Abstract

Heart diseases, which are one of the death reasons, are among the several serious problems in this century and as per the latest survey, 60% of the patients die due to Heart problems. These diseases can be diagnosed by ECG (Electrocardiogram) signals. ECG measures electrical potentials on the body surface via contact electrodes thus it is very important signal in cardiology. Different artifacts affect the ECG signals which can thus cause problems in analyzing the ECG Thus signal processing schemes are applied to remove those interferences. The work proposed in this paper is removal of low frequency interference i.e. baseline wandering in ECG signal and digital filters are designed to remove it. The digital filters designed are FIR with different windowing methods as of Rectangular, Gaussian, Hamming, and Kaiser. The results obtained are at a low order of 56. The signals are taken from the MIT-BIH database which includes the normal and abnormal waveforms. The work has been done in MAT LAB environment where filters are designed in FDA Tool. The parameters are selected such that the noise is removed permanently. Also the best results are obtained at an order of 56 which makes hardware implementation easier. The result obtained for all FIR filters with different windows are compared by comparing the waveforms and power spectrums of the original and filtered ECG signals. The filters which gives the best results is the one using Kaiser Window.

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