AIMC Topic: Electroencephalography

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An EEG-EMG dataset from a standardized reaching task for biomarker research in upper limb assessment.

Scientific data May 20, 2025
This work describes a dataset containing high-density EEG (hd-EEG) and surface electromiography (sEMG) to capture neuromechanical responses during a reaching task with and without the assistance of an upper-limb exoskeleton. It was designed to explor...
Humans Electromyography Movement Upper Extremity Adult Electroencephalography Biomarkers
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PhyTransformer: A unified framework for learning spatial-temporal representation from physiological signals.

Neural networks : the official journal of the International Neural Network Society May 19, 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 ...
Signal Processing, Computer-Assisted Humans Neural Networks, Computer Electromyography Eye-Tracking Technology Electroencephalography
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Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods.

Sensors (Basel, Switzerland) May 18, 2025
Driven by the remarkable capabilities of machine learning, brain-computer interfaces (BCIs) are carving out an ever-expanding range of applications across a multitude of diverse fields. Notably, electroencephalogram (EEG) signals have risen to promin...
Electroencephalography Signal Processing, Computer-Assisted Machine Learning Brain-Computer Interfaces Humans Algorithms Neural Networks, Computer Brain
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Decision support system based on ensemble models in distinguishing epilepsy types.

Epilepsy & behavior : E&B May 17, 2025
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...
Adult Male Middle Aged Female Young Adult Epilepsy Epilepsies, Partial Epilepsy, Generalized Support Vector Machine Electroencephalography Adolescent Machine Learning Retrospective Studies Humans
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MT-RCAF: A Multi-Task Residual Cross Attention Framework for EEG-based emotion recognition and mood disorder detection.

Computer methods and programs in biomedicine May 17, 2025
BACKGROUND AND OBJECTIVE: Prolonged abnormal emotions can gradually evolve into mood disorders such as anxiety and depression, making it critical to study the relationship between emotions and mood disorders to explore the causes of mood disorders. E...
Attention Mood Disorders Algorithms Emotions Electroencephalography Humans
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Lightweight hybrid transformers-based dyslexia detection using cross-modality data.

Scientific reports May 16, 2025
Early and precise diagnosis of dyslexia is crucial for implementing timely intervention to reduce its effects. Timely identification can improve the individual's academic and cognitive performance. Traditional dyslexia detection (DD) relies on length...
Dyslexia Neural Networks, Computer Humans Electroencephalography Deep Learning Magnetic Resonance Imaging Handwriting
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Clinical Value of ChatGPT for Epilepsy Presurgical Decision-Making: Systematic Evaluation of Seizure Semiology Interpretation.

Journal of medical Internet research May 12, 2025
BACKGROUND: For patients with drug-resistant focal epilepsy, surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures. Accurate localization of the EZ is crucial and is typically achieved through comprehensive p...
Magnetic Resonance Imaging Adult Seizures Electroencephalography Epilepsy Male Humans Generative Artificial Intelligence Drug Resistant Epilepsy Female
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Behavioural and EEG correlates of forward and backward priming-An exploratory study.

PloS one May 8, 2025
During affective priming, perception of an emotional "prime stimulus" influences the reaction time to the subsequent emotional "target stimulus". If prime and target have the same valence (congruent trials), reactions to the target are faster than if...
Humans Female Adult Male Young Adult Emotions Electroencephalography Reaction Time Evoked Potentials Behavior
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Event driven neural network on a mixed signal neuromorphic processor for EEG based epileptic seizure detection.

Scientific reports May 7, 2025
Long-term monitoring of biomedical signals is essential for the modern clinical management of neurological conditions such as epilepsy. However, developing wearable systems that are able to monitor, analyze, and detect epileptic seizures with long-la...
Electroencephalography Epilepsy Seizures Humans Signal Processing, Computer-Assisted Neural Networks, Computer
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Enhanced classification of tinnitus patients using EEG microstates and deep learning techniques.

Scientific reports May 7, 2025
This study aims to deepen the understanding and classification of tinnitus through a comprehensive analysis of EEG signals utilizing innovative microstate analysis techniques and cutting-edge machine learning approaches. EEG data were collected from ...
Support Vector Machine Electroencephalography Tinnitus Middle Aged Deep Learning Female Humans Adult Male
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