AIMC Topic: Electroencephalography
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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...
Thalamic neural activity and epileptic network analysis using stereoelectroencephalography: a prospective study protocol.
BMJ open
Jun 10, 2025
INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of patients experiencing intractable epilepsy, often necessitating surgical intervention. Deep brain stimulation (DBS) of the thalamus has been introduc...
Automated classification of seizure onset pattern using intracranial electroencephalogram signal of non-human primates.
Physiological measurement
Jun 10, 2025
To develop and validate a machine learning framework for the classification of distinct seizure onset patterns using intracranial EEG (iEEG) recordings in a non-human primate (NHP) model of penicillin-induced seizures.iEEG data were collected from si...
Emotion recognition with multiple physiological parameters based on ensemble learning.
Scientific reports
Jun 6, 2025
Emotion recognition is a key research area in artificial intelligence, playing a critical role in enhancing human-computer interaction and optimizing user experience design. This study explores the application and effectiveness of ensemble learning m...
Optimal graph representations and neural networks for multichannel time series data in seizure phase classification.
Scientific reports
Jun 4, 2025
In recent years, several machine-learning (ML) solutions have been proposed to solve the problems of seizure detection, seizure phase classification, seizure prediction, and seizure onset zone (SOZ) localization, achieving excellent performance with ...
Requirement Analysis for Data-Driven Electroencephalography Seizure Monitoring Software to Enhance Quality and Decision Making in Digital Care Pathways for Epilepsy: A Feasibility Study from the Perspectives of Health Care Professionals.
JMIR human factors
May 30, 2025
BACKGROUND: Abnormal brain activity is the source of epileptic seizures, which can present a variety of symptoms and influence patients' quality of life. Therefore, it is critical to track epileptic seizures, diagnose them, and provide potential ther...
A data-centric and interpretable EEG framework for depression severity grading using SHAP-based insights.
Journal of neuroengineering and rehabilitation
May 25, 2025
BACKGROUND: Major Depressive Disorder is a leading cause of disability worldwide. An accurate assessment of depression severity is critical for diagnosis, treatment planning, and monitoring, yet current clinical tools are largely subjective, relying ...
Automated depression detection via cloud based EEG analysis with transfer learning and synchrosqueezed wavelet transform.
Scientific reports
May 23, 2025
Post-COVID-19, depression rates have risen sharply, increasing the need for early diagnosis using electroencephalogram (EEG) and deep learning. To tackle this, we developed a cloud-based computer-aided depression diagnostic (CCADD) system that utiliz...
Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus.
Neurobiology of disease
May 20, 2025
Status epilepticus (SE), seizures lasting beyond five minutes, is a medical emergency commonly treated with benzodiazepines which enhance GABA receptor (GABAR) conductance. Despite widespread use, benzodiazepines fail in over one-third of patients, p...
Decoding the Narcissistic Brain.
NeuroImage
May 20, 2025
There is a substantial knowledge gap in the narcissism literature: <1 % of the nearly 12,000 articles on narcissism have addressed its neural basis. To help fill this gap, we asked whether the multifacetedness of narcissism could be decoded from spon...
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