AIMC Topic: Electroencephalography
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Prediction of central neuropathic pain in spinal cord injury based on EEG classifier.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
May 23, 2018
OBJECTIVES: To create a classifier based on electroencephalography (EEG) to identify spinal cord injured (SCI) participants at risk of developing central neuropathic pain (CNP) by comparing them with patients who had already developed pain and with a...
Tensor-driven extraction of developmental features from varying paediatric EEG datasets.
Journal of neural engineering
May 21, 2018
OBJECTIVE: Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usabil...
A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.
Computers in biology and medicine
May 17, 2018
The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic sei...
Differential Effects of Simulated Cortical Network Lesions on Synchrony and EEG Complexity.
International journal of neural systems
May 15, 2018
Brain function has been proposed to arise as a result of the coordinated activity between distributed brain areas. An important issue in the study of brain activity is the characterization of the synchrony among these areas and the resulting complexi...
Machine Learning for Outcome Prediction in Electroencephalograph (EEG)-Monitored Children in the Intensive Care Unit.
Journal of child neurology
May 13, 2018
The aim of this study was to evaluate the performance of models predicting in-hospital mortality in critically ill children undergoing continuous electroencephalography (cEEG) in the intensive care unit (ICU). We evaluated the performance of machine ...
Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram.
Neural networks : the official journal of the International Neural Network Society
May 7, 2018
Seizure prediction has attracted growing attention as one of the most challenging predictive data analysis efforts to improve the life of patients with drug-resistant epilepsy and tonic seizures. Many outstanding studies have reported great results i...
A fresh look at functional link neural network for motor imagery-based brain-computer interface.
Journal of neuroscience methods
May 4, 2018
BACKGROUND: Artificial neural networks (ANNs) are one of the widely used classifiers in the brain-computer interface (BCI) systems-based on noninvasive electroencephalography (EEG) signals. Among the different ANN architectures, the most commonly app...
How Much Does Movement and Location Encoding Impact Prefrontal Cortex Activity? An Algorithmic Decoding Approach in Freely Moving Rats.
eNeuro
Apr 27, 2018
Specialized brain structures encode spatial locations and movements, yet there is growing evidence that this information is also represented in the rodent medial prefrontal cortex (mPFC). Disambiguating such information from the encoding of other typ...
Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network.
Journal of medical systems
Apr 23, 2018
In this study, we propose a method for the automated detection of obstructive sleep apnea (OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network (CNN). A CNN model was designed with six optimized convolution layers incl...
Automated EEG-based screening of depression using deep convolutional neural network.
Computer methods and programs in biomedicine
Apr 18, 2018
In recent years, advanced neurocomputing and machine learning techniques have been used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In this paper, a novel computer model is presented for EEG-based screening of de...
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