AIMC Topic: Electroencephalography
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Latent Phase Identification of High-Frequency Micro-Scale Gamma Spike Transients in the Hypoxic Ischemic EEG of Preterm Fetal Sheep Using Spectral Analysis and Fuzzy Classifiers.
Sensors (Basel, Switzerland)
Mar 5, 2020
Premature babies are at high risk of serious neurodevelopmental disabilities, which in many cases are related to perinatal hypoxic-ischemic encephalopathy (HIE). Studies of neuroprotection in animal models consistently suggest that treatment must be ...
SeizureBank: A Repository of Analysis-ready Seizure Signal Data.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Approximately 60 million people worldwide suffer from epileptic seizures. A key challenge in machine learning ap proaches for epilepsy research is the lack of a data resource of analysis-ready (no additional preprocessing is needed when using the dat...
A Residual Based Attention Model for EEG Based Sleep Staging.
IEEE journal of biomedical and health informatics
Mar 3, 2020
Sleep staging is to score the sleep state of a subject into different sleep stages such as Wake and Rapid Eye Movement (REM). It plays an indispensable role in the diagnosis and treatment of sleep disorders. As manual sleep staging through well-train...
Automated classification of five seizure onset patterns from intracranial electroencephalogram signals.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Mar 3, 2020
OBJECTIVE: The electroencephalographic (EEG) signals contain information about seizures and their onset location. There are several seizure onset patterns reported in the literature, and these patterns have clinical significance. In this work, we pro...
Constructing large-scale cortical brain networks from scalp EEG with Bayesian nonnegative matrix factorization.
Neural networks : the official journal of the International Neural Network Society
Mar 3, 2020
A large-scale network provides a high hierarchical level for understanding the adaptive adjustment of the human brain during cognition processes. Since high spatial resolution is required, most of the related works are based on functional magnetic re...
A-phase classification using convolutional neural networks.
Medical & biological engineering & computing
Mar 2, 2020
A series of short events, called A-phases, can be observed in the human electroencephalogram (EEG) during Non-Rapid Eye Movement (NREM) sleep. These events can be classified in three groups (A1, A2, and A3) according to their spectral contents, and a...
Assistance Robotics and Biosensors 2019.
Sensors (Basel, Switzerland)
Feb 29, 2020
This Special Issue is focused on breakthrough developments in the field of assistive and rehabilitation robotics. The selected contributions include current scientific progress from biomedical signal processing and cover applications to myoelectric p...
Computer-assisted estimation of interictal discharge burden in idiopathic generalized epilepsy.
Epilepsy & behavior : E&B
Feb 27, 2020
Investigating the temporal dynamics of electroencephalogram (EEG) microstates using recurrent neural networks.
Human brain mapping
Feb 24, 2020
Electroencephalogram (EEG) microstates that represent quasi-stable, global neuronal activity are considered as the building blocks of brain dynamics. Therefore, the analysis of microstate sequences is a promising approach to understand fast brain dyn...
A Comprehensive Machine-Learning-Based Software Pipeline to Classify EEG Signals: A Case Study on PNES vs. Control Subjects.
Sensors (Basel, Switzerland)
Feb 24, 2020
The diagnosis of psychogenic nonepileptic seizures (PNES) by means of electroencephalography (EEG) is not a trivial task during clinical practice for neurologists. No clear PNES electrophysiological biomarker has yet been found, and the only tool ava...
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