IEEE transactions on bio-medical engineering
Oct 1, 2025
Deep learning-based methods for automatic sleep staging offer an efficient and objective alternative to costly manual scoring. However, their reliance on extensive labeled datasets and the challenge of generalization to new subjects and datasets limi...
Emotion recognition via electroencephalogram (EEG) data is crucial for improving human-computer interaction. In practice, researchers require a substantial quantity of EEG samples to train and validate models. However, existing EEG datasets typically...
PURPOSE: Music perception is a fundamental human experience, integral to cognitive and emotional processing, making it a crucial area for neuroscientific investigation. This study examined the neural dynamics underlying music perception and identifie...
Brain-controlled systems have experienced significant advancements in overall performance, largely driven by continuous optimization and innovation in electroencephalography (EEG) acquisition experimental paradigms and decoding algorithms. However, t...
BACKGROUND: The evolution in peri-ictal period (from pre-ictal to ictal phase) of seizures contains abundant epileptogenic information, which aids in exploring the mechanism of seizures and localizing the epileptogenic zone (EZ). This study aims to i...
This study focuses on the binary classification of pediatric epilepsy seizure types as focal or generalized using Turkish electroencephalography (EEG) reports, leveraging natural language processing (NLP) and machine learning methodologies. A novel d...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
As a modal of physiological information, electroencephalogram (EEG), surface electromyography (sEMG), and eye tracking (ET) signals are widely used to decode human intention, promoting the development of human-computer interaction systems. Extensive ...
In recent years, Artificial Intelligence (AI), with a specific emphasis on attention mechanisms instead of conventional Deep Learning (DL) or Machine Learning (ML), has demonstrated significant applicability across diverse medical domains. This paper...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Synaptic increase is a common phenomenon in the brain of autism spectrum disorder (ASD). However, the impact of increased synapses on the neurophysiological activity of ASD remains unclear. To address this, we propose a large-scale cortical network m...
This study aimed to classify patients' focal (frontal, temporal, parietal, occipital), multifocal, and generalized epileptiform activities based on EEG findings using artificial intelligence models. The study included 575 patients followed in the Neu...
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