Improved Detection of ECG Features Using Wavelet for Emergency Medical Application | OMICS International | Abstract
ISSN: 2277-1891

International Journal of Advance Innovations, Thoughts & Ideas
Open Access

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Improved Detection of ECG Features Using Wavelet for Emergency Medical Application

A.K.M Fazlul Haque*

Department of Electronics and Telecommunication Engineering, Daffodil International University

*Corresponding Author:
A.K.M Fazlul Haque
Department of Electronics and Telecommunication Engineering
Daffodil International University
E-mail: [email protected]


 Heart is one of the vital organs of human being. Cardiac activities of heart are also significant and very well known of medical sector. ECG (Electrocardiogram) contains very important clinical information about the cardiac activities of heart. The features of ECG signal may be extracted using FFT (Fast Fourier Transform) and Wavelet, especially for emergency medical situation. But it is difficult to extract the changes of small variation of ECG signal with time-varying morphological characteristics. So, it is needed to be extracted by signal processing method because there are not visible of graphical ECG signal. In this paper, an improved wavelet method has been proposed to extract the precise detection of small abnormalities of both simulated normal and noise corrupted ECG signal by writing MATLAB program. The proposed wavelet method found to be more summarized over conventional FFT and Wavelet in finding the small abnormalities of ECG signal.