AIMC Topic: Electroencephalography

Clear Filters Showing 361 to 370 of 2116 articles

Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models.

Neuroinformatics Sep 10, 2024
Theta oscillations, ranging from 4-8 Hz, play a significant role in spatial learning and memory functions during navigation tasks. Frontal theta oscillations are thought to play an important role in spatial navigation and memory. Electroencephalograp...
Male Electroencephalography Markov Chains Spatial Navigation Theta Rhythm Female Young Adult Adult Machine Learning Brain Learning Humans
View on PubMed DOI

Automatic Recognition of Multiple Emotional Classes from EEG Signals through the Use of Graph Theory and Convolutional Neural Networks.

Sensors (Basel, Switzerland) Sep 10, 2024
Emotion is a complex state caused by the functioning of the human brain in relation to various events, for which there is no scientific definition. Emotion recognition is traditionally conducted by psychologists and experts based on facial expression...
Neural Networks, Computer Algorithms Brain Humans Brain-Computer Interfaces Emotions Electroencephalography Signal Processing, Computer-Assisted
View on PubMed DOI

Intelligent Control System for Brain-Controlled Mobile Robot Using Self-Learning Neuro-Fuzzy Approach.

Sensors (Basel, Switzerland) Sep 10, 2024
Brain-computer interface (BCI) provides direct communication and control between the human brain and physical devices. It is achieved by converting EEG signals into control commands. Such interfaces have significantly improved the lives of disabled i...
Brain-Computer Interfaces Fuzzy Logic Humans Robotics Neural Networks, Computer Electroencephalography Machine Learning Algorithms Brain
View on PubMed DOI

Deep Learning-Based Artificial Intelligence Can Differentiate Treatment-Resistant and Responsive Depression Cases with High Accuracy.

Clinical EEG and neuroscience Sep 9, 2024
Although there are many treatment options available for depression, a large portion of patients with depression are diagnosed with treatment-resistant depression (TRD), which is characterized by an inadequate response to antidepressant treatment. Id...
Adult Male Middle Aged Neural Networks, Computer Artificial Intelligence Female Antidepressive Agents Depressive Disorder, Treatment-Resistant Deep Learning Depression Electroencephalography Humans
View on PubMed DOI

Siamese based deep neural network for ADHD detection using EEG signal.

Computers in biology and medicine Sep 9, 2024
BACKGROUND: Detecting Attention-Deficit/Hyperactivity Disorder (ADHD) in children is crucial for timely intervention and personalized treatment.
Deep Learning Brain Adolescent Attention Deficit Disorder with Hyperactivity Female Child Humans Electroencephalography Male Signal Processing, Computer-Assisted Neural Networks, Computer
View on PubMed DOI

A Comprehensive Review of Hardware Acceleration Techniques and Convolutional Neural Networks for EEG Signals.

Sensors (Basel, Switzerland) Sep 7, 2024
This paper comprehensively reviews hardware acceleration techniques and the deployment of convolutional neural networks (CNNs) for analyzing electroencephalogram (EEG) signals across various application areas, including emotion classification, motor ...
Humans Neural Networks, Computer Wearable Electronic Devices Electroencephalography Epilepsy Signal Processing, Computer-Assisted
View on PubMed DOI

HEMAsNet: A Hemisphere Asymmetry Network Inspired by the Brain for Depression Recognition From Electroencephalogram Signals.

IEEE journal of biomedical and health informatics Sep 5, 2024
Depression is a prevalent mental disorder that affects a significant portion of the global population. Despite recent advancements in EEG-based depression recognition models rooted in machine learning and deep learning approaches, many lack comprehen...
Humans Electroencephalography Neural Networks, Computer Signal Processing, Computer-Assisted Brain Depression
View on PubMed DOI

PSEENet: A Pseudo-Siamese Neural Network Incorporating Electroencephalography and Electrooculography Characteristics for Heterogeneous Sleep Staging.

IEEE journal of biomedical and health informatics Sep 5, 2024
Sleep staging plays a critical role in evaluating the quality of sleep. Currently, most studies are either suffering from dramatic performance drops when coping with varying input modalities or unable to handle heterogeneous signals. To handle hetero...
Electrooculography Sleep Stages Middle Aged Electroencephalography Signal Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans Female Young Adult Adult Male
View on PubMed DOI

EEGDepressionNet: A Novel Self Attention-Based Gated DenseNet With Hybrid Heuristic Adopted Mental Depression Detection Model Using EEG Signals.

IEEE journal of biomedical and health informatics Sep 5, 2024
World Health Organization (WHO) has identified depression as a significant contributor to global disability, creating a complex thread in both public and private health. Electroencephalogram (EEG) can accurately reveal the working condition of the hu...
Humans Depression Electroencephalography Signal Processing, Computer-Assisted Heuristics Neural Networks, Computer Algorithms Deep Learning
View on PubMed DOI

ABR-Attention: An Attention-Based Model for Precisely Localizing Auditory Brainstem Response.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 5, 2024
Auditory Brainstem Response (ABR) is an evoked potential in the brainstem's neural centers in response to sound stimuli. Clinically, characteristic waves, especially Wave V latency, extracted from ABR can objectively indicate auditory loss and diagno...
Adult Female Acoustic Stimulation Male Electroencephalography Reproducibility of Results Evoked Potentials, Auditory, Brain Stem Deep Learning Reaction Time Young Adult Humans Attention Neural Networks, Computer Algorithms
View on PubMed DOI
Popular Topics
Recent Journals