AIMC Topic: Electroencephalography

Clear Filters Showing 861 to 870 of 2123 articles

A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram.

International journal of environmental research and public health May 23, 2022
The classification of sleep stages is an important process. However, this process is time-consuming, subjective, and error-prone. Many automated classification methods use electroencephalogram (EEG) signals for classification. These methods do not cl...
Sleep Stages Neural Networks, Computer Deep Learning Electroencephalography Sleep
View on PubMed DOI

A Bimodal Deep Learning Architecture for EEG-fNIRS Decoding of Overt and Imagined Speech.

IEEE transactions on bio-medical engineering May 19, 2022
OBJECTIVE: Brain-computer interfaces (BCI) studies are increasingly leveraging different attributes of multiple signal modalities simultaneously. Bimodal data acquisition protocols combining the temporal resolution of electroencephalography (EEG) wit...
Electroencephalography Brain-Computer Interfaces Deep Learning Speech Humans Neural Networks, Computer
View on PubMed DOI

Multimodal Vigilance Estimation Using Deep Learning.

IEEE transactions on cybernetics May 19, 2022
The phenomenon of increasing accidents caused by reduced vigilance does exist. In the future, the high accuracy of vigilance estimation will play a significant role in public transportation safety. We propose a multimodal regression network that cons...
Wakefulness Electrooculography Deep Learning Electroencephalography
View on PubMed DOI

Spatial-frequency-temporal convolutional recurrent network for olfactory-enhanced EEG emotion recognition.

Journal of neuroscience methods May 16, 2022
BACKGROUND: Multimedia stimulation of brain activity is important for emotion induction. Based on brain activity, emotion recognition using EEG signals has become a hot issue in the field of affective computing.
Emotions Electroencephalography Attention Humans Neural Networks, Computer
View on PubMed DOI

Deep-learning-based seizure detection and prediction from electroencephalography signals.

International journal for numerical methods in biomedical engineering May 13, 2022
Electroencephalography (EEG) is among the main tools used for analyzing and diagnosing epilepsy. The manual analysis of EEG must be conducted by highly trained clinicians or neuro-physiologists; a process that is considered to have a comparatively lo...
Electroencephalography Epilepsy Neural Networks, Computer Deep Learning Seizures Humans
View on PubMed DOI

A neuroscience-inspired spiking neural network for EEG-based auditory spatial attention detection.

Neural networks : the official journal of the International Neural Network Society May 11, 2022
Recent studies have shown that alpha oscillations (8-13 Hz) enable the decoding of auditory spatial attention. Inspired by sparse coding in cortical neurons, we propose a spiking neural network model for auditory spatial attention detection. The prop...
Neural Networks, Computer Neurons Models, Neurological Attention Electroencephalography
View on PubMed DOI

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

IEEE transactions on neural networks and learning systems May 2, 2022
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...
Neural Networks, Computer Algorithms Humans Evoked Potentials, Visual Electroencephalography Photic Stimulation Brain-Computer Interfaces Robotics
View on PubMed DOI

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 May 2, 2022
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...
Brain-Computer Interfaces Brain Neural Networks, Computer Anesthetics Electroencephalography Deep Learning Humans Anesthesia Algorithms
View on PubMed DOI

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

Sleep medicine Apr 30, 2022
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...
Electroencephalography Humans Support Vector Machine Sleep Initiation and Maintenance Disorders Brain Magnetic Resonance Imaging
View on PubMed DOI

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

Computers in biology and medicine Apr 28, 2022
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...
Deep Learning Electroencephalography Schizophrenia Neural Networks, Computer Humans Brain
View on PubMed DOI
Popular Topics
Recent Journals