Auto analysis of ECG signals using artificial neural network

Author

Raj, A. Abishek Santhosh ; Dheetsith, N. ; Nair, Sainath S. ; Ghosh, Debashree

Author_Institution

Dept. of Biomed. Eng., Alpha Coll. of Eng., Chennai, India

fYear

2014

Firstpage

1

Lastpage

4

Abstract

The greatest challenge faced during the process of diagnosis of cardiovascular diseases is the accurate analyses of the Electrocardiogram (ECG). Many researches are being done to classify and analyze the ECG signals automatically. In this paper, a novel method for the Auto analysis of the ECG signals using MATLAB is proposed and implemented. In this method, the raw ECG data obtained from the patient goes through a process of Wavelet Packet Decomposition (WPD) followed by Feature extraction. The classification is further done using Artificial Neural Network (ANN). This method, succeeding in differentiating the Abnormal ECG signals from the Normal signals, is proved to be a novel method for Auto analysis of ECG signals.

Keywords

backpropagation; cardiovascular system; diseases; electrocardiography; feature extraction; mathematics computing; medical signal processing; patient diagnosis; signal classification; wavelet neural nets; wavelet transforms; ANN method; ECG signal auto analysis; MATLAB; WPD; abnormal ECG signals; abnormal electrocardiogram signal; accurate ECG signal analyses; accurate electrocardiogram signal analyses; artificial neural network; automatic ECG signal analysis; automatic ECG signal classification; automatic electrocardiogram signal analysis; automatic electrocardiogram signal classification; cardiovascular disease diagnosis; electrocardiogram signal auto analysis; feature extraction; matrix laboratory; patient ECG data; patient electrocardiogram data; raw ECG data; raw electrocardiogram data; wavelet packet decomposition; Discrete wavelet transforms; Diseases; Electrocardiography; Feature extraction; Heart; Training; Wavelet packets; Artificial Neural Network (ANN); Eletrocardiogram (ECG); Wavelet Packet Decomposition (WPD);

fLanguage

English

Publisher

ieee

Conference_Titel

Science Engineering and Management Research (ICSEMR), 2014 International Conference on

Print_ISBN

978-1-4799-7614-0

Type

conf

DOI

10.1109/ICSEMR.2014.7043597

Filename

7043597