Analysis of Cardiac Beats using Higher Order Spectra
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Date
2014-10-29
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
For 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%.
Description
Keywords
ECG, HOS, Bispectrum, Bicoherence, Pan Tompkins