AIMC Topic: Electroencephalography

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A Combinatorial Deep Learning Structure for Precise Depth of Anesthesia Estimation From EEG Signals.

IEEE journal of biomedical and health informatics Sep 3, 2021
Electroencephalography (EEG) is commonly used to measure the depth of anesthesia (DOA) because EEG reflects surgical pain and state of the brain. However, precise and real-time estimation of DOA index for painful surgical operations is challenging du...
Humans Deep Learning Electroencephalography Anesthesia Neural Networks, Computer Algorithms
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Notable Papers and New Directions in Sensors, Signals, and Imaging Informatics.

Yearbook of medical informatics Sep 3, 2021
OBJECTIVE: To identify and highlight research papers representing noteworthy developments in signals, sensors, and imaging informatics in 2020.
Machine Learning Humans Biometry Electroencephalography Reproducibility of Results Neural Networks, Computer Medical Informatics Diagnostic Imaging
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Deep learning based smart health monitoring for automated prediction of epileptic seizures using spectral analysis of scalp EEG.

Physical and engineering sciences in medicine Sep 1, 2021
Being one of the most prevalent neurological disorders, epilepsy affects the lives of patients through the infrequent occurrence of spontaneous seizures. These seizures can result in serious injuries or unexpected deaths in individuals due to acciden...
Humans Seizures Quality of Life Deep Learning Scalp Algorithms Electroencephalography Epilepsy
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Generative Adversarial Networks-Based Data Augmentation for Brain-Computer Interface.

IEEE transactions on neural networks and learning systems Aug 31, 2021
The performance of a classifier in a brain-computer interface (BCI) system is highly dependent on the quality and quantity of training data. Typically, the training data are collected in a laboratory where the users perform tasks in a controlled envi...
Machine Learning Algorithms Computer Simulation Humans Neural Networks, Computer Young Adult Adult Male Female Reproducibility of Results Imagination Healthy Volunteers Psychomotor Performance Brain-Computer Interfaces Electroencephalography Attention
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Deep learning multimodal fNIRS and EEG signals for bimanual grip force decoding.

Journal of neural engineering Aug 31, 2021
Non-invasive brain-machine interfaces (BMIs) offer an alternative, safe and accessible way to interact with the environment. To enable meaningful and stable physical interactions, BMIs need to decode forces. Although previously addressed in the unima...
Electroencephalography Brain-Computer Interfaces Deep Learning Hand Strength Humans Spectroscopy, Near-Infrared
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Fused CNN-LSTM deep learning emotion recognition model using electroencephalography signals.

The International journal of neuroscience Aug 27, 2021
The traditional machine learning-based emotion recognition models have shown effective performance for classifying Electroencephalography (EEG) based emotions. The different machine learning algorithms outperform the various EEG based emotion models...
Machine Learning Algorithms Emotions Electroencephalography Deep Learning
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Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data.

The journal of pain Aug 21, 2021
Recent attempts to utilize machine learning (ML) to predict pain-related outcomes from Electroencephalogram (EEG) data demonstrate promising results. The primary aim of this review was to evaluate the effectiveness of ML algorithms for predicting pai...
Machine Learning Algorithms Treatment Outcome Pain Measurement Phenotype Electroencephalography Humans Pain
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I, robot: depression plays different roles in human-human and human-robot interactions.

Translational psychiatry Aug 21, 2021
Socially engaging robots have been increasingly applied to alleviate depressive symptoms and to improve the quality of social life among different populations. Seeing that depression negatively influences social reward processing in everyday interact...
Electroencephalography Humans Reward Depression Evoked Potentials Robotics
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Generalized Deep Learning EEG Models for Cross-Participant and Cross-Task Detection of the Vigilance Decrement in Sustained Attention Tasks.

Sensors (Basel, Switzerland) Aug 20, 2021
Tasks which require sustained attention over a lengthy period of time have been a focal point of cognitive fatigue research for decades, with these tasks including air traffic control, watchkeeping, baggage inspection, and many others. Recent researc...
Wakefulness Humans Aviation Deep Learning Electroencephalography Attention
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Inter-database validation of a deep learning approach for automatic sleep scoring.

PloS one Aug 16, 2021
STUDY OBJECTIVES: Development of inter-database generalizable sleep staging algorithms represents a challenge due to increased data variability across different datasets. Sharing data between different centers is also a problem due to potential restr...
Deep Learning Algorithms Electroencephalography Polysomnography Humans Sleep Databases, Factual Neural Networks, Computer Sleep Stages
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