A Lightweight Deep Learning Model for Fast Electrocardiographic Beats Classification With a Wearable Cardiac Monitor: Development and Validation Study

BACKGROUND: Electrocardiographic (ECG) monitors have been widely used for diagnosing cardiac arrhythmias for decades. However, accurate analysis of ECG signals is difficult and time-consuming work because large amounts of beats need to be inspected. In order to enhance ECG beat classification, machi...

Descripción completa

Detalles Bibliográficos
Autores principales: Jeon, Eunjoo, Oh, Kyusam, Kwon, Soonhwan, Son, HyeongGwan, Yun, Yongkeun, Jung, Eun-Soo, Kim, Min Soo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099397/
https://www.ncbi.nlm.nih.gov/pubmed/32163037
http://dx.doi.org/10.2196/17037

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7099397/
https://www.ncbi.nlm.nih.gov/pubmed/32163037
http://dx.doi.org/10.2196/17037

Ejemplares similares