• Sohail Shaikh

ECG being a non-stationary signal, the irregularities won't be periodic and cannot show up all the time, but would manifest at positive irregular intervals throughout the day. So, continuous ECG monitoring permits observation of cardiac variations over an extended period of time, either at the bad side or when patients are ambulatory, providing more information to physician. The Arrhythmia detection techniques used until now are complex in nature. Reduction in complexity remains the challenge now a day. Also arrhythmias classification methods based on ECG signals were developed but were weak and inaccurate. So it is important to develop computer based system that categorizes ECG signals and make improvements in the techniques of ECG analysis. There are many types of heart arrhythmias which can be detected by analysis of the ECG signals. In ECG analysis, the most focus is to reinforce degree of accuracy and embrace a lot of range of heart diseases which will be classified. ECG signals have well defined P, T waves and QRS complexes. The present work will help in building up a PC based framework that will be capable to classify the ECG signals.

ECG

"ECG Heart Disease detection using DWT and Artificial Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.22-26, June 2019, Available :http://www.jetir.org/papers/JETIR1906Q04.pdf

"ECG Heart Disease detection using DWT and Artificial Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp22-26, June 2019, Available at : http://www.jetir.org/papers/JETIR1906Q04.pdf