Congestive
Heart Failure is a growing menace spreading its jaws worldwide. As for all
diseases, early detection of the disease is the key to thwart the rampagecaused by the disease.
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| Cardiac Dysfunction |
With the
existent diagnostic devices and methodologies, cost of diagnosis is high and
some are painful due to their invasive nature. This has led us to apply
non-linear methods for analysis of ECG signals and formulate biomarkers. Analysis
of cardiac signals using fractal analysis has gained sufficient momentum over
the past few years. In this article the cardiac dynamics of ECG data are
explored with chaos based non-linear time series analysis techniques -- Hurst
exponent and Power of scale freeness in Visibility Graph PSVG. The ECG data of
normal subjects and CHF subjects are taken from Physionet database and analyzed
with these techniques to calculate values of Hurst Exponent and PSVG.
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