%0 Journal Article
%T Dwt - Based Feature Extraction from ecg Signal
%A V.K.Srivastava
%J American Journal of Engineering Research
%D 2013
%I American Journal of Engineering Research
%X Electrocardiogram is used to measure the rate and regularity of heartbeats to detect any irregularity to the heart. An ECG translates the heart electrical activity into wave-line on paper or screen. For the feature extraction and classification task we will be using discrete wavelet transform (DWT) as wavelet transform is a two-dimensional timescale processing method, so it is suitable for the non-stationary ECG signals(due to adequate scale values and shifting in time). Then the data will be analyzed and classified using neuro-fuzzy which is a hybrid of artificial neural networks and fuzzy logic.
%K Electrocardiogram (ECG)
%K DWT
%K Neuro Fuzzy.
%U http://www.ajer.org/papers/v2(3)/G0234450.pdf