Neurology

Seizures

Latest AI and machine learning research in seizures for healthcare professionals.

3,730 articles
Stay Ahead - Weekly Seizures research updates
Subscribe
Browse Specialties
Showing 379-399 of 3,730 articles
Real-Time Postural Disturbance Detection Through Sensor Fusion of EEG and Motion Data Using Machine Learning.

Millions of people around the globe are impacted by falls annually, making it a significant public h...

Sleep Stage Classification Via Multi-View Based Self-Supervised Contrastive Learning of EEG.

Self-supervised learning (SSL) is a challenging task in sleep stage classification (SSC) that is cap...

MSVTNet: Multi-Scale Vision Transformer Neural Network for EEG-Based Motor Imagery Decoding.

OBJECT: Transformer-based neural networks have been applied to the electroencephalography (EEG) deco...

CareSleepNet: A Hybrid Deep Learning Network for Automatic Sleep Staging.

Sleep staging is essential for sleep assessment and plays an important role in disease diagnosis, wh...

Low-power and lightweight spiking transformer for EEG-based auditory attention detection.

EEG signal analysis can be used to study brain activity and the function and structure of neural net...

Can people with epilepsy trust AI chatbots for information on physical exercise?

PURPOSE: This study aims to evaluate the similarity, readability, and alignment with current scienti...

Eeg based smart emotion recognition using meta heuristic optimization and hybrid deep learning techniques.

In the domain of passive brain-computer interface applications, the identification of emotions is bo...

On the role of visual feedback and physiotherapist-patient interaction in robot-assisted gait training: an eye-tracking and HD-EEG study.

BACKGROUND: Treadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor...

Hybrid Network Using Dynamic Graph Convolution and Temporal Self-Attention for EEG-Based Emotion Recognition.

The electroencephalogram (EEG) signal has become a highly effective decoding target for emotion reco...

Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective From the Time-Frequency Analysis.

The motor imagery (MI) classification has been a prominent research topic in brain-computer interfac...

A Bio-Inspired Spiking Attentional Neural Network for Attentional Selection in the Listening Brain.

Humans show a remarkable ability in solving the cocktail party problem. Decoding auditory attention ...

An adaptive session-incremental broad learning system for continuous motor imagery EEG classification.

Motor imagery electroencephalography (MI-EEG) is usually used as a driving signal in neuro-rehabilit...

A Novel Real-time Phase Prediction Network in EEG Rhythm.

Closed-loop neuromodulation, especially using the phase of the electroencephalography (EEG) rhythm t...

Combining MRI radiomics and clinical features for early identification of drug-resistant epilepsy in people with newly diagnosed epilepsy.

OBJECTIVE: To identify newly diagnosed patients with drug-resistant epilepsy (DRE) based on radiomic...

Comparison analysis between standard polysomnographic data and in-ear-electroencephalography signals: a preliminary study.

STUDY OBJECTIVES: Polysomnography (PSG) currently serves as the benchmark for evaluating sleep disor...

Estimating global phase synchronization by quantifying multivariate mutual information and detecting network structure.

In neuroscience, phase synchronization (PS) is a crucial mechanism that facilitates information proc...

MACNet: A Multidimensional Attention-Based Convolutional Neural Network for Lower-Limb Motor Imagery Classification.

Decoding lower-limb motor imagery (MI) is highly important in brain-computer interfaces (BCIs) and r...

Single-channel electroencephalography decomposition by detector-atom network and its pre-trained model.

Signal decomposition techniques utilizing multi-channel spatial features are critical for analyzing,...

Neural correlates of empathy in donation decisions: Insights from EEG and machine learning.

Empathy is central to individual and societal well-being. Numerous studies have examined how trait o...

Prediction of Survival After Pediatric Cardiac Arrest Using Quantitative EEG and Machine Learning Techniques.

BACKGROUND AND OBJECTIVES: Early neuroprognostication in children with reduced consciousness after c...

Browse Specialties