Automatic Detection of Faults in Race Walking: A Comparative Analysis of Machine-Learning Algorithms Fed with Inertial Sensor Data

Automatic Detection of Faults in Race Walking: A Comparative Analysis of Machine-Learning Algorithms Fed with Inertial Sensor Data

The validity of results in race walking is often questioned due to subjective decisions in the detection of faults. This study aims to compare machine-learning algorithms fed with data gathered from inertial sensors placed on lower-limb segments to define the best-performing classifiers for the auto...

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Bibliographic Details
Main Authors: Juri Taborri, Eduardo Palermo, Stefano Rossi
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Sensors
Subjects:
race walking
illegal steps
machine-learning algorithms
inertial sensors
activity recognition
Online Access:https://www.mdpi.com/1424-8220/19/6/1461

Internet

https://www.mdpi.com/1424-8220/19/6/1461

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