FIR Cutoff Frequency Calculating for ECG Signal Noise Removing Using Artificial Neural Network

In this paper, an automated approach for electrocardiogram (ECG) signal noise removing using artificial neural network is investigated. First, 150 of noisy heart signal are collected form MIT-BIH database. Then signals are transformed to frequency domain and cutoff frequency is calculated. Since heart signals are lowpass frequency, a Finite Impulse Response (FIR) filter is adequate to remove the noise. In the next step, a dataset is configured for a multilayer perceptron (MLP) training with feedforward algorithm. Finally, the MLP is trained and results of cutoff frequency calculation are shown.