AIMC Topic: Electroencephalography

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A Cross-modality Deep Learning Method for Measuring Decision Confidence from Eye Movement Signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Electroencephalography (EEG) signals can effectively measure the level of human decision confidence. However, it is difficult to acquire EEG signals in practice due to the ex-pensive cost and complex operation, while eye movement signals are much eas...
Mental Processes Eye Movements Electroencephalography Humans Deep Learning
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A Pruned Deep Learning Approach for Classification of Motor Imagery Electroencephalography Signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
The Deep Learning (DL) approach has been gaining much popularity in recent years in the development of electroencephalogram (EEG) based Motor Imagery (MI) Brain-Computer Interface (BCI) systems, aiming to improve the performance of existing stroke re...
Imagery, Psychotherapy Deep Learning Electroencephalography Humans Neural Networks, Computer Algorithms
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A streamable large-scale clinical EEG dataset for Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Deep Learning has revolutionized various fields, including Computer Vision, Natural Language Processing, as well as Biomedical research. Within the field of neuroscience, specifically in electrophysiological neuroimaging, researchers are starting to ...
Humans Deep Learning Electroencephalography Neurosciences Brain Biomedical Research
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Label Alignment Improves EEG-based Machine Learning-based Classification of Traumatic Brain Injury.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Machine learning and deep learning algorithms have paved the way for improved analysis of biomedical data which has led to a better understanding of various biological conditions. However, one major hindrance to leveraging the potential of machine le...
Mice Brain Injuries, Traumatic Electroencephalography Humans Algorithms Machine Learning Animals
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A novel deep learning approach using AlexNet for the classification of electroencephalograms in Alzheimer's Disease and Mild Cognitive Impairment.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Alzheimer's Disease (AD) is the most common form of dementia. Mild Cognitive Impairment (MCI) is the term given to the stage describing prodromal AD and represents a 'risk factor' in early-stage AD diagnosis from normal cognitive decline due to agein...
Electroencephalography Humans Alzheimer Disease Aging Deep Learning Cognitive Dysfunction
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MEMD-HHT based Emotion Detection from EEG using 3D CNN.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
In this study, the Multivariate Empirical Mode Decomposition (MEMD) is applied to multichannel EEG to obtain scale-aligned intrinsic mode functions (IMFs) as input features for emotion detection. The IMFs capture local signal variation related to emo...
Emotions Electroencephalography Arousal Neural Networks, Computer Databases, Factual
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Constructive Fuzzy Cognitive Map for Depression Severity Estimation.

Studies in health technology and informatics May 25, 2022
Depression is a common and serious medical disorder that negatively affects the mood and the emotions of people, especially adolescents. In this paper, a novel framework for automatically creating Fuzzy Cognitive Maps (FCMs) is proposed. It is applie...
Humans Algorithms Severity of Illness Index Electroencephalography Cognition Depression Fuzzy Logic Adolescent
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Classifying Numbers from EEG Data - Which Neural Network Architecture Performs Best?

Studies in health technology and informatics May 16, 2022
This paper presents a comparison of deep learning models for classifying P300 events, i.e., event-related potentials of the brain triggered during the human decision-making process. The evaluated models include CNN, (Bi | Deep | CNN-) LSTM, ConvLSTM,...
Humans Child Neural Networks, Computer Electroencephalography
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[Epilepsy detection and analysis method for specific patient based on data augmentation and deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Apr 25, 2022
In recent years, epileptic seizure detection based on electroencephalogram (EEG) has attracted the widespread attention of the academic. However, it is difficult to collect data from epileptic seizure, and it is easy to cause over fitting phenomenon ...
Wavelet Analysis Seizures Signal Processing, Computer-Assisted Electroencephalography Algorithms Epilepsy Deep Learning Child Humans
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Frontal lobe real-time EEG analysis using machine learning techniques for mental stress detection.

Journal of integrative neuroscience Jan 28, 2022
Stress has become a dangerous health problem in our life, especially in student education journey. Accordingly, previous methods have been conducted to detect mental stress based on biological and biochemical effects. Moreover, hormones, physiologica...
Signal Processing, Computer-Assisted Adult Female Fourier Analysis Sensitivity and Specificity Frontal Lobe Male Young Adult Humans Support Vector Machine Stress, Psychological Machine Learning Electroencephalography
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