Dwt - Based Feature Extraction from ecg Signal

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.