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 …

Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain
signals produced by brain neurons. Neurons are connected to each other in a complex way …

Since the manual detection of electrographic seizures in continuous electroencephalogram
(EEG) monitoring is very time-consuming and requires a trained expert, attempts to develop …

Electroencephalography (EEG) is the most popular brain activity recording technique used
in wide range of applications. One of the commonly faced problems in EEG recordings is the …

Deep brain stimulation (DBS) is an effective treatment for common movement disorders and
has been used to modulate neural activity through delivery of electrical stimulation to key …

Sleep stage classification is one of the most critical steps in effective diagnosis and the
treatment of sleep-related disorders. Visual inspection undertaken by sleep experts is a time …

Abstract Machine learning (ML) methods have the potential to automate clinical EEG
analysis. They can be categorized into feature-based (with handcrafted features), and end-to …

Closed-loop neural interfaces with on-chip machine learning can detect and suppress
disease symptoms in neurological disorders or restore lost functions in paralyzed patients …

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 …

Cerebrocortical injuries such as stroke are a major source of disability. Maladaptive
consequences can result from post-injury local reorganization of cortical circuits. For …