Seizures

Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic-Ischemic Encephalopathy Injury.

Hypoxic-Ischemic Encephalopathy (HIE) occurs in patients who experience a decreased flow of blood and oxygen to the brain, with the optimal window for effective treatment being within the first six hours of life. This puts a significant demand on medical professionals to accurately and effectively grade the severity of the HIE present, which is a time-consuming and challenging task. This paper pro...

Deep Learning for EEG-Based Visual Classification and Reconstruction: Panorama, Trends, Challenges and Opportunities.

Deep learning has significantly enhanced the research on the emerging issue of Electroencephalogram (EEG)-based visual classification and reconstruction, which has gained a growth of attention and concern recently. To promote the research progress, at this critical moment, a review work on the deep learning methodology for the issue becomes necessary and important. However, such a work seems absen...

Enhanced Graph Attention Network by Integrating Transformer for Epileptic EEG Identification.

Electroencephalography signal classification is essential for the diagnosis and monitoring of neurological disorders, with significant implications fo...

Novel neural activity profiles underlying inhibitory control deficits of clinical relevance in ADHD - insights from EEG tensor decomposition.

BACKGROUND: Attention-Deficit-Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental disorder that impacts cognitive control processes. Wh...

Wearable sleep recording augmented by artificial intelligence for Alzheimer's disease screening.

The recent emergence of wearable devices will enable large scale remote brain monitoring. This study investigated whether multimodal wearable sleep re...

EEG-based Signatures of Schizophrenia, Depression, and Aberrant Aging: A Supervised Machine Learning Investigation.

BACKGROUND: Electroencephalography (EEG) is a noninvasive, cost-effective, and robust tool, which directly measures in vivo neuronal mass activity wit...

ALFEE: Adaptive Large Foundation Model for EEG Representation

While foundation models excel in text, image, and video domains, the critical biological signals, particularly electroencephalography(EEG), remain u...

Depolarization block induction via slow NaV1.1 inactivation in Dravet syndrome

Dravet syndrome is a developmental and epileptic encephalopathy, characterized by the early onset of drug-resistant seizures and various comorbiditi...

Closed-loop control of seizure activity via real-time seizure forecasting by reservoir neuromorphic computing

Closed-loop brain stimulation holds potential as personalized treatment for drug-resistant epilepsy (DRE) but still suffers from limitations that re...

Low-dimensional representation of brain networks for seizure risk forecasting

Identifying preictal states -- periods during which seizures are more likely to occur -- remains a central challenge in clinical computational neuro...

KnowEEG: Explainable Knowledge Driven EEG Classification

Electroencephalography (EEG) is a method of recording brain activity that shows significant promise in applications ranging from disease classificat...

Adaptive Dynamic Surface Control of Epileptor Model Based on Nonlinear Luenberger State Observer.

Epilepsy is a prevalent neurological disorder characterized by recurrent seizures, which are sudden bursts of electrical activity in the brain. The Ep...

Mental state classification based on electroencephalogram (EEG) using multiclass support vector machine.

INTRODUCTION: Mental state refers to a person's state of mind from various perspectives, including consciousness, intention, and functionalism. Mental...

An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.

ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload as...

Juvenile Myoclonic Epilepsy Imaging Endophenotypes and Relationship With Cognition and Resting-State EEG.

Structural neuroimaging studies of patients with Juvenile Myoclonic Epilepsy (JME) typically present two findings: 1-volume reduction of subcortical g...

xEEGNet: Towards Explainable AI in EEG Dementia Classification

This work presents xEEGNet, a novel, compact, and explainable neural network for EEG data analysis. It is fully interpretable and reduces overfittin...

NRevisit: A Cognitive Behavioral Metric for Code Understandability Assessment

Measuring code understandability is both highly relevant and exceptionally challenging. This paper proposes a dynamic code understandability assessm...

Subject-independent Classification of Meditative State from the Resting State using EEG

While it is beneficial to objectively determine whether a subject is meditating, most research in the literature reports good results only in a subj...

The use of Multi-domain Electroencephalogram Representations in the building of Models based on Convolutional and Recurrent Neural Networks for Epilepsy Detection

Epilepsy, affecting approximately 50 million people globally, is characterized by abnormal brain activity and remains challenging to treat. The diag...

Neuroadaptive Haptics: Comparing Reinforcement Learning from Explicit Ratings and Neural Signals for Adaptive XR Systems

Neuroadaptive haptics offers a path to more immersive extended reality (XR) experiences by dynamically tuning multisensory feedback to user preferen...