AIMC Topic: Electroencephalography

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Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study.

Journal of medical Internet research Feb 10, 2023
BACKGROUND: Most existing automated sleep staging methods rely on multimodal data, and scoring a specific epoch requires not only the current epoch but also a sequence of consecutive epochs that precede and follow the epoch.
Sleep Sleep Stages Algorithms Electroencephalography Humans Neural Networks, Computer
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Classification of Motor Imagery EEG Signals Based on Data Augmentation and Convolutional Neural Networks.

Sensors (Basel, Switzerland) Feb 9, 2023
In brain-computer interface (BCI) systems, motor imagery electroencephalography (MI-EEG) signals are commonly used to detect participant intent. Many factors, including low signal-to-noise ratios and few high-quality samples, make MI classification d...
Algorithms Electroencephalography Intention Imagery, Psychotherapy Humans Neural Networks, Computer
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A Spatiotemporal Graph Attention Network Based on Synchronization for Epileptic Seizure Prediction.

IEEE journal of biomedical and health informatics Feb 3, 2023
Accurate early prediction of epileptic seizures can provide timely treatment for patients. Previous studies have mainly focused on a single temporal or spatial dimension, making it difficult to take both relationships into account. Therefore, the eff...
Humans Deep Learning Seizures Electroencephalography Epilepsy
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Cognitive Depression Detection Cyber-Medical System Based on EEG Analysis and Deep Learning Approaches.

IEEE journal of biomedical and health informatics Feb 3, 2023
Long-term depression and negative emotional cycles affect life quality and work productivity. However, depression is not easy to detect, with current methods mostly relying on scales that make it impossible to quickly and directly measure the severit...
Deep Learning Depression Electroencephalography Cognition Humans Emotions
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Mutual Information-Driven Subject-Invariant and Class-Relevant Deep Representation Learning in BCI.

IEEE transactions on neural networks and learning systems Feb 3, 2023
In recent years, deep learning-based feature representation methods have shown a promising impact on electroencephalography (EEG)-based brain-computer interface (BCI). Nonetheless, owing to high intra- and inter-subject variabilities, many studies on...
Neural Networks, Computer Machine Learning Humans Calibration Brain-Computer Interfaces Algorithms Electroencephalography
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EEG emotion recognition using improved graph neural network with channel selection.

Computer methods and programs in biomedicine Feb 1, 2023
BACKGROUND AND OBJECTIVE: Emotion classification tasks based on electroencephalography (EEG) are an essential part of artificial intelligence, with promising applications in healthcare areas such as autism research and emotion detection in pregnant w...
Pregnancy Female Artificial Intelligence Brain Emotions Electroencephalography Humans Neural Networks, Computer
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Research of intent recognition in rehabilitation robots: a systematic review.

Disability and rehabilitation. Assistive technology Jan 25, 2023
PURPOSE: Rehabilitation robots with intent recognition are helping people with dysfunction to enjoy better lives. Many rehabilitation robots with intent recognition have been developed by academic institutions and commercial companies. However, there...
Rehabilitation Intention Exoskeleton Device Electroencephalography Electromyography Humans Biomechanical Phenomena Robotics
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An Efficient Machine Learning-Based Emotional Valence Recognition Approach Towards Wearable EEG.

Sensors (Basel, Switzerland) Jan 21, 2023
Emotion artificial intelligence (AI) is being increasingly adopted in several industries such as healthcare and education. Facial expressions and tone of speech have been previously considered for emotion recognition, yet they have the drawback of be...
Wearable Electronic Devices Artificial Intelligence Electroencephalography Emotions Humans Machine Learning
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Extracting a Novel Emotional EEG Topographic Map Based on a Stacked Autoencoder Network.

Journal of healthcare engineering Jan 19, 2023
Emotion recognition based on brain signals has increasingly become attractive to evaluate human's internal emotional states. Conventional emotion recognition studies focus on developing machine learning and classifiers. However, most of these methods...
Emotions Electroencephalography Humans Brain Mapping Neural Networks, Computer Brain
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Precise Discrimination for Multiple Etiologies of Dementia Cases Based on Deep Learning with Electroencephalography.

Neuropsychobiology Jan 19, 2023
INTRODUCTION: It is critical to develop accurate and universally available biomarkers for dementia diseases to appropriately deal with the dementia problems under world-wide rapid increasing of patients with dementia. In this sense, electroencephalog...
Humans Alzheimer Disease Deep Learning Lewy Body Disease Electroencephalography
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