Prediction of epileptic seizures based on heart rate variability.
BACKGROUND
Until now, different approaches have been published to resolve the problem of predicting epileptic seizures. The results are reminiscent of a substantial need for improvements in these methods to reach the stage of the clinical application. Our aim is to develop a reliable epileptic seizure prediction algorithm based on the Heart Rate Variability (HRV) analysis.


METHODS
We analyzed the HRV of sixteen epileptic patients with a total of 170 seizures, to predict the occurrence of seizures based on the dynamic changes of Electrocardiogram (ECG) during the pre-ictal period. Time and frequency-domain features were computed forthe consecutive time windows with a length of five minutes. An adaptive decision threshold method was used for raising alarms. Predictions were made when selected features exceeded the decision thresholds.


RESULTS
For the seizure occurrence period (SOP) of 4:30 minutes, and intervention time (IT) of 110 Sec, the presented method showed an average sensitivity of 78.59%, and average false prediction rate of 0.21/Hr, which indicates that the system has superiority to the random predictor.


CONCLUSIONS
The proposed approach shows a potential in the monitoring of epileptic patients and improving their life quality. The overall performance of the algorithm is a step forward for clinical implementation.
Department of Electrical Engineering, Islamic Azad University, South Tehran Branch, Iran.
Soroor
S
Behbahani
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Nader Jafarnia
NJ
Dabanloo
Department of Biomedical Engineering, Shahed University, Tehran, Iran.
Ali Motie
AM
Nasrabadi
Center for Informatics and Systems (CISUC), Department of Informatics Engineering, University of Coimbra, Portugal.
Antonio
A
Dourado
D000293:Adolescent; D000328:Adult; D000368:Aged; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000503:physiopathology*; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D055815:Young Adult
Epilepsy; HRV; circadian rhythm; prediction; threshold