Comparative analysis of different fractal methods in studying post-ictal ECG signals of epilepsy patient

Measuring EEG signals as a diagnostic tool for Epileptic patient is a well traveled way. Different non-linear statistical approaches have been applied over the past years on this signal to reveal the nature of connection between epilepsy and EEG. In this work we study the post-ictal ECG signals of epileptic patient collected from MIT-BIH database using mono-fractal methods as well as multifractal approach. We compare the results of the same statistical methods with healthy normal group. Result from monofractal analysis such as Rescaled range analysis indicates that the ECG signals of epileptic patients are anti-persistent in nature whereas for healthy normal people it is persistent. Detrended fluctuation analysis also confirms the same fact and declares that ECG signals of healthy normal people are more persistent and more correlated than epileptic patients. Finally we use the multifractal approach on the ECG signals. Result from the Multifractal detrended fluctuation analysis confirms that healthy normal people have higher degree of multifractality compared to epileptic patients.

[1]  H. E. Hurst,et al.  Long-Term Storage Capacity of Reservoirs , 1951 .

[2]  Bruce J. West,et al.  Fractal physiology , 1994, IEEE Engineering in Medicine and Biology Magazine.

[3]  H. Stanley,et al.  Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. , 1995, Chaos.

[4]  Jeffrey M. Hausdorff,et al.  Postictal heart rate oscillations in partial epilepsy. , 1999, Neurology.

[5]  H V Huikuri,et al.  Heart rate dynamics in refractory and well controlled temporal lobe epilepsy , 2002, Journal of neurology, neurosurgery, and psychiatry.

[6]  H. Stanley,et al.  Multifractal Detrended Fluctuation Analysis of Nonstationary Time Series , 2002, physics/0202070.

[7]  N. Kannathal,et al.  Complex dynamics of epileptic EEG , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  H V Huikuri,et al.  Suppressed circadian heart rate dynamics in temporal lobe epilepsy , 2005, Journal of Neurology, Neurosurgery & Psychiatry.

[9]  H. Huikuri,et al.  Cardiac Autonomic Control in Patients with Refractory Epilepsy before and during Vagus Nerve Stimulation Treatment: A One‐Year Follow‐up Study , 2006, Epilepsia.

[10]  L. Lagae,et al.  Cardiac changes in epilepsy , 2010, Seizure.

[11]  Sabine Van Huffel,et al.  Heart Rate Variability Analysis of Children with Refractory Epilepsy before and after the Vagus Nerve Stimulation , 2011, BIOSIGNALS.

[12]  Andre R Brunoni,et al.  A systematic review and meta-analysis of heart rate variability in epilepsy and antiepileptic drugs. , 2012, Epilepsia.

[13]  Vo Van Toi,et al.  Higuchi Fractal Properties of Onset Epilepsy Electroencephalogram , 2012, Comput. Math. Methods Medicine.