Prediction of epileptic seizures based on multivariate multiscale modified-distribution entropy.

ABSTRACT: Epilepsy is a common neurological disease that affects a wide range of the world population and is not limited by age. Moreover, seizures can occur anytime and anywhere because of the sudden abnormal discharge of brain neurons, leading to malfunction. The seizures of approximately 30% of epilepsy patients cannot be treated with medicines or surgery; hence these patients would benefit from a seizure prediction system to live normal lives. Thus, a system that can predict a seizure before its onset could improve not only these patients' social lives but also their safety. Numerous seizure prediction methods have already been proposed, but the performance measures of these methods are still inadequate for a complete prediction system. Here, a seizure prediction system is proposed by exploring

SUBMITTER: Aung ST 

PROVIDER: S-EPMC8530096 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature