Practical Method for ECG Classification Using Weighted ELM

Hui Liu; Xin Yu Jin; Lan Juan Li

doi:10.4028/www.scientific.net/AMM.738-739.832

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 738-739Practical Method for ECG Classification Using...

Practical Method for ECG Classification Using Weighted ELM

Abstract:

Automatic detection of electrocardiogram (ECG) plays an important role in reducing pressure of nursing patients with heart disease. There have been many studies about ECG classification,which mostly based on machine learning, such as neural networks, extreme learning machine (ELM), and have reached a high accuracy. But it remains to be improved when applied in practice. In this paper, we propose a more practical method, namely the weighted ELM algorithm,which has better time performance and better generalization capability than traditional machine learning method. In particular,classification models trained by this method have better decision-boundary when faced with the imbalance ECG samples.

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Periodical:

Applied Mechanics and Materials (Volumes 738-739)

Pages:

832-835

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.738-739.832

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Online since:

March 2015

Authors:

Hui Liu*, Xin Yu Jin, Lan Juan Li

Keywords:

ECG Signals Classification, Imbalanced Classification, Weighted ELM

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