Analyzing ElectroCardioGraphy Signals using Least-Square Linear Phase FIR Methodology

This paper presents a signal processing methodology to analyze Electrocardiography (ECG) signals. Discrete Wavelet Transform (DWT) is used as a feature extraction methodology to achieve efficient design. Baseline wandering noise is removed in this design using Lest-Square Linear Phase FIR methodology. ECG signals classification is done using Feed forward neural network methodology. An accuracy of 100% in identifying the normal samples, and accuracy of 95.23% for identifying abnormal ECG beats are obtained, achieving a total accuracy of 97.78% for identifying ECG signals using this presented methodology.