Electrocardiogram (ECG), a non-invasive recording method of bioelectric signal originated in the heart, provides valuable information about the electrical activity of human heart during its contraction and expansion. It is one of the important tools used by medical practitioners to examine the pathological condition of the heart. Different features of the ECG can be extracted from the intervals and amplitudes of these waves at different sections. But it becomes difficult if it is corrupted by noise during acquisition. Thus, noise removal becomes an essential part in ECG preprocessing for better performance in ECG analysis and characterization. Many denoising techniques have been reported in the literature for ECG denoising such as adaptive filtering, wavelet denoising etc,.In this project noisy ECG signal is initially decomposed into a set of Intrinsic Mode Functions (IMFs) using EMD adaptive Filter The Empirical Mode Decomposition (EMD) is becoming a multi-scale analysis of signals. This method breaks down a signal without leaving the time.