Electroencephalography (EEG) is a non-invasive measurement method for brain activity.
Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural …

Brain-machine interfaces are promising tools to restore lost motor functions and probe brain
functional mechanisms. As the number of recording electrodes has been exponentially …

Epilepsy is a health problem that seriously affects the quality of humans for many years.
Therefore, it is important to accurately analyze and recognize epilepsy based on EEG …

This paper presents a patient‐specific epileptic seizure predication method relying on the
common spatial pattern‐(CSP‐) based feature extraction of scalp electroencephalogram …

To recognize the user's motion intention, brain-machine interfaces (BMI) usually decode
movements from cortical activity to control exoskeletons and neuroprostheses for daily …

Classifying single-trial electroencephalogram (EEG) based motor imagery (MI) tasks is
extensively used to control brain-computer interface (BCI) applications, as a communication …

Closed-loop stimulation of many neurological disorders, such as epilepsy, is an emerging
technology and regarded as a promising alternative for surgical and drug treatment. In this …

Epilepsy is one of the most common neurological disorders in the world. Prompt detection of
seizure onset from electroencephalogram (EEG) signals can improve the treatment of …

This paper presents a novel method for seizure onset detection using fused information
extracted from multichannel electroencephalogram (EEG) and single-channel …

Background and objectives Epileptic seizure prediction using EEG signal analysis is an
important application for drug therapy and pediatric patient monitoring. Time series …