Wavelet transform is an effective tool for feature extraction, because this allows analysis of images at various levels of resolution. Consideringthe Discrete Wavelet Transform (DWT) based wavelet, de-noising has been incorporated using four different thresholding techniques to removethe three major sources of noises from the acquired ECG signals namely, power line interference, baseline wandering, and high frequency noises. SEVEN wavelet functions ("db1", "coif1","rbio1.1" , "dmey" , "bior1.1" ,"haar" and "sym1") and four different thresholding levels (at 0.0056, 0.0156, 0.0256 and 0.0356 levels) were utilised to denoise the ECG signals. This paper describes theway toprocesstheECGsignals(makethemnoisefree).