation theory, motion estimation, regression analysis, velocity measurement, Gaussian process regression, biomechanical motion constraint, commercial tethered reference system, high linear correlation, inertial measurement unit, pervasive estimation, sensor inherent errors, single low-cost body-worn IMU, swimming velocity estimation, velocity RMS error
Web of science
Création de la notice
26/12/2013 19:00
Dernière modification de la notice
03/03/2018 19:19
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