AIMC Topic: Electroencephalography
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Enhanced EEG-based Alzheimer's disease detection using synchrosqueezing transform and deep transfer learning.
Neuroscience
Apr 24, 2025
The most prevalent type of dementia and a progressive neurodegenerative disease, Alzheimer's disease has a major influence on day-to-day functioning due to memory loss, cognitive decline, and behavioral problems. By using synchrosqueezing representat...
SS-EMERGE - self-supervised enhancement for multidimension emotion recognition using GNNs for EEG.
Scientific reports
Apr 24, 2025
Self-supervised learning (SSL) is a potent method for leveraging unlabelled data. Nonetheless, EEG signals, characterised by their low signal-to-noise ratio and high-frequency attributes, often do not surpass fully-supervised techniques in cross-subj...
EEG-based epilepsy detection using CNN-SVM and DNN-SVM with feature dimensionality reduction by PCA.
Scientific reports
Apr 24, 2025
This study focuses on epilepsy detection using hybrid CNN-SVM and DNN-SVM models, combined with feature dimensionality reduction through PCA. The goal is to evaluate the effectiveness and performance of these models in accurately identifying epilepti...
Data-driven sleep structure deciphering based on cardiorespiratory signals.
Computer methods and programs in biomedicine
Apr 23, 2025
BACKGROUND AND OBJECTIVE: Cardiorespiratory signals provide a novel perspective for understanding sleep structure through the physiological mechanism of cardiopulmonary coupling. This mechanism divides the coupling spectrum into high-frequency (HF) a...
Challenges and Opportunities: Nanomaterials in Epilepsy Diagnosis.
ACS nano
Apr 23, 2025
Epilepsy is a common neurological disorder characterized by a significant rate of disability. Accurate early diagnosis and precise localization of the epileptogenic zone are essential for timely intervention, seizure prevention, and personalized trea...
AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition.
IEEE transactions on cybernetics
Apr 23, 2025
The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions in electroencephalogram (EEG) topology and representations within and between individuals. However, current works primarily align the distributions of ...
Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.
IEEE transactions on cybernetics
Apr 23, 2025
The neural activity patterns of localized brain regions are crucial for recognizing brain intentions. However, existing electroencephalogram (EEG) decoding models, especially those based on deep learning, predominantly focus on global spatial feature...
HATNet: EEG-Based Hybrid Attention Transfer Learning Network for Train Driver State Detection.
IEEE transactions on cybernetics
Apr 23, 2025
Electroencephalography (EEG) is widely utilized for train driver state detection due to its high accuracy and low latency. However, existing methods for driver status detection rarely use the rich physiological information in EEG to improve detection...
Functional connectivity anomalies in medication-naive children with ADHD: Diagnostic potential, symptoms interpretation, and a mediation model.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Apr 18, 2025
OBJECTIVE: To identify reliable electroencephalography (EEG) biomarkers for attention deficit/hyperactivity disorder (ADHD) by investigating anomalous functional connectivity patterns and their clinical relevance.
Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients.
Journal of visualized experiments : JoVE
Apr 18, 2025
This study introduces a Brain-Computer Interface (BCI)-controlled upper limb assistive robot for post-stroke rehabilitation. The system utilizes electroencephalogram (EEG) and electrooculogram (EOG) signals to help users assist upper limb function in...
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