Heartbeat Electrocardiogram (ECG) Signal Feature Extraction Using Discrete Wavelet Transforms (DWT)

ECG is a method 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. In this paper, discrete wavelet transform (DWT) will be used to extract the relevant information from the ECG input data in order to perform the classification task. Previous study suggests DWT-based feature extraction technique yields better data. The Wavelet transform is a two-dimensional timescale processing method. DWT is suitable for the nonstationary ECG signals as it has adequate scale values and shifting in time. The data will then be analyzed and classified using neuro-fuzzy which is a hybrid of artificial neural networks and fuzzy logic. Keyword : Electrocardiogram (ECG), DWT, Neuro Fuzzy.