Abnormal ECG detection based on an adversarial autoencoder

Automatic detection and alarm of abnormal electrocardiogram (ECG) events play an important role in an ECG monitor system; however, popular classification models based on supervised learning fail to detect abnormal ECG effectively. Thus, we propose an ECG anomaly detection framework (ECG-AAE) based o...

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Detalles Bibliográficos
Autores principales: Shan, Lianfeng, Li, Yu, Jiang, Hua, Zhou, Peng, Niu, Jing, Liu, Ran, Wei, Yuanyuan, Peng, Jiao, Yu, Huizhen, Sha, Xianzheng, Chang, Shijie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481281/
https://www.ncbi.nlm.nih.gov/pubmed/36117713
http://dx.doi.org/10.3389/fphys.2022.961724

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481281/
https://www.ncbi.nlm.nih.gov/pubmed/36117713
http://dx.doi.org/10.3389/fphys.2022.961724

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