Signal De - nosing using Wavelet Transform from MIT - BIH Database

In recent years, there is a trend of automated analysis of biomedical signals. Analysis of real time patient’s data, picked up by various transducers or sensors is very important. Electrocardiographic (ECG) signals may be corrupted by various kinds of noise. Its processing has most demanding application in digital design concepts and practices. Signal processing is most important technology domain where the demand for enhanced performance and reduced resource application has increased exponentially over the years. Recently advances in FPGA design becomes the preferred platform for evaluating and implementing the signal processing algorithms and its utilization in real world problems. There are different methods to remove this noise like digital filters, adaptive filters. The paper presents the design and implementation of digital notch filter. The filter is implemented on ECG signal which is corrupted by the power line interference. The simulation results are presented in tabular form. But by considering the advantages of wavelet transform, this paper presents a wavelet based de-noising technique to remove power line interference from ECG signal. The wavelet transform is applied to the ECG signal so that wavelet coefficients are formed. Soft thresholding is applied to these coefficients which can remove noise due to power line interference. The proposed architecture can remove efficiently the power line interference from ECG signal.