The paper is devoted to the study of EEG-based people verification. Analyzed solutions employed shallow artificial neural networks using spectral EEG features as input representation. We investigated the impact of the features derived from different ...
Motor Imagery Brain-Computer Interfaces (MI-BCIs) are AI-driven systems that capture brain activity patterns associated with mental imagination of movement and convert them into commands for external devices. Traditionally, MI-BCIs operate on Machine...
Computational intelligence and neuroscience
Jul 21, 2022
The efficient biological signal processing method can effectively improve the efficiency of researchers to explore the work of life mechanism, so as to better reveal the relationship between physiological structure and function, thus promoting the ge...
Although increasing evidences support the notion that psychiatric disorders are associated with abnormal communication between brain regions, scattered studies have investigated brain electrophysiological disconnectivity of patients with generalized ...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jul 19, 2022
Electrical status epilepticus during sleep (ESES) is an epileptic encephalopathy in children with complex clinical manifestations. It is accompanied by specific electroencephalography (EEG) patterns of continuous spike and slow-waves. Quantifying suc...
Healthy sleep is essential for the rejuvenation of the body and helps in maintaining good health. Many people suffer from sleep disorders that are characterized by abnormal sleep patterns. Automated assessment of such disorders using biomedical signa...
Depression is a global psychological disease that does serious harm to people. Traditional diagnostic method of the doctor-patient communication, is not objective and accurate enough. Thus, a more accurate and objective method for depression detectio...
IEEE transactions on neural networks and learning systems
Jul 6, 2022
This article addresses the problem of estimating brain effective connectivity from electroencephalogram (EEG) signals using a Granger causality (GC) characterized on state-space models, extended from the conventional vector autoregressive (VAR) proce...
IEEE transactions on neural networks and learning systems
Jul 6, 2022
Convolutional neural networks (CNNs) have recently been applied to electroencephalogram (EEG)-based brain-computer interfaces (BCIs). EEG is a noninvasive neuroimaging technique, which can be used to decode user intentions. Because the feature space ...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jul 4, 2022
In this study, we present a new Deep Learning (DL) architecture for Motor Imagery (MI) based Brain Computer Interfaces (BCIs) called EEGSym. Our implementation aims to improve previous state-of-the-art performances on MI classification by overcoming ...
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