Functional Brain Network Based on Improved Ensemble Empirical Mode Decomposition of EEG for Anxiety Analysis and Detection

Information Science, Artificial Intelligence, Medicine, Psychiatry, Neurology, Medical Imaging, Life Sciences, Biophysics,
Functional Brain Network   EEG   Anxiety   Improved Ensemble Empirical Mode Decomposition   Support Vector Machine   Phase Lag Index  

Brain Functional Network for Anxiety Analysis and Detection Based on Improved Ensemble Empirical Mode Decomposition Academic Background and Research Objectives With the increasing stress of modern life, anxiety, a common neurological disorder, has become an urgent issue in global public health. Anxiety not only manifests as mental disorders but als...

Deep Learning-Based Assessment Model for Real-Time Identification of Visual Learners Using Raw EEG

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Bioengineering,
deep learning   real-time identification   visual learners   EEG   machine learning   electroencephalogram   classification  

In the current educational environment, understanding students’ learning styles is crucial for improving their learning efficiency. Specifically, the identification of visual learning styles can help teachers and students adopt more effective strategies in the teaching and learning process. Currently, automatic identification of visual learning sty...

ADFCNN: Attention-Based Dual-Scale Fusion Convolutional Neural Network for Motor Imagery Brain–Computer Interface

ADFCNN: Attention-Based Dual-Scale Fusion Convolutional Neural Network for Motor Imagery Brain–Computer Interface

Information Science, Automation, Artificial Intelligence, Medicine, Neurology, Life Sciences, Bioengineering,
Attention   Dual-Scale Fusion   Convolutional Neural Network   Motor Imagery   Brain-Computer Interface   EEG   Self-Attention Mechanism  

Brain-Computer Interface (BCI) has emerged as an enhanced communication and control technology in recent years. In BCI based on electrophysiological characteristics (such as Electroencephalogram, EEG), Motor Imagery (MI) is an important branch that decodes users’ motor intentions for use in clinical rehabilitation, intelligent wheelchair control, c...

Changes in Brain Functional Networks Induced by Visuomotor Integration Task

Engineering, Electrical Engineering, Information Science, Electronic Information, Medicine, Neurology,
visuomotor integration   EEG   connectivity   functional networks   dominant hand   non-dominant hand   electroencephalographic  

Frequency-Specific Reorganization of Brain Networks during Visuomotor Tasks Research Background Executing movements is a complex cognitive function that relies on the coordinated activation of spatially proximal and distal brain regions. Visuomotor integration tasks require processing and interpreting visual inputs to plan motor execution and adjus...

GCTNet: A Graph Convolutional Transformer Network for Major Depressive Disorder Detection Based on EEG Signals

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Psychiatry, Neurology, Clinical Psychology, Medical Imaging,
Major Depressive Disorder   EEG   Deep Learning   Phase Locking Value   Contrastive Learning  

GCTNet: Graph Convolution Transformer Network for Detecting Major Depressive Disorder Based on EEG Signals Research Background Major Depressive Disorder (MDD) is a prevalent mental illness characterized by significant and persistent low mood, affecting over 350 million people worldwide. MDD is one of the leading causes of suicide, resulting in appr...