A Bayesian Approach for Pervasive Estimation of Breaststroke Velocity Using a Wearable IMU
Dadashi, Farzin; Millet, Gregoire; Aminian, Kamiar
2015

Abstract

An ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1±9.6 % and high correlation with the tethered reference system (rX,Y = 0.91) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.

Details

Title A Bayesian Approach for Pervasive Estimation of Breaststroke Velocity Using a Wearable IMU
Author(s) Dadashi, Farzin ; Millet, Gregoire ; Aminian, Kamiar
Published in Pervasive and Mobile Computing
Pagination 10
Volume 19
Pages 37-46
Date 2015
Publisher Amsterdam, Elsevier Science Bv
Keywords
DOI https://doi.org/10.1016/j.pmcj.2014.03.001
Other identifier(s) View record in Web of Science
Laboratories LMAM
Record Appears in Scientific production and competences > STI - School of Engineering > IBI-STI - Interfaculty Institute of Bioengineering > LMAM - Laboratory of Movement Analysis and Measurement
Peer-reviewed publications
Work produced at EPFL
Journal Articles
Published
Record creation date 2014-03-03

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