Automated Method for Discrimination of Arrhythmias Using Time, Frequency, and Nonlinear Features of Electrocardiogram Signals

We developed an automated approach to differentiate between different types of arrhythmic episodes in electrocardiogram (ECG) signals, because, in real-life scenarios, a software application does not know in advance the type of arrhythmia a patient experiences. Our approach has four main stages: (1)...

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Detalles Bibliográficos
Autores principales: Hajeb-Mohammadalipour, Shirin, Ahmadi, Mohsen, Shahghadami, Reza, Chon, Ki H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068712/
https://www.ncbi.nlm.nih.gov/pubmed/29966276
http://dx.doi.org/10.3390/s18072090

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068712/
https://www.ncbi.nlm.nih.gov/pubmed/29966276
http://dx.doi.org/10.3390/s18072090

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