AIMC Topic: Electroencephalography

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EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning.

Journal of neuroscience methods Jul 3, 2024
Brain-computer interface (BCI) technology holds promise for individuals with profound motor impairments, offering the potential for communication and control. Motor imagery (MI)-based BCI systems are particularly relevant in this context. Despite the...
Imagination Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Algorithms Brain Deep Learning Humans
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Deep learning-based stress detection for daily life use using single-channel EEG and GSR in a virtual reality interview paradigm.

PloS one Jul 3, 2024
This research aims to establish a practical stress detection framework by integrating physiological indicators and deep learning techniques. Utilizing a virtual reality (VR) interview paradigm mirroring real-world scenarios, our focus is on classifyi...
Deep Learning Young Adult Stress, Psychological Humans Adult ROC Curve Virtual Reality Galvanic Skin Response Neural Networks, Computer Male Female Electroencephalography
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A Method to Extract Task-Related EEG Feature Based on Lightweight Convolutional Neural Network.

Neuroscience bulletin Jul 2, 2024
Unlocking task-related EEG spectra is crucial for neuroscience. Traditional convolutional neural networks (CNNs) effectively extract these features but face limitations like overfitting due to small datasets. To address this issue, we propose a light...
Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Humans Adult Neural Networks, Computer Female Male Brain Young Adult
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Unraveling Brain Synchronisation Dynamics by Explainable Neural Networks using EEG Signals: Application to Dyslexia Diagnosis.

Interdisciplinary sciences, computational life sciences Jul 2, 2024
The electrical activity of the neural processes involved in cognitive functions is captured in EEG signals, allowing the exploration of the integration and coordination of neuronal oscillations across multiple spatiotemporal scales. We have proposed ...
Female Male Deep Learning Dyslexia Child Electroencephalography Humans Neural Networks, Computer Brain
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Power spectral density-based resting-state EEG classification of first-episode psychosis.

Scientific reports Jul 2, 2024
Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during sensory and c...
Humans Electroencephalography Machine Learning Signal Processing, Computer-Assisted Brain Psychotic Disorders Male Young Adult Rest Adolescent Female Adult Support Vector Machine
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A Deep Learning Approach to Estimate Multi-Level Mental Stress From EEG Using Serious Games.

IEEE journal of biomedical and health informatics Jul 2, 2024
Stress is revealed by the inability of individuals to cope with their environment, which is frequently evidenced by a failure to achieve their full potential in tasks or goals. This study aims to assess the feasibility of estimating the level of stre...
Male Deep Learning Stress, Psychological Electroencephalography Female Young Adult Adult Signal Processing, Computer-Assisted Video Games Humans
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MASA-TCN: Multi-Anchor Space-Aware Temporal Convolutional Neural Networks for Continuous and Discrete EEG Emotion Recognition.

IEEE journal of biomedical and health informatics Jul 2, 2024
Emotion recognition from electroencephalogram (EEG) signals is a critical domain in biomedical research with applications ranging from mental disorder regulation to human-computer interaction. In this paper, we address two fundamental aspects of EEG ...
Neural Networks, Computer Algorithms Emotions Electroencephalography Humans Signal Processing, Computer-Assisted
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Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation.

IEEE journal of biomedical and health informatics Jul 2, 2024
Soft robotic glove controlled by a brain-computer interface (BCI) have demonstrated effectiveness in hand rehabilitation for stroke patients. Current systems rely on static visual representations for patients to perform motor imagination (MI) tasks, ...
Adult Evoked Potentials, Visual Female Humans Male Aged Equipment Design Hand Stroke Rehabilitation Algorithms Middle Aged Young Adult Signal Processing, Computer-Assisted Stroke Brain-Computer Interfaces Robotics Electroencephalography
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SMARTSeiz: Deep Learning With Attention Mechanism for Accurate Seizure Recognition in IoT Healthcare Devices.

IEEE journal of biomedical and health informatics Jul 2, 2024
The Internet of Things (IoT) is capable of controlling the healthcare monitoring system for remote-based patients. Epilepsy, a chronic brain syndrome characterized by recurrent, unpredictable attacks, affects individuals of all ages. IoT-based seizur...
Epilepsy Humans Seizures Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms Internet of Things Deep Learning Electroencephalography
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Do all sedatives promote biological sleep electroencephalogram patterns? A machine learning framework to identify biological sleep promoting sedatives using electroencephalogram.

PloS one Jul 2, 2024
BACKGROUND: Sedatives are commonly used to promote sleep in intensive care unit patients. However, it is not clear whether sedation-induced states are similar to the biological sleep. We explored if sedative-induced states resemble biological sleep u...
Adult Machine Learning Humans Sleep Female Male Sevoflurane Young Adult Propofol Hypnotics and Sedatives Sleep Stages Electroencephalography Dexmedetomidine
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