QRS Detection in ECG Signal and De-noising using Biorthogonal DWT Technique

Noise is the most deterrent in signal transmission and processing. It results in faulty information after processing the signals, henceforth reducing its usability. In our work, Biorthogonal Wavelet was used to filter out the noise by implementing a cascade of low pass and high pass filter. The motivation of this research work was derived from the quest to develop wavelet based filters for ECG signal filtering with better results as compared to FIR filters. Electrocardiogram (ECG) signal has been widely used for heart diagnosis. This algorithm and architectural level approach has been implemented on the Field Programmable Gate Array (FPGA). The main focus of the work is to filter and detect the QRS complex in ECG signal and to identify the time and frequency variations. By comparing these variations with that of the variations in the normal ECG waveform one may reach to the conclusion if the patient is suffering from Arrhythmia or not.