Cargando…
Arrhythmia Detection based on Morphological and Time-frequency Features of T-wave in Electrocardiogram
As the T-wave section in electrocardiogram (ECG) illustrates the repolarization phase of heart activity, the information which is accumulated in this section is so significant that it can explain the proper operation of electrical activities in heart. Long QT syndrome (LQT) and T-Wave Alternans (TWA...
Autores principales: | Zeraatkar, Elham, Kermani, Saeed, Mehridehnavi, Alireza, Aminzadeh, A., Zeraatkar, E., Sanei, Hamid |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3342620/ https://www.ncbi.nlm.nih.gov/pubmed/22606664 |
Ejemplares similares
-
Automated Method for Discrimination of Arrhythmias Using Time, Frequency, and Nonlinear Features of Electrocardiogram Signals
por: Hajeb-Mohammadalipour, Shirin, et al.
Publicado: (2018) -
Privacy-Preserving Electrocardiogram Monitoring for Intelligent Arrhythmia Detection †
por: Son, Junggab, et al.
Publicado: (2017) -
Arrhythmia classification detection based on multiple electrocardiograms databases
por: Qi, Meng, et al.
Publicado: (2023) -
Detection of Heart Arrhythmia on Electrocardiogram using Artificial Neural Networks
por: Badr, Malek, et al.
Publicado: (2022) -
Convolutional neural network for classification of eight types of arrhythmia using 2D time–frequency feature map from standard 12-lead electrocardiogram
por: Jeong, Da Un, et al.
Publicado: (2021)