AIMC Topic: Electroencephalography

Clear Filters Showing 681 to 690 of 2121 articles

An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea.

Computers in biology and medicine Aug 31, 2023
Automatic deep-learning models used for sleep scoring in children with obstructive sleep apnea (OSA) are perceived as black boxes, limiting their implementation in clinical settings. Accordingly, we aimed to develop an accurate and interpretable deep...
Deep Learning Child Electroencephalography Sleep Humans Sleep Apnea Syndromes Artificial Intelligence
View on PubMed DOI

Electroencephalogram (EEG) based prediction of attention deficit hyperactivity disorder (ADHD) using machine learning.

Applied neuropsychology. Adult Aug 30, 2023
"Attention-Deficit Hyperactivity Disorder (ADHD)" is a neuro-developmental disorder in children under 12 years old. Learning deficits, anxiety, depression, sensory processing disorder, and oppositional defiant disorder are the most frequent comorbidi...
Bayes Theorem Female Electroencephalography Male Humans Attention Deficit Disorder with Hyperactivity Machine Learning Child Principal Component Analysis
View on PubMed DOI

An Explainable EEG-Based Human Activity Recognition Model Using Machine-Learning Approach and LIME.

Sensors (Basel, Switzerland) Aug 27, 2023
Electroencephalography (EEG) is a non-invasive method employed to discern human behaviors by monitoring the neurological responses during cognitive and motor tasks. Machine learning (ML) represents a promising tool for the recognition of human activi...
Human Activities Machine Learning Electroencephalography Humans Artificial Intelligence
View on PubMed DOI

Application of cluster repeated mini-batch training method to classify electroencephalography for grab and lift tasks.

Medical engineering & physics Aug 23, 2023
Modern deep neural network training is based on mini-batch stochastic gradient optimization. While using extensive mini-batches improves the computational parallelism, the small batch training proved that it delivers improved generalization performan...
Neural Networks, Computer Algorithms Electroencephalography
View on PubMed DOI

Optimizing detection and deep learning-based classification of pathological high-frequency oscillations in epilepsy.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Aug 9, 2023
OBJECTIVE: This study aimed to explore sensitive detection methods for pathological high-frequency oscillations (HFOs) to improve seizure outcomes in epilepsy surgery.
Humans Electroencephalography Epilepsy Deep Learning Child Seizures Drug Resistant Epilepsy
View on PubMed DOI

Decoding movement kinematics from EEG using an interpretable convolutional neural network.

Computers in biology and medicine Aug 8, 2023
Continuous decoding of hand kinematics has been recently explored for the intuitive control of electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs). Deep neural networks (DNNs) are emerging as powerful decoders, for their ability to au...
Movement Electroencephalography Brain-Computer Interfaces Neural Networks, Computer Machine Learning Algorithms Biomechanical Phenomena Humans
View on PubMed DOI

A novel method for modeling effective connections between brain regions based on EEG signals and graph neural networks for motor imagery detection.

Computer methods in biomechanics and biomedical engineering Aug 7, 2023
Classified as biomedical signal processing, cerebral signal processing plays a key role in human-computer interaction (HCI) and medical diagnosis. The motor imagery (MI) problem is an important research area in this field. Accurate solutions to this ...
Brain Electroencephalography Signal Processing, Computer-Assisted Imagination Humans Neural Networks, Computer
View on PubMed DOI

Self-Attentive Channel-Connectivity Capsule Network for EEG-Based Driving Fatigue Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Aug 7, 2023
Deep neural networks have recently been successfully extended to EEG-based driving fatigue detection. Nevertheless, most existing models fail to reveal the intrinsic inter-channel relations that are known to be beneficial for EEG-based classification...
Electroencephalography Adult Male Female Young Adult Machine Learning Humans Learning Neural Networks, Computer
View on PubMed DOI

Deep-learning detection of mild cognitive impairment from sleep electroencephalography for patients with Parkinson's disease.

PloS one Aug 3, 2023
Parkinson's disease which is the second most prevalent neurodegenerative disorder in the United States is a serious and complex disease that may progress to mild cognitive impairment and dementia. The early detection of the mild cognitive impairment ...
Electroencephalography Sleep Humans Cognitive Dysfunction Parkinson Disease Quality of Life Deep Learning
View on PubMed DOI

An extended clinical EEG dataset with 15,300 automatically labelled recordings for pathology decoding.

NeuroImage. Clinical Jul 28, 2023
Automated clinical EEG analysis using machine learning (ML) methods is a growing EEG research area. Previous studies on binary EEG pathology decoding have mainly used the Temple University Hospital (TUH) Abnormal EEG Corpus (TUAB) which contains appr...
Electroencephalography Machine Learning Algorithms Humans Neural Networks, Computer
View on PubMed DOI
Popular Topics
Recent Journals