European Journal of Molecular & Clinical Medicine

Abstract

The Electro Cardio Gram (ECG) is a parametric index to diagnose heart diseases. During the process of acquisition of the ECG signals, it is added up by large amount of noise, which affects the patient diagnosis with respect to telemedicine. The noisy ECG signals have drift in baseline, motion electrodes artefacts, interference of line, muscle contraction noise, etc. Noise reduction is accomplished by making using of adaptive filter which employs wavelet transform. Computer simulation results are shown for the improvement in performance. This methodology adapted successfully removes various types of noise with Signal to noise ratio (SNR). The impact of noise and removal of it are shown in the waveforms and the methodology adopted has produced 82% improvement on the SNR of de-noised signals.