A Spatial Pyramid Pooling-Based Deep Convolutional Neural Network for the Classification of Electrocardiogram Beats

A Spatial Pyramid Pooling-Based Deep Convolutional Neural Network for the Classification of Electrocardiogram Beats

An accurate electrocardiogram (ECG) beat classification can benefit the diagnosis of the cardiovascular disease. Deep convolutional neural networks (CNN) can automatically extract valid features from data, which is an effective way for the classification of the ECG beats. However, the fully-connecte...

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Bibliographic Details
Main Authors: Jia Li, Yujuan Si, Liuqi Lang, Lixun Liu, Tao Xu
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Applied Sciences
Subjects:
ECG beats
classification
feature extraction
convolutional neural networks
spatial pyramid pooling
Online Access:http://www.mdpi.com/2076-3417/8/9/1590

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