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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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Veröffentlicht in:Sensors (Basel)
Hauptverfasser: Taborri, Juri, Palermo, Eduardo, Rossi, Stefano
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI 2019
Schlagworte:
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6470680/
https://ncbi.nlm.nih.gov/pubmed/30934643
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19061461
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