AIMC Topic: Electroencephalography

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Automated spectrographic seizure detection using convolutional neural networks.

Seizure Jul 8, 2019
PURPOSE: Non-convulsive seizures are common in critically ill patients, and delays in diagnosis contribute to increased morbidity and mortality. Many intensive care units employ continuous EEG (cEEG) for seizure monitoring. Although cEEG is continuou...
Image Interpretation, Computer-Assisted Electroencephalography Seizures Critical Care Humans Neural Networks, Computer Retrospective Studies Sensitivity and Specificity
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Exploring Douglas-Peucker Algorithm in the Detection of Epileptic Seizure from Multicategory EEG Signals.

BioMed research international Jul 7, 2019
Discovering the concealed patterns of Electroencephalogram (EEG) signals is a crucial part in efficient detection of epileptic seizures. This study develops a new scheme based on Douglas-Peucker algorithm (DP) and principal component analysis (PCA) f...
Electroencephalography Female Humans Epilepsy Male Databases, Factual Signal Processing, Computer-Assisted Support Vector Machine
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Body Patches in Inferior Temporal Cortex Encode Categories with Different Temporal Dynamics.

Journal of cognitive neuroscience Jul 5, 2019
An unresolved question in cognitive neuroscience is how representations of object categories at different levels (basic and superordinate) develop during the course of the neural response within an area. To address this, we decoded categories of diff...
Animals Male Electroencephalography Concept Formation Macaca mulatta Time Factors Support Vector Machine Magnetic Resonance Imaging Pattern Recognition, Visual Temporal Lobe Electrophysiological Phenomena
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Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks.

PloS one Jul 5, 2019
State Visual Evoked Potentials (SSVEPs) arise from a resonance phenomenon in the visual cortex that is produced by a repetitive visual stimulus. SSVEPs have long been considered a steady-state response resulting from purely oscillatory components pha...
Models, Neurological Electroencephalography Humans Brain-Computer Interfaces Neural Networks, Computer Evoked Potentials, Visual Algorithms Adult Photic Stimulation Male Visual Cortex Middle Aged
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Bypassing the volume conduction effect by multilayer neural network for effective connectivity estimation.

Medical & biological engineering & computing Jul 4, 2019
Differentiation of real interactions between different brain regions from spurious ones has been a challenge in neuroimaging researches. While using electroencephalographic data, those spurious interactions are mostly caused by the volume conduction ...
Brain Computer Simulation Brain Mapping Humans Electroencephalography Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms
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Learning-based classification of valence emotion from electroencephalography.

The International journal of neuroscience Jul 3, 2019
The neuroimaging research field has been revolutionized with the development of human cognitive functions without the use of brain pathways. To assist such systems, electroencephalography (EEG) based measures play an important role. In this study, th...
Young Adult Adult Models, Theoretical Neural Networks, Computer Machine Learning Brain Humans Datasets as Topic Brain Waves Recognition, Psychology Emotions Electroencephalography Signal Processing, Computer-Assisted
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Comparison of machine learning models for seizure prediction in hospitalized patients.

Annals of clinical and translational neurology Jun 27, 2019
OBJECTIVE: To compare machine learning methods for predicting inpatient seizures risk and determine the feasibility of 1-h screening EEG to identify low-risk patients (<5% seizures risk in 48 h).
Monitoring, Physiologic Electroencephalography Seizures Critical Care Young Adult Male Humans Cohort Studies Neural Networks, Computer Female Machine Learning Aged Aged, 80 and over
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Characterization of Industry 4.0 Lean Management Problem-Solving Behavioral Patterns Using EEG Sensors and Deep Learning.

Sensors (Basel, Switzerland) Jun 26, 2019
Industry 4.0 leaders solve problems all of the time. Successful problem-solving behavioral pattern choice determines organizational and personal success, therefore a proper understanding of the problem-solving-related neurological dynamics is sure to...
Humans Deep Learning Electroencephalography Industry Problem Solving
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Brain wave classification using long short-term memory network based OPTICAL predictor.

Scientific reports Jun 24, 2019
Brain-computer interface (BCI) systems having the ability to classify brain waves with greater accuracy are highly desirable. To this end, a number of techniques have been proposed aiming to be able to classify brain waves with high accuracy. However...
Electroencephalography Signal Processing, Computer-Assisted Benchmarking Humans Brain Waves Neural Networks, Computer Support Vector Machine
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An automatic single-channel EEG-based sleep stage scoring method based on hidden Markov Model.

Journal of neuroscience methods Jun 19, 2019
OBJECTIVE: Sleep stage scoring is essential for diagnosing sleep disorders. Visual scoring of sleep stages is very time-consuming and prone to human errors. In this work, we introduce an efficient approach to improve the accuracy of sleep stage scori...
Markov Chains Sleep Stages Humans Support Vector Machine Female Electroencephalography Signal Processing, Computer-Assisted Young Adult Adult Male
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