AIMC Topic: Electroencephalography

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Unsupervised and semi-supervised domain adaptation networks considering both global knowledge and prototype-based local class information for Motor Imagery Classification.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2024
The non-stationarity of EEG signals results in variability across sessions, impeding model building and data sharing. In this paper, we propose a domain adaptation method called GPL, which simultaneously considers global knowledge and prototype-based...
Humans Neural Networks, Computer Electroencephalography Supervised Machine Learning Brain-Computer Interfaces Imagination Algorithms Brain Unsupervised Machine Learning
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Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population.

Epilepsy research Jul 1, 2024
PURPOSE: This study aimed to develop a classifier using supervised machine learning to effectively assess the impact of clinical, demographical, and biochemical factors in accurately predicting the antiseizure medications (ASMs) treatment response in...
Anticonvulsants Electroencephalography Epilepsy Seizures Male Middle Aged Adolescent Treatment Outcome Support Vector Machine Child India Female Young Adult Adult Humans Machine Learning Algorithms
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Efficient Generalized Electroencephalography-Based Drowsiness Detection Approach with Minimal Electrodes.

Sensors (Basel, Switzerland) Jun 30, 2024
Drowsiness is a main factor for various costly defects, even fatal accidents in areas such as construction, transportation, industry and medicine, due to the lack of monitoring vigilance in the mentioned areas. The implementation of a drowsiness dete...
Electroencephalography Signal Processing, Computer-Assisted Electrodes Algorithms Support Vector Machine Bayes Theorem Sleep Stages Humans Machine Learning
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MSE-VGG: A Novel Deep Learning Approach Based on EEG for Rapid Ischemic Stroke Detection.

Sensors (Basel, Switzerland) Jun 29, 2024
Ischemic stroke is a type of brain dysfunction caused by pathological changes in the blood vessels of the brain which leads to brain tissue ischemia and hypoxia and ultimately results in cell necrosis. Without timely and effective treatment in the ea...
Aged Stroke Male Ischemic Stroke Humans Brain Ischemia Middle Aged Electroencephalography Female Deep Learning Signal Processing, Computer-Assisted
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Wavelet Transform, Reconstructed Phase Space, and Deep Learning Neural Networks for EEG-Based Schizophrenia Detection.

International journal of neural systems Jun 28, 2024
This study proposes an innovative expert system that uses exclusively EEG signals to diagnose schizophrenia in its early stages. For diagnosing psychiatric/neurological disorders, electroencephalogram (EEG) testing is considered a financially viable,...
Electroencephalography Reproducibility of Results Wavelet Analysis Humans Signal Processing, Computer-Assisted Adult Schizophrenia Deep Learning Neural Networks, Computer Algorithms
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HiRENet: Novel convolutional neural network architecture using Hilbert-transformed and raw electroencephalogram (EEG) for subject-independent emotion classification.

Computers in biology and medicine Jun 27, 2024
BACKGROUND AND OBJECTIVES: Convolutional neural networks (CNNs) are the most widely used deep-learning framework for decoding electroencephalograms (EEGs) due to their exceptional ability to extract hierarchical features from high-dimensional EEG dat...
Humans Emotions Neural Networks, Computer Electroencephalography Brain Signal Processing, Computer-Assisted Deep Learning
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Speech decoding from stereo-electroencephalography (sEEG) signals using advanced deep learning methods.

Journal of neural engineering Jun 27, 2024
Brain-computer interfaces (BCIs) are technologies that bypass damaged or disrupted neural pathways and directly decode brain signals to perform intended actions. BCIs for speech have the potential to restore communication by decoding the intended spe...
Neural Networks, Computer Female Adult Humans Electroencephalography Epilepsy Brain-Computer Interfaces Stereotaxic Techniques Male Deep Learning Speech
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STaRNet: A spatio-temporal and Riemannian network for high-performance motor imagery decoding.

Neural networks : the official journal of the International Neural Network Society Jun 26, 2024
Brain-computer interfaces (BCIs), representing a transformative form of human-computer interaction, empower users to interact directly with external environments through brain signals. In response to the demands for high accuracy, robustness, and end...
Neural Networks, Computer Brain Electroencephalography Imagination Brain-Computer Interfaces Movement Humans
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When performing actions with robots, attribution of intentionality affects the sense of joint agency.

Science robotics Jun 26, 2024
Sense of joint agency (SoJA) is the sense of control experienced by humans when acting with others to bring about changes in the shared environment. SoJA is proposed to arise from the sensorimotor predictive processes underlying action control and mo...
Intention Psychomotor Performance Cooperative Behavior Humans Female Young Adult Robotics Electroencephalography Adult Male
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Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning.

Scientific reports Jun 25, 2024
Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostatectomy (RARP), early in their training. VUA assessment and training significantly impact patient outcomes and have high educational value. This study a...
Urinary Bladder Urethra Eye-Tracking Technology Clinical Competence Electroencephalography Robotic Surgical Procedures Anastomosis, Surgical Prostatectomy Humans Machine Learning Male
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