Fuzzy Generalized Fractal Dimensions Using Inter-Heartbeat Interval Dynamics in ECG Signals for Age Related Discrimination - Easwaramoorthy, D.; S. Eliahim Jeevaraj, P.; Gowrisankar, A.; Manimaran, A.; Nandhini, S. (International Journal of Engineering and Technology, 2018)
Fractal theory is the propelled technique to analyze the non-linear signals with more complexity.  Quantification of chaotic nature and complexity of the multifaceted therapeutic signals requires the estimation of the spectrum of Generalized Fractal Dimensions (GFD) where the complexity means greater inconstancy in the general form of fractal dimension range.  This paper has proposed a fuzzy multifractal technique to analyze the age related classifications by using the Fuzzy Generalized Fractal Dimensions (F–GFD) with Gaussian fuzzy valued function through the cardiac inter-beat interval dynamics in electrocardiogram (ECG) signals.  It has been revealed that, the designed Fuzzy GFD method accurately categorizes the young and old age subjects by graphical comparison with the typical GFD method.  The classification rate of young and elderly subjects has also supported statistically by ANOVA test.   Hence the fuzzified multifractal analysis accomplishes significantly to discriminate age groups than the classical multifractal analysis in heartbeat rate time series from ECG signals and also the conventional GFD is a specific case of the proposed F–GFD.