The abnormal condition of electrical activity of the heart given by ECG (Electrocardiogram) shows the cardiac diseases affecting the human being. The P, QRS, T wave shape, amplitude and time intervals between its various peaks contains useful information about the nature of disease. This paper presents wavelet technique to analyze ECG signal. Discrete Wavelet Transform (DWT) is employed as noise removal and feature extraction tool to achieve efficient design. Daubechies wavelet of order 10 has been designed using Verilog Hardware Description Language (HDL) and ModelSim Altera 6.4a is used as simulator. MIT BIH database has been used for the analysis.