In the previous decade, breakthroughs in the central nervous system bioinformatics and
computational innovation have prompted significant developments in brain–computer …

Constructing reliable and effective models to recognize human emotional states has
become an important issue in recent years. In this article, we propose a double way deep …

Epilepsy is a neurological disease caused by ab-normal neural electrical discharges.
Electroencephalography (EEG) is a powerful tool to measure the brain electrical activity and …

Machine learning algorithms for seizure detection have shown great diagnostic potential,
with recent reported accuracies reaching 100%. However, few published algorithms have …

Background and objective Epilepsy is a brain disorder consisting of abnormal electrical
discharges of neurons resulting in epileptic seizures. The nature and spatial distribution of …

Constructing an efficient and accurate epilepsy detection system is an urgent research task.
In this paper, we developed an EEG-based multi-frequency multilayer brain network …

Effective description of the brain function after stroke is the key to accurate rehabilitation
assessment, and it is of great significance to explore the nonlinear complexity characteristics …

Research on the electroencephalogram-electromyo-gram (EEG-EMG) functional network is
of great significance for exploring the correlation and diagnosing neurological diseases …

Electroencephalogram (EEG) has emerged as the most favorable source for recognizing
brain disorders like epileptic seizure (ES) using deep learning (DL) methods. This study …

Childhood epilepsy seriously affects the nervous system development of children.
Electroencephalogram (EEG) based epilepsy analysis is common in the past, but the …