A method for the automatic classification of ECG beat on mobile phones

Author

Varella, Fernando Arena ; De Lima, Guilherme Lazzarotto ; Iochpe, Cirano ; Roesler, Valter

fYear

2011

fDate

27-30 June 2011

Firstpage

1

Lastpage

6

Abstract

In this paper, we propose a novel method to perform the classification of electrocardiogram (ECG) beats on mobile phones. The Discrete Wavelet Transform and Higher Order Statistics are used to extract a set of eleven features from each ECG beat, and a Multilayer Perceptron is used to classify it between six types of beats. Our experiments show that a mobile phone can classify the ECG beats with an overall accuracy of 99.83%, and the sensitivity rates are greater than 99.48% for all beat. Running in a mobile phone phone, it needs only 27ms to classify each heart beat, what makes this method a reliable choice to perform computer-aided diagnosis on remote and critical situations.

Keywords

discrete wavelet transforms; electrocardiography; medical signal processing; mobile computing; multilayer perceptrons; patient diagnosis; signal classification; statistics; ECG beat; automatic classification; computer-aided diagnosis; discrete wavelet transform; electrocardiogram beats; higher order statistics; mobile phones; multilayer perceptron; Accuracy; Discrete wavelet transforms; Electrocardiography; Feature extraction; Mobile handsets; Neurons; Sensitivity;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems (CBMS), 2011 24th International Symposium on

Conference_Location

Bristol

ISSN

1063-7125

Print_ISBN

978-1-4577-1189-3

Type

conf

DOI

10.1109/CBMS.2011.5999107

Filename

5999107