AIMC Topic: Electroencephalography
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Reachability Analysis of Neural Masses and Seizure Control Based on Combination Convolutional Neural Network.
International journal of neural systems
Aug 2, 2019
Epileptic seizures arise from synchronous firing of multiple spatially separated neural masses; therefore, many synchrony measures are used for seizure detection and characterization. However, synchrony measures reflect only the overall interaction s...
Advances in computer-aided medical systems and clinical measurement.
Computer assisted surgery (Abingdon, England)
Aug 2, 2019
Electroencephalogram Spectral Moments for the Detection of Nocturnal Hypoglycemia.
IEEE journal of biomedical and health informatics
Jul 29, 2019
Hypoglycemia or low blood glucose is the most feared complication of insulin treatment of diabetes. For people with diabetes, the mismatch between the insulin therapy and the body's physiology could increase the risk of hypoglycemia. Nocturnal hypogl...
Epileptic Seizure Detection with EEG Textural Features and Imbalanced Classification Based on EasyEnsemble Learning.
International journal of neural systems
Jul 29, 2019
Imbalance data classification is a challenging task in automatic seizure detection from electroencephalogram (EEG) recordings when the durations of non-seizure periods are much longer than those of seizure activities. An imbalanced learning model is ...
Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jul 25, 2019
OBJECTIVE: Electroencephalogram (EEG) reactivity is a robust predictor of neurological recovery after cardiac arrest, however interrater-agreement among electroencephalographers is limited. We sought to evaluate the performance of machine learning me...
Biometric identification of listener identity from frequency following responses to speech.
Journal of neural engineering
Jul 23, 2019
OBJECTIVE: We investigate the biometric specificity of the frequency following response (FFR), an EEG marker of early auditory processing that reflects phase-locked activity from neural ensembles in the auditory cortex and subcortex (Chandrasekaran a...
Intracortical neural activity distal to seizure-onset-areas predicts human focal seizures.
PloS one
Jul 22, 2019
The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in...
Is it possible to detect cerebral dominance via EEG signals by using deep learning?
Medical hypotheses
Jul 20, 2019
Each brain hemisphere is dominant for certain functions such as speech. The determination of speech laterality prior to surgery is of paramount importance for accurate risk prediction. In this study, we aimed to determine speech laterality via EEG si...
Novel drug-independent sedation level estimation based on machine learning of quantitative frontal electroencephalogram features in healthy volunteers.
British journal of anaesthesia
Jul 18, 2019
BACKGROUND: Sedation indicators based on a single quantitative EEG (QEEG) feature have been criticised for their limited performance. We hypothesised that integration of multiple QEEG features into a single sedation-level estimator using a machine le...
Efficient Epileptic Seizure Prediction Based on Deep Learning.
IEEE transactions on biomedical circuits and systems
Jul 17, 2019
Epilepsy is one of the world's most common neurological diseases. Early prediction of the incoming seizures has a great influence on epileptic patients' life. In this paper, a novel patient-specific seizure prediction technique based on deep learning...
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