Preictal Time Assessment using Heart Rate Variability Features in Drug-resistant Epilepsy Patients

Epileptic seizures are by default associated with the occurrence of EEG changes as a consequence of alterations in brain activity seconds to hours before the seizure onset. Additionally, the influence of the autonomic nervous system may also be reflected in the electrocardiogram (ECG) trace. In both biosignals (EEG and ECG), differences have been reported between normal epochs, known as interictal periods and the interval preceding seizures, preictal period. However, the existence of a preictal state indicating the transition between epileptic brain states has not yet been clinically defined. In fact, some studies report differences in preictal location and duration among patients and among seizures occurring in the same patient as well. Based on the above, a study was designed in order to investigate the existence of a preictal interval specific for each seizure, using heart rate variability (HRV) features. Time and frequency domain features (linear and non-linear) were extracted from ECG data acquired in 37 drug-resistant epilepsy patients, comprised in EPILEPSIAE database. A total of 209 seizures occurring in the temporal lobe were analysed. The existence of a transition period before the seizure onset was inspected using a linear discriminant analysis classifier. The overall best performance (88.04%±12.30% of accuracy) was obtained by combining RRMean, NN50 and SD₂ features when discriminating the 50 min of interictal located farthest from seizure onset from the nearest preictal 50 min.