AIMC Topic: Electroencephalography
Clear Filters Showing 81 to 90 of 2114 articles
Optimized driver fatigue detection method using multimodal neural networks.
Scientific reports
Apr 10, 2025
Driver fatigue is a significant factor contributing to road accidents, highlighting the need for precise and reliable detection systems. This study introduces a comprehensive approach using multimodal neural networks, leveraging the DROZY dataset, wh...
DP-MP: a novel cross-subject fatigue detection framework with DANN-based prototypical representation and mix-up pairwise learning.
Journal of neural engineering
Apr 7, 2025
. Electroencephalography (EEG) is widely recognized as an effective method for detecting fatigue. However, practical applications of EEG for fatigue detection in real-world scenarios are often challenging, particularly in cases involving subjects not...
Artificial neural networks applied to somatosensory evoked potentials for migraine classification.
The journal of headache and pain
Apr 4, 2025
BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recurrent alterations in the brainstem-thalamo-cortical loop, including reduced thalamocortical activity...
Decoding SSVEP Via Calibration-Free TFA-Net: A Novel Network Using Time-Frequency Features.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Brain-computer interfaces (BCIs) based on steady-state visual evoked potential (SSVEP) signals offer high information transfer rates and non-invasive brain-to-device connectivity, making them highly practical. In recent years, deep learning technique...
A Hybrid Artificial Intelligence System for Automated EEG Background Analysis and Report Generation.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Electroencephalography (EEG) plays a crucial role in the diagnosis of various neurological disorders. However, small hospitals and clinics often lack advanced EEG signal analysis systems and are prone to misinterpretation in manual EEG reading. This ...
DC-ASTGCN: EEG Emotion Recognition Based on Fusion Deep Convolutional and Adaptive Spatio-Temporal Graph Convolutional Networks.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Thanks to advancements in artificial intelligence and brain-computer interface (BCI) research, there has been increasing attention towards emotion recognition techniques based on electroencephalogram (EEG) recently. The complexity of EEG data poses a...
An Efficient Graph Learning System for Emotion Recognition Inspired by the Cognitive Prior Graph of EEG Brain Network.
IEEE transactions on neural networks and learning systems
Apr 4, 2025
Benefiting from the high-temporal resolution of electroencephalogram (EEG), EEG-based emotion recognition has become one of the hotspots of affective computing. For EEG-based emotion recognition systems, it is crucial to utilize state-of-the-art lear...
Increased Global and Regional Connectivity in Propofol-induced Unconsciousness: Human Intracranial Electroencephalography Study.
Anesthesiology
Apr 3, 2025
BACKGROUND: The conscious state is maintained through intact communication between brain regions. However, studies on global and regional connectivity changes in unconscious state have been inconsistent. These inconsistencies could arise from unclear...
An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion.
Scientific reports
Apr 3, 2025
Classical approaches to diagnosis frequently rely on self-reported symptoms or clinician observations, which can make it difficult to examine mental health illnesses due to their subjective and complicated nature. In this work, we offer an innovative...
Explainable machine learning model based on EEG, ECG, and clinical features for predicting neurological outcomes in cardiac arrest patient.
Scientific reports
Apr 3, 2025
Early and accurate prediction of neurological outcomes in comatose patients following cardiac arrest is critical for informed clinical decision-making. Existing studies have predominantly focused on EEG for assessing brain injury, with some exploring...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823