Background Seizure prediction would be clinically useful in patients with epilepsy and could
improve safety, increase independence, and allow acute treatment. We did a multicentre …

Diagnosing depression in the early curable stages is very important and may even save the
life of a patient. In this paper, we study nonlinear analysis of EEG signal for discriminating …

A novel patient-specific seizure prediction method based on the analysis of positive zero-
crossing intervals in scalp electroencephalogram (EEG) is proposed. In a moving-window …

Great effort has been made toward defining and characterizing the pre-ictal state. Many
studies have pursued the idea that there are recognizable electrographic (EEG-based) …

Combining multiple linear univariate features in one feature space and classifying the
feature space using machine learning methods could predict epileptic seizures in patients …

Understanding how populations of neurons encode information is the challenge faced by
researchers in the field of neural coding. Focusing on the many mysteries and marvels of the …

Epilepsy is one of the most common neurological disorders, characterized by recurrent
seizures. Being able to predict impending seizures could greatly improve the lives of …

Epilepsy is not a disease in and of itself, but rather is a state of the brain characterised by
recurrent epileptic events that occur as a result of chronic structural or functional changes in …

Accurate localization of the epileptic seizure onset zones (SOZs) is crucial for successful
surgery, which usually depends on the information obtained from intracranial …

Background Brain computer interfaces (BCI) is one of the most popular branches in
biomedical engineering. It aims at constructing a communication between the disabled …