Title :
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
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);
Conference_Titel :
Science Engineering and Management Research (ICSEMR), 2014 International Conference on
Print_ISBN :
978-1-4799-7614-0
DOI :
10.1109/ICSEMR.2014.7043597