Seizures

MSE-VGG: A Novel Deep Learning Approach Based on EEG for Rapid Ischemic Stroke Detection.

Ischemic stroke is a type of brain dysfunction caused by pathological changes in the blood vessels o...

Wavelet Transform, Reconstructed Phase Space, and Deep Learning Neural Networks for EEG-Based Schizophrenia Detection.

This study proposes an innovative expert system that uses exclusively EEG signals to diagnose schizo...

Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy.

BACKGROUND: Epilepsy is a serious complication after an ischemic stroke. Although two studies have d...

An rs-fMRI based neuroimaging marker for adult absence epilepsy.

OBJECTIVE: Approximately 20-30 % of epilepsy patients exhibit negative findings on routine magnetic ...

HiRENet: Novel convolutional neural network architecture using Hilbert-transformed and raw electroencephalogram (EEG) for subject-independent emotion classification.

BACKGROUND AND OBJECTIVES: Convolutional neural networks (CNNs) are the most widely used deep-learni...

When performing actions with robots, attribution of intentionality affects the sense of joint agency.

Sense of joint agency (SoJA) is the sense of control experienced by humans when acting with others t...

Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning.

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostate...

Robots as Mental Health Coaches: A Study of Emotional Responses to Technology-Assisted Stress Management Tasks Using Physiological Signals.

The current study investigated the effectiveness of social robots in facilitating stress management ...

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.

This study addresses the challenge of differentiating between bipolar disorder II (BD II) and border...

Validation of artificial intelligence for epileptic seizure detection: Moving from research into the clinic.

Multiclass Classification of Visual Electroencephalogram Based on Channel Selection, Minimum Norm Estimation Algorithm, and Deep Network Architectures.

This work addresses the challenge of classifying multiclass visual EEG signals into 40 classes for b...

SleepFC: Feature Pyramid and Cross-Scale Context Learning for Sleep Staging.

Automated sleep staging is essential to assess sleep quality and treat sleep disorders, so the issue...

Rapid Electroencephalography and Artificial Intelligence in the Detection and Management of Nonconvulsive Seizures.

STUDY OBJECTIVE: Nonconvulsive status epilepticus is a commonly overlooked cause of altered mental s...

Classification of Visually Induced Motion Sickness Based on Phase-Locked Value Functional Connectivity Matrix and CNN-LSTM.

To effectively detect motion sickness induced by virtual reality environments, we developed a classi...

Development and validation of an automatic machine learning model to predict abnormal increase of transaminase in valproic acid-treated epilepsy.

Valproic acid (VPA) is a primary medication for epilepsy, yet its hepatotoxicity consistently raises...

EEG emotion recognition based on data-driven signal auto-segmentation and feature fusion.

Pattern recognition based on network connections has recently been applied to the brain-computer int...

Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach.

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized ...

GCTNet: a graph convolutional transformer network for major depressive disorder detection based on EEG signals.

Identifying major depressive disorder (MDD) using objective physiological signals has become a press...

An optimized EEGNet decoder for decoding motor image of four class fingers flexion.

As a cutting-edge technology of connecting biological brain and external devices, brain-computer int...

TPRO-NET: an EEG-based emotion recognition method reflecting subtle changes in emotion.

Emotion recognition based on Electroencephalogram (EEG) has been applied in various fields, includin...

LCADNet: a novel light CNN architecture for EEG-based Alzheimer disease detection.

Alzheimer's disease (AD) is a progressive and incurable neurologi-cal disorder with a rising mortali...