Expert-level classification of ventilatory thresholds from cardiopulmonary exercising test data with recurrent neural networks.

Retrospective study cardiopulmonary exercise testing machine learning ventilatory threshold detection

Journal

European journal of sport science
ISSN: 1536-7290
Titre abrégé: Eur J Sport Sci
Pays: England
ID NLM: 101146739

Informations de publication

Date de publication:
Oct 2019
Historique:
pubmed: 19 3 2019
medline: 18 12 2019
entrez: 19 3 2019
Statut: ppublish

Résumé

First and second ventilatory thresholds (VT

Identifiants

pubmed: 30880591
doi: 10.1080/17461391.2019.1587523
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1221-1229

Auteurs

Andrea Zignoli (A)

Department of Industrial Engineering, University of Trento , Trento , Italy.
CeRiSM Research Centre, University of Verona , Rovereto , Trento , Italy.

Alessandro Fornasiero (A)

CeRiSM Research Centre, University of Verona , Rovereto , Trento , Italy.
Department of Neuroscience, Biomedicine and Movement, University of Verona , Verona , Italy.

Federico Stella (F)

CeRiSM Research Centre, University of Verona , Rovereto , Trento , Italy.

Barbara Pellegrini (B)

CeRiSM Research Centre, University of Verona , Rovereto , Trento , Italy.
Department of Neuroscience, Biomedicine and Movement, University of Verona , Verona , Italy.

Federico Schena (F)

CeRiSM Research Centre, University of Verona , Rovereto , Trento , Italy.
Department of Neuroscience, Biomedicine and Movement, University of Verona , Verona , Italy.

Francesco Biral (F)

Department of Industrial Engineering, University of Trento , Trento , Italy.

Paul B Laursen (PB)

Sports Performance Research Institute NZ, Auckland University of Technology , Auckland , New Zealand.

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Classifications MeSH