LEAST-SQUARE LINEAR PHASE FIR ELECTRO CARDIO GRAPHY (ECG) SIGNAL ANALYSIS

Signal processing methodology to analyze Electrocardiography (ECG) signals is proposed in this paper. Discrete Wavelet Transform (DWT) is employed as a feature extraction tool to achieve efficient design, and to overcome the limitations of previous methodologies like Fast Fourier Transform (FFT) and Short Time Fourier Transform (STFT). Least-Square Linear Phase FIR filtering denoising methodology is presented in this design to suppress baseline wander noise. Feed forward neural network methodology is used as the classifier to analyze the ECG signal from the myocardium. The proposed design is implemented on FPGA with low resources utilization, and achieving overall accuracy of 97.78 % for classifying ECG signals