Electrocardiogram based arrhythmia classification using wavelet transform with deep learning model

Electrocardiogram based arrhythmia classification using wavelet transform with deep learning model

High-risk patients of cardiovascular disease can be provided with computerized electrocardiogram (ECG) devices to detect Arrhythmia. These require long segments of quality ECG which however can lead to missing the episode. To overcome this, we have proposed a deep-learning approach, where the scalog...

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Bibliographic Details
Main Authors: Shadhon Chandra Mohonta, Mohammod Abdul Motin, Dinesh Kant Kumar
Format: Article
Language:English
Published: Elsevier 2022-08-01
Series:Sensing and Bio-Sensing Research
Subjects:
Arrhythmia
Continuous wavelet transform (CWT)
Convolutional neural network (CNN)
Fast Fourier transform (FFT)
Short-time Fourier transform (STFT)
Online Access:http://www.sciencedirect.com/science/article/pii/S2214180422000319

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http://www.sciencedirect.com/science/article/pii/S2214180422000319

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