A simple approach to determine loss of physiological complexity in heart rate series
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Date
2023
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Abstract
There are several ways to assess complexity, but no method has yet been developed for quantitatively calculating the ‘loss of fractal complexity’ under pathological or physiological states. In this paper, we aimed to quantitatively evaluate fractal complexity loss using a novel approach and new variables developed from Detrended Fluctuation Analysis (DFA) log-log graphics. Three study groups were established to evaluate the new approach: one for normal sinus rhythm (NSR), one for congestive heart failure (CHF), and white noise signal (WNS). ECG recordings of the NSR and CHF groups were obtained from PhysioNET Database and were used for analysis. For all groups Detrended Fluctuation Analysis scaling exponents (DFAα 1, DFAα 2) were determined. Scaling exponents were used to recreate the DFA log-log graph and lines. Then, the relative total logarithmic fluctuations for each sample were identified and new parameters were computed. To do this, we used a standard log-log plane to standardize the DFA log-log curves and calculated the differences between the standardized and expected areas. We quantified the total difference in standardized areas using parameters called dS1, dS2, and TdS. Our results showed that; compared to the NSR group, DFAα 1 was lower in both CHF and WNS groups. However, DFAα 2 was only reduced in the WNSgroup and not in the CHFgroup. Newly derived parameters: dS1, dS2, and TdS were significantly lowerin the NSR group compared to the CHF and WNS groups. The new parameters derived from the DFA log-log graphs are highly distinguishing for congestive heart failure and white noise signal. In addition, it may be concluded that a potential feature of our approach can be beneficial in classifying the severity of cardiac abnormalities. © 2023 IOP Publishing Ltd.
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Arrhythmias, Cardiac , Fractals , Heart Failure , Heart Rate , Humans , Cardiology , Fractals , White noise , Congestive heart failures , Detrended fluctuation analysis , Fractal complexity , Fractal complexity loss , Heart rate complexity , Heart rate variability , Heart-rate , Noise signals , Normal sinus rhythm , Scaling exponent , adult , aged , analysis , Article , clinical article , computer simulation , congestive heart failure , controlled study , data base , detrended fluctuation analysis , electrocardiogram , entropy , female , fractal analysis , fractal complexity loss , heart rate variability , human , male , parameters , relative total logarithmic fluctuation , RR interval , sinus rhythm , time series analysis , white noise signal , fractal analysis , heart arrhythmia , heart failure , heart rate , physiology , Heart