With the advancement in artificial intelligence (AI) and machine learning (ML) techniques,
researchers are striving towards employing these techniques for advancing clinical practice …

Many complex and interesting phenomena in nature are due to nonlinear phenomena. The
theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a …

The electroencephalogram (EEG) has proven a valuable tool in the study and detection of
epilepsy. This paper investigates for the first time the use of Permutation Entropy (PE) as a …

The sudden and apparently unpredictable nature of seizures is one of the most disabling
aspects of the disease epilepsy. A method capable of predicting the occurrence of seizures …

Recent research has investigated the possibility of predicting epileptic seizures. Intervention
before the onset of seizure manifestations could be envisioned with accurate seizure …

Today, neuroimaging techniques are frequently used to investigate the integration of
functionally specialized brain regions in a network. Functional connectivity, which quantifies …

Research in seizure prediction has come a long way since its debut almost 4 decades ago.
Early studies suffered methodological caveats leading to overoptimistic results and lack of …

Objective: An important issue in epileptology is the question whether information extracted
from the EEG of epilepsy patients can be used for the prediction of seizures. Several studies …

The brain is in a constant state of dynamic change, for example switching between cognitive
and behavioural tasks, and between wakefulness and sleep. The brains of people with …

The exact mechanisms leading to the occurrence of epileptic seizures in humans are still
poorly understood. It is widely accepted, however, that the process of seizure generation is …