Biomedical digital signal processing: C-language examples and laboratory experiments for the IBM PC
Biomedical digital signal processing: C-language examples and laboratory experiments for the IBM PC
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QRS and ventricular beat detection is a basic procedure for electrocardiogram (ECG) processing and analysis. Large variety of methods have been proposed and used, featuring high percentages of correct detection. Nevertheless, the problem remains open especially with respect to higher detection accuracy in noisy ECGs. LabVIEW (Laboratory Virtual Instrument Engineering Workbench) is a graphical programming language that uses icons instead of lines of text to create programs. We developed in LabVIEW the filtering for removal of artifacts in biomedical signals and the Pan-Tompkins algorithm. We have investigated problems posed by artifact, noise and interference of various forms in the acquisition and analysis of several biomedical signals. We have also established links between the characteristics of certain epochs in a number of biomedical signals and the corresponding physiological or pathological events in the biomedical systems of concern. Event detection is an important step that is required before we may attempt to analyze the corresponding waves in more detail. A real-time detection method is proposed, based on comparison between absolute values of summed differentiated electrocardiograms of one of more ECG leads and adaptive threshold. Also, a cardiac beat recognition based on continuous wavelet transform is presented.