AIMC Topic: Electroencephalography

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Real-time Inference and Detection of Disruptive EEG Networks for Epileptic Seizures.

Scientific reports May 26, 2020
Recent studies in brain science and neurological medicine paid a particular attention to develop machine learning-based techniques for the detection and prediction of epileptic seizures with electroencephalogram (EEG). As a noninvasive monitoring met...
Female Male Infant Child Electroencephalography Diagnosis, Computer-Assisted Child, Preschool Epilepsy Humans Seizures Machine Learning Biomedical Engineering Brain
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The interplay between multisensory integration and perceptual decision making.

NeuroImage May 23, 2020
Facing perceptual uncertainty, the brain combines information from different senses to make optimal perceptual decisions and to guide behavior. However, decision making has been investigated mostly in unimodal contexts. Thus, how the brain integrates...
Electroencephalography Supervised Machine Learning Psychomotor Performance Cerebral Cortex Functional Neuroimaging Models, Theoretical Decision Making Signal Detection, Psychological Concept Formation Pattern Recognition, Visual Auditory Perception Humans Adult Male Female Young Adult
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Detection of Depression and Scaling of Severity Using Six Channel EEG Data.

Journal of medical systems May 21, 2020
Depression is a psychiatric problem which affects the growth of a person, like how a person thinks, feels and behaves. The major reason behind wrong diagnosis of depression is absence of any laboratory test for detection as well as severity scaling o...
Support Vector Machine Brain Electroencephalography Female Signal Processing, Computer-Assisted Adult Humans Depressive Disorder Male Algorithms Severity of Illness Index
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An improved common spatial pattern combined with channel-selection strategy for electroencephalography-based emotion recognition.

Medical engineering & physics May 19, 2020
Emotional human-computer interaction (HCI) has become an important research area in the fields of artificial intelligence and cognitive science, owing to the requirement for active emotion perception. To enhance the performance of electroencephalogra...
Algorithms Emotions Humans Electroencephalography Artificial Intelligence
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Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.

NeuroImage May 18, 2020
Predicting biomedical outcomes from Magnetoencephalography and Electroencephalography (M/EEG) is central to applications like decoding, brain-computer-interfaces (BCI) or biomarker development and is facilitated by supervised machine learning. Yet, m...
Humans Machine Learning Computer Simulation Cerebral Cortex Electroencephalography Electromyography Adult Brain Waves Signal Processing, Computer-Assisted Supervised Machine Learning Models, Theoretical Magnetoencephalography Regression Analysis
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Industry 4.0 Lean Shopfloor Management Characterization Using EEG Sensors and Deep Learning.

Sensors (Basel, Switzerland) May 18, 2020
Achieving the shift towards Industry 4.0 is only feasible through the active integration of the shopfloor into the transformation process. Several shopfloor management (SM) systems can aid this conversion. They form two major factions. The first incl...
Brain-Computer Interfaces Manufacturing Industry Humans Deep Learning Brain Electroencephalography
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EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

Computational and mathematical methods in medicine May 16, 2020
In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) signal analysis methods, using EEG signals to monitor human health has become a very popular research fi...
Electroencephalography Computational Biology Brain Waves Head Movements Humans Signal Processing, Computer-Assisted Fatigue Logistic Models Ocular Physiological Phenomena Neural Networks, Computer Wavelet Analysis Support Vector Machine Algorithms
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EEG classification across sessions and across subjects through transfer learning in motor imagery-based brain-machine interface system.

Medical & biological engineering & computing May 11, 2020
Transfer learning enables the adaption of models to handle mismatches of distributions across sessions or across subjects. In this paper, we proposed a new transfer learning algorithm to classify motor imagery EEG data. By analyzing the power spectru...
Brain-Computer Interfaces Imagery, Psychotherapy Signal Processing, Computer-Assisted Hand Healthy Volunteers Male Support Vector Machine Electroencephalography Humans Machine Learning Algorithms Female Young Adult
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Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning.

Computational and mathematical methods in medicine May 8, 2020
Electroencephalography (EEG) plays an import role in monitoring the brain activities of patients with epilepsy and has been extensively used to diagnose epilepsy. Clinically reading tens or even hundreds of hours of EEG recordings is very time consum...
Diagnosis, Computer-Assisted Deep Learning Child Computational Biology Electroencephalography Signal Processing, Computer-Assisted Humans Epilepsy Fourier Analysis Neural Networks, Computer Seizures Databases, Factual
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Time-resolved correspondences between deep neural network layers and EEG measurements in object processing.

Vision research May 7, 2020
The ventral visual stream is known to be organized hierarchically, where early visual areas processing simplistic features feed into higher visual areas processing more complex features. Hierarchical convolutional neural networks (CNNs) were largely ...
Electroencephalography Signal Processing, Computer-Assisted Visual Perception Visual Cortex Humans Neural Networks, Computer Time Factors
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