This paper proposes a novel method of identifying the time of epileptic seizure happening
on patients by employing feature extraction and machine learning-based classification on …

The closed-loop application of electrical stimulation via chronically implanted electrodes is a
novel approach to stop seizures in patients with focal-onset epilepsy. To this end, an energy …

This study investigates the properties of the brain electrical activity from different recording
regions and physiological states for seizure detection. Neurophysiologists will find the work …

Epileptic seizure is a neurological disorder characterized by abnormal synchronous
discharge of the neuronal activities in the brain structures. These abnormal electrical …

Purpose This work focuses on automated epileptic seizure diagnosis (ESD) and prediction
(ESP) to clarify the expanding role of machine learning (ML) in epileptic analysis. It outlines …

Epilepsy is a neurological disorder produced due to abnormal excitability of neurons in the
brain. The research reveals that brain activity is monitored through electroencephalogram …

Throughout the last decades there has been an increasing interest in analyzing the EEG
signals of epilepsy patients in order to relate it to epilepsy seizure onsets. Previous research …

Epilepsy is a common neurological disease that affects more than 2 percent of the
population globally. An imbalance in brain electrical activities causes unpredictable …

Neuronal activity analysis of the brain for epileptic seizure detection. This neuronal activity is
recorded in electroencephalogram (EEG) data. Present work focused on two temporal …

Epilepsy is a neurological condition that is rather common and is thought to afflict around 70
million individuals all over the globe. If epilepsy is to be monitored properly and successfully …