Removal of noise from electrocardiogram using digital FIR and IIR filters with various methods

Abstract

Electrocardiogram (ECG) is a type of measuring the electrical activities of heart. Each section of ECG is necessary for the diagnosis of various cardiac problems. But the amplitude and time period of ECG signal is generally corrupted by various noises. After an analog ECG signal is transformed into digital format, appropriate digital filter can be utilized to repress the various kinds of noise like Baseline Wander, Power line Interference, High -frequency Noise, Physiological Artifacts etc., depends on their specifications. In generic two types of method can be classified in this paper; FIR filters like Rectangular, Hann, Blackman, Hamming and Kaiser window techniques and IIR filters like Butterworth, Chebyshev I, Chebyshev II and Elliptic filters are also prospected to reduce artifacts in ECG signal. The results are collected from different orders for FIR filter as 56, 300, 450, and 600 and for IIR filter as 1, 2, and 3. The signals taken from the MIT-BIH data base which contains the normal and abnormal waveforms. The work has been implemented in MATLAB FDA Tool. The results are obtained using different window based FIR filters, IIR filter with different approximation methods and their respective waveforms are shown. In addition, power spectrum density, signal to noise ratio (SNR) and means square error (MSE) of both noisy and filtered ECG signals are calculated. We observed that Digital FIR filter with Kaiser Window in order 56 shows high performance as compared to the other windowing techniques and Digital IIR filter approximation methods.