Analysis of Cardiac Beats using Higher Order Spectra

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dc.contributor.authorKaraye, Ibrahim Abdullahi
dc.contributor.authorSaminu, Sani
dc.contributor.authorÖzkurt, Nalan
dc.date.accessioned2022-01-10T10:27:10Z
dc.date.available2022-01-10T10:27:10Z
dc.date.issued2014-10-29
dc.description.abstractFor early diagnosis of the heart failures, the electrocardiography (ECG) is the most common method because of its simplicity and cost. Computer based analysis of ECG provides reliable and efficient tools in diagnostics of arrhythmias. With this objective there are lots of studies on automatic and semi-automatic ECG analysis. Like many biosignals, ECG signals are nonlinear in nature, higher order spectral analysis (HOS) is known to be a very good tool for the analysis of nonlinear systems producing good noise immunity. Thus in this study, HOS analysis of ECG signals of normal heart rate, right bundle branch block, paced beat, left bundle block branch and atrial premature beats have been studied in order to reveal the complex dynamics of ECG signals using the tools of nonlinear systems theory. Some of the general characteristics for each of these classes in the bispectrum and bicoherence plot for visual observation have been presented. For the extraction of RR intervals, well known Pan-Tompkins algorithm has been used and three higher order statistical parameters of skewness, kurtosis and variance from these features have been computed. These features with statistical parameters fed into artificial neural network classifier (ANN) and obtained an average accuracy of 94.9%.en_US
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/7277
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectECGen_US
dc.subjectHOSen_US
dc.subjectBispectrumen_US
dc.subjectBicoherenceen_US
dc.subjectPan Tompkinsen_US
dc.titleAnalysis of Cardiac Beats using Higher Order Spectraen_US
dc.typeArticleen_US
dc.typePresentationen_US

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