AIMC Topic: Electroencephalography

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Applying Common Spatial Pattern and Convolutional Neural Network to Classify Movements via EEG Signals.

Clinical EEG and neuroscience Mar 24, 2024
Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to enhancing the control of external prostheses by accurately distinguishing various movements through brain signals. This innovation can provide comfor...
Movement Young Adult Algorithms Electroencephalography Adult Brain Wrist Signal Processing, Computer-Assisted Female Humans Brain-Computer Interfaces Male Neural Networks, Computer
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Deep learning approaches for seizure video analysis: A review.

Epilepsy & behavior : E&B Mar 23, 2024
Seizure events can manifest as transient disruptions in the control of movements which may be organized in distinct behavioral sequences, accompanied or not by other observable features such as altered facial expressions. The analysis of these clinic...
Humans Video Recording Deep Learning Electroencephalography Seizures
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Using multivariate pattern analysis to increase effect sizes for event-related potential analyses.

Psychophysiology Mar 22, 2024
Multivariate pattern analysis (MVPA) approaches can be applied to the topographic distribution of event-related potential (ERP) signals to "decode" subtly different stimulus classes, such as different faces or different orientations. These approaches...
Electroencephalography Signal Processing, Computer-Assisted Evoked Potentials Multivariate Analysis Male Support Vector Machine Data Interpretation, Statistical Young Adult Adult Humans Female
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A hybrid EEG classification model using layered cascade deep learning architecture.

Medical & biological engineering & computing Mar 20, 2024
The problem of multi-class classification is always a challenge in the field of EEG (electroencephalogram)-based seizure detection. The traditional studies focus on computing or learning a set of features from EEG to distinguish between different pat...
Electroencephalography Seizures Signal Processing, Computer-Assisted Algorithms Deep Learning Principal Component Analysis Humans
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eDeeplepsy: An artificial neural framework to reveal different brain states in children with epileptic spasms.

Epilepsy & behavior : E&B Mar 20, 2024
OBJECTIVE: Despite advances, analysis and interpretation of EEG still essentially rely on visual inspection by a super-specialized physician. Considering the vast amount of data that composes the EEG, much of the detail inevitably escapes ordinary hu...
Epilepsy Humans Deep Learning Adolescent Female Male Neural Networks, Computer Child, Preschool Child Infant Brain Electroencephalography
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Prediction of cognitive conflict during unexpected robot behavior under different mental workload conditions in a physical human-robot collaboration.

Journal of neural engineering Mar 19, 2024
. Brain-computer interface (BCI) technology is poised to play a prominent role in modern work environments, especially a collaborative environment where humans and machines work in close proximity, often with physical contact. In a physical human rob...
Humans Electroencephalography Cognition Workload Robotics Brain-Computer Interfaces
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PMF-CNN: parallel multi-band fusion convolutional neural network for SSVEP-EEG decoding.

Biomedical physics & engineering express Mar 8, 2024
Steady-state visual evoked potential (SSVEP) is a key technique of electroencephalography (EEG)-based brain-computer interfaces (BCI), which has been widely applied to neurological function assessment and postoperative rehabilitation. However, accura...
Electroencephalography Evoked Potentials, Visual Algorithms Brain Neural Networks, Computer
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Detecting cognitive traits and occupational proficiency using EEG and statistical inference.

Scientific reports Mar 7, 2024
Machine learning (ML) is widely used in classification tasks aimed at detecting various cognitive states or neurological diseases using noninvasive electroencephalogram (EEG) time series. However, successfully detecting specific cognitive skills in a...
Cognition Electroencephalography Humans Machine Learning
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Evaluating the performance of the cognitive workload model with subjective endorsement in addition to EEG.

Medical & biological engineering & computing Mar 3, 2024
The aptitude-oriented exercises from almost all domains impose cognitive load on their operators. Evaluating such load poses several challenges owing to many factors like measurement mode and complexity, nature of the load, overloading conditions, et...
Humans Female Young Adult Cognition Support Vector Machine Electroencephalography Adult Male Workload Task Performance and Analysis
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A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure.

BMC medical informatics and decision making Mar 1, 2024
INTRODUCTION: Epilepsy is a disease characterized by an excessive discharge in neurons generally provoked without any external stimulus, known as convulsions. About 2 million people are diagnosed each year in the world. This process is carried out by...
Algorithms Electroencephalography Seizures Epilepsy Humans Artificial Intelligence Machine Learning
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