AIMC Topic: Electroencephalography
Clear Filters Showing 31 to 40 of 2152 articles
The class imbalance problem in automatic localization of the epileptogenic zone for epilepsy surgery: a systematic review.
Journal of neural engineering
Jun 26, 2025
Accurate localization of the epileptogenic zone (EZ) is crucial for epilepsy surgery, but the class imbalance of epileptogenic vs. non-epileptogenic electrode contacts in intracranial electroencephalography (iEEG) data poses significant challenges fo...
A novel dual-branch network for comprehensive spatiotemporal information integration for EEG-based epileptic seizure detection.
PloS one
Jun 26, 2025
Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal brain activity, which can severely affects people's normal lives. To improve the lives of these patients, it is necessary to develop accurate methods to predic...
Epilepsy Prediction via Time-Frequency Features and Multi-Scale Hybrid Neural Networks.
Journal of medical systems
Jun 25, 2025
The prediction of epileptic seizures heavily depends on the precise embedding and classification of complex, multi-dimensional electroencephalogram (EEG) signals. Due to individual variability and the dynamic non-linear nature of EEG signals, extract...
Learning from small datasets-review of workshop 6 of the 10th International BCI Meeting 2023.
Journal of neural engineering
Jun 24, 2025
In a brain-computer interface (BCI), a primary objective is to reduce calibration time by recording as few as possible novel data points to (re-)train decoder models.Minimizing the calibration can be crucial for enhancing the usability of a BCI appli...
Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study.
Journal of neuroengineering and rehabilitation
Jun 18, 2025
BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walking ability in stroke patients compared to conventional rehabilitation, but the neural mechanisms remain unclear. This study aims to explore the effec...
Test-retest reliability of kinematic and EEG low-beta spectral features in a robot-based arm movement task.
Biomedical physics & engineering express
Jun 18, 2025
Low-beta (L, 13-20 Hz) power plays a key role in upper-limb motor control and afferent processing, making it a strong candidate for a neurophysiological biomarker. We investigate the test-retest reliability of Lpower and kinematic features from a rob...
Identifying and predicting EEG microstates with sequence-to-sequence deep learning models for online applications.
Journal of neural engineering
Jun 17, 2025
Electroencephalographic (EEG) microstates, as a non-invasive and high-temporal-resolution tool for analyzing time-space features of brain activity, have been validated and applied in various research domains. However, current methods for EEG microsta...
Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation.
PloS one
Jun 13, 2025
INTRODUCTION: Sleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. This high...
POC-CSP: a novel parameterised and orthogonally-constrained neural network layer for learning common spatial patterns (CSP) in EEG signals.
Journal of neural engineering
Jun 11, 2025
. Common spatial patterns (CSPs) has been established as a powerful feature extraction method in EEG signal processing with machine learning, but it has shortcomings including sensitivity to noise and rigidity in the value of the weights. Our goal wa...
Roman domination-based spiking neural network for optimized EEG signal classification of four class motor imagery.
Computers in biology and medicine
Jun 10, 2025
The Spiking Neural Network (SNN) is a third-generation neural network recognized for its energy efficiency and ability to process spatiotemporal information, closely imitating the behavioral mechanisms of biological neurons in the brain. SNN exhibit ...
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 31963
- Neural Networks, Computer 30200
- Algorithms 27375
- Deep Learning 26880
- Artificial Intelligence 24816
- Robotics 13382
- Image Processing, Computer-Assisted 9730
- Retrospective Studies 9328
- Magnetic Resonance Imaging 6341
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4863
- Support Vector Machine 4762
- Computational Biology 4327
- Brain 4124
- Computer Simulation 3932
Recent Journals
- Scientific reports 6689
- Sensors (Basel, Switzerland) 4794
- PloS one 4186
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1915
- 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 1378
- IEEE journal of biomedical and health informatics 1167
- Journal of chemical information and modeling 1059
- Nature communications 1029
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 872
- Journal of medical Internet research 853
- Briefings in bioinformatics 853