A study on ECG signal characterization and practical implementation of some ECG characterization techniques

The role of ECG is pivotal in medical field for the analysis of cardiac physiology and abnormalities. The interpretation of ECG signal is performed by signal processing algorithms for diagnosis of cardiac diseases. This work analyses filtering approaches, component extraction, classification and compression algorithms for the ECG signal. The portable ECG systems are also analysed; results and discussion comprises of IIR notch filter for the removal of power line interference, hybrid wavelet filter for removal of baseline wander, FFT algorithm for R peak detection and hybrid filtering approach for the detection of P, QRS and T components. The outcome of this research work is an aid for researchers developing novel algorithms in ECG filtering, segmentation and classification. The algorithms are developed in Matlab 2015b and tested on fantasia database data sets.