AIMC Topic: Electroencephalography
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Classification of Internal and External Distractions in an Educational VR Environment Using Multimodal Features.
IEEE transactions on visualization and computer graphics
Oct 11, 2024
Virtual reality (VR) can potentially enhance student engagement and memory retention in the classroom. However, distraction among participants in a VR-based classroom is a significant concern. Several factors, including mind wandering, external noise...
Artificial intelligence and machine learning in disorders of consciousness.
Current opinion in neurology
Oct 9, 2024
PURPOSE OF REVIEW: As artificial intelligence and machine learning technologies continue to develop, they are being increasingly used to improve the scientific understanding and clinical care of patients with severe disorders of consciousness followi...
Adapting Action Recognition Neural Networks for Automated Infantile Spasm Detection.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 9, 2024
Infantile spasms are a severe epileptic syndrome characterized by short muscular contractions lasting from 0.5 to 2 seconds. They are often misdiagnosed due to their atypical presentation, and treatment is frequently delayed, leading to stagnation or...
Detection of Low Resilience Using Data-Driven Effective Connectivity Measures.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 1, 2024
Conventional thresholding techniques for graph theory analysis, such as absolute, proportional and mean degree, have often been used in characterizing human brain networks under different mental disorders, such as mental stress. However, these approa...
Deep Neural Network-Based Empirical Mode Decomposition for Motor Imagery EEG Classification.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 1, 2024
Motor imagery refers to the brain's response during the mental simulation of physical activities, which can be detected through electroencephalogram (EEG) signals. However, EEG signals exhibit a low signal-to-noise ratio (SNR) due to various artifact...
Predicting the effectiveness of binaural beats on working memory.
Neuroreport
Sep 30, 2024
Working memory is vital for short-term information processing. Binaural beats can enhance working memory by improving attention and memory consolidation through neural synchronization. However, individual differences in cognitive and neuronal functio...
A Lightweight Convolutional Neural Network-Reformer Model for Efficient Epileptic Seizure Detection.
International journal of neural systems
Sep 30, 2024
A real-time and reliable automatic detection system for epileptic seizures holds significant value in assisting physicians with rapid diagnosis and treatment of epilepsy. Aiming to address this issue, a novel lightweight model called Convolutional Ne...
Machine-learning-based classification of obstructive sleep apnea using 19-channel sleep EEG data.
Sleep medicine
Sep 29, 2024
OBJECTIVE: This study aimed to investigate the neurophysiological effects of obstructive sleep apnea (OSA) using multi-channel sleep electroencephalography (EEG) through machine learning methods encompassing various analysis methodologies including p...
Classification of mindfulness experiences from gamma-band effective connectivity: Application of machine-learning algorithms on resting, breathing, and body scan.
Computer methods and programs in biomedicine
Sep 28, 2024
BACKGROUND AND OBJECTIVE: Practicing mindfulness is a mental process toward interoceptive awareness, achieving stress reduction and emotion regulation through brain-function alteration. Literature has shown that electroencephalography (EEG)-derived c...
Cortical ROI Importance Improves MI Decoding From EEG Using Fused Light Neural Network.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 27, 2024
Decoding motor imagery (MI) using deep learning in cortical level has potential in brain computer interface based intelligent rehabilitation. However, a mass of dipoles is inconvenient to extract the personalized features and requires a more complex ...
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