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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Detalles Bibliográficos
Autores principales: Taborri, Juri, Palermo, Eduardo, Rossi, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470680/
https://www.ncbi.nlm.nih.gov/pubmed/30934643
http://dx.doi.org/10.3390/s19061461

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470680/
https://www.ncbi.nlm.nih.gov/pubmed/30934643
http://dx.doi.org/10.3390/s19061461

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