Epileptic Seizure: A New Approach for Quantification of Autonomic Deregulation with Chaos Based Technique

Background: Epileptic seizures can lead to changes in autonomic function affecting the sympathetic, parasympathetic and enteric nervous systems. Changes in cardiac signals are potential biomarkers that may provide an extracerebral indicator of ictal onset in some patients. Patients suffering from epilepsy experience some significant cardiac changes during seizure, causing some serious cardiac malfunctions which may lead to sudden unexpected death (SUDEP). The fluctuations observed in the heart rate during the process are non-linear and extremely complex. Chaos based non-linear methodology has become a very powerful tool in recent years in analysing such complex systems. Although a few papers on effect of seizure have been reported where study was done to assess the dynamics of cardiac systems for post-ictal patients not using non-linear technique, this paper reports the analysis of ECG signals of post-ictal patients using a modern and rigorous non-linear technique. Methods and findings: Multifractal detrended fluctuation analysis (MFDFA) technique has been applied here to determine the degree of multifractality of cardiac dynamics quantitatively of five women patients suffering from partial seizures. The analysis of the ECG clinical data obtained from ‘PhysioNet’ database shows that the degree of multifractality or complexity for each subject is different indicating the difference of severity of occurrences of seizure. Conclusion: The study reveals that the degree of autonomic deregulation can be quantified with the help of two parameters, the multifractal width and the autocorrelation exponent.