AIMC Topic: Electroencephalography

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A Deep Shared Multi-Scale Inception Network Enables Accurate Neonatal Quiet Sleep Detection With Limited EEG Channels.

IEEE journal of biomedical and health informatics Mar 7, 2022
In this paper, we introduce a new variation of the Convolutional Neural Network Inception block, called Sinc, for sleep stage classification in premature newborn babies using electroencephalogram (EEG). In practice, there are many medical centres whe...
Humans Neural Networks, Computer Electroencephalography Sleep Algorithms Sleep Stages Infant, Newborn
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Two-dimensional CNN-based distinction of human emotions from EEG channels selected by multi-objective evolutionary algorithm.

Scientific reports Mar 3, 2022
In this study we explore how different levels of emotional intensity (Arousal) and pleasantness (Valence) are reflected in electroencephalographic (EEG) signals. We performed the experiments on EEG data of 32 subjects from the DEAP public dataset, wh...
Arousal Emotions Electroencephalography Neural Networks, Computer Humans Algorithms
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An interactive framework for the detection of ictal and interictal activities: Cross-species and stand-alone implementation.

Computer methods and programs in biomedicine Mar 2, 2022
BACKGROUND AND OBJECTIVE: Despite advances on signal analysis and artificial intelligence, visual inspection is the gold standard in event detection on electroencephalographic recordings. This process requires much time of clinical experts on both an...
Humans Epilepsy Seizures Animals Mice Electroencephalography Artificial Intelligence Machine Learning
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Automated seizure activity tracking and onset zone localization from scalp EEG using deep neural networks.

PloS one Feb 28, 2022
We propose a novel neural network architecture, SZTrack, to detect and track the spatio-temporal propagation of seizure activity in multichannel EEG. SZTrack combines a convolutional neural network encoder operating on individual EEG channels with re...
Female Male Electroencephalography Humans Scalp Epilepsy Neural Networks, Computer Seizures
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Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning.

Nature communications Feb 25, 2022
Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these components have not been reported. Here, we propose an ex...
Wakefulness Consciousness Arousal Anesthesia, General Electroencephalography Humans Deep Learning Brain Injuries
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Classification of Electroencephalogram Signal for Developing Brain-Computer Interface Using Bioinspired Machine Learning Approach.

Computational intelligence and neuroscience Feb 25, 2022
Transforming human intentions into patterns to direct the devices connected externally without any body movements is called Brain-Computer Interface (BCI). It is specially designed for rehabilitation patients to overcome their disabilities. Electroen...
Adult User-Computer Interface Machine Learning Humans Electroencephalography Age Factors Algorithms Neural Networks, Computer Young Adult Brain-Computer Interfaces
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Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach.

Sensors (Basel, Switzerland) Feb 24, 2022
Extensive possibilities of applications have rendered emotion recognition ineluctable and challenging in the fields of computer science as well as in human-machine interaction and affective computing. Fields that, in turn, are increasingly requiring ...
Electroencephalography Neural Networks, Computer Arousal Deep Learning Humans Emotions
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Resting-state electroencephalography based deep-learning for the detection of Parkinson's disease.

PloS one Feb 24, 2022
Parkinson's disease (PD) is one of the most serious and challenging neurodegenerative disorders to diagnose. Clinical diagnosis on observing motor symptoms is the gold standard, yet by this point nerve cells are degenerated resulting in a lower effic...
Middle Aged Deep Learning Electroencephalography Wavelet Analysis Parkinson Disease Aged Humans Mental Health Machine Learning Neural Networks, Computer Male Female Membrane Potentials
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Conditional generative adversarial networks applied to EEG data can inform about the inter-relation of antagonistic behaviors on a neural level.

Communications biology Feb 21, 2022
Goal-directed actions frequently require a balance between antagonistic processes (e.g., executing and inhibiting a response), often showing an interdependency concerning what constitutes goal-directed behavior. While an inter-dependency of antagonis...
Humans Artificial Intelligence Evoked Potentials Inhibition, Psychological Electroencephalography
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Spatiotemporal dynamics in spiking recurrent neural networks using modified-full-FORCE on EEG signals.

Scientific reports Feb 21, 2022
Methods on modelling the human brain as a Complex System have increased remarkably in the literature as researchers seek to understand the underlying foundations behind cognition, behaviour, and perception. Computational methods, especially Graph The...
Brain Cognition Models, Neurological Humans Neural Networks, Computer Perception Behavior Electroencephalography Neurons
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