Epilepsy is among the most dynamic disorders in neurology. A canonical view holds that
seizures, the characteristic sign of epilepsy, occur at random, but, for centuries, humans …

Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …

Abstract Machine learning leverages statistical and computer science principles to develop
algorithms capable of improving performance through interpretation of data rather than …

Seizure prediction has attracted growing attention as one of the most challenging predictive
data analysis efforts to improve the life of patients with drug-resistant epilepsy and tonic …

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

Epilepsy is a common disorder characterized by recurrent seizures. An overwhelming
majority of people with epilepsy regard the unpredictability of seizures as a major issue …

Epilepsy is defined by the seemingly random occurrence of spontaneous seizures. The
ability to anticipate seizures would enable preventative treatment strategies. A central but …

Responsive neurostimulation (RNS) devices, able to detect imminent seizures and to rapidly
deliver electrical stimulation to the brain, are effective in reducing seizures in some patients …

Epilepsy seizure prediction paves the way of timely warning for patients to take more active
and effective intervention measures. Compared to seizure detection that only identifies the …

Objective: This paper investigates the hypothesis that focal seizures can be predicted using
scalp electroencephalogram (EEG) data. Our first aim is to learn features that distinguish …