AIMC Topic: Electroencephalography

Clear Filters Showing 1011 to 1020 of 2295 articles

An MVMD-CCA Recognition Algorithm in SSVEP-Based BCI and Its Application in Robot Control.

IEEE transactions on neural networks and learning systems
This article proposes a novel recognition algorithm for the steady-state visual evoked potentials (SSVEP)-based brain-computer interface (BCI) system. By combining the advantages of multivariate variational mode decomposition (MVMD) and canonical cor...

Inference of Brain States Under Anesthesia With Meta Learning Based Deep Learning Models.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Monitoring the depth of unconsciousness during anesthesia is beneficial in both clinical settings and neuroscience investigations to understand brain mechanisms. Electroencephalogram (EEG) has been used as an objective means of characterizing brain a...

Insomnia disorder diagnosed by resting-state fMRI-based SVM classifier.

Sleep medicine
BACKGROUND: The main classification systems of sleep disorders are based on the subjective self-reported criteria. Objective measures are essential to characterize the nocturnal sleep disturbance, identify daytime impairment, and determine the course...

Detection of schizophrenia using hybrid of deep learning and brain effective connectivity image from electroencephalogram signal.

Computers in biology and medicine
Detection of mental disorders such as schizophrenia (SZ) through investigating brain activities recorded via Electroencephalogram (EEG) signals is a promising field in neuroscience. This study presents a hybrid brain effective connectivity and deep l...

Sleep staging classification based on a new parallel fusion method of multiple sources signals.

Physiological measurement
In the field of medical informatics, sleep staging is a challenging and time consuming task undertaken by sleep experts. The conventional method for sleep staging is to analyze Polysomnograms (PSGs) recorded in a sleep lab, but the sleep monitoring w...

Stress Classification Using Brain Signals Based on LSTM Network.

Computational intelligence and neuroscience
The early diagnosis of stress symptoms is essential for preventing various mental disorder such as depression. Electroencephalography (EEG) signals are frequently employed in stress detection research and are both inexpensive and noninvasive modality...

Task-State EEG Signal Classification for Spatial Cognitive Evaluation Based on Multiscale High-Density Convolutional Neural Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In this study, a multi-scale high-density convolutional neural network (MHCNN) classification method for spatial cognitive ability assessment was proposed, aiming at achieving the binary classification of task-state EEG signals before and after spati...

Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches large...

SCC-MPGCN: self-attention coherence clustering based on multi-pooling graph convolutional network for EEG emotion recognition.

Journal of neural engineering
The emotion recognition with electroencephalography (EEG) has been widely studied using the deep learning methods, but the topology of EEG channels is rarely exploited completely. In this paper, we propose a self-attention coherence clustering based ...

Key Feature Extraction Method of Electroencephalogram Signal by Independent Component Analysis for Athlete Selection and Training.

Computational intelligence and neuroscience
Emotion is an important expression generated by human beings to external stimuli in the process of interaction with the external environment. It affects all aspects of our lives all the time. Accurate identification of human emotional states and furt...