Analysis and automatic identification of sleep stages using higher order spectra.
about
Adaptive filtering and random variables coefficient for analyzing functional magnetic resonance imaging data.Adaptive cerebellar spiking model embedded in the control loop: context switching and robustness against noise.A General Approach for Quantifying Nonlinear Connectivity in the Nervous System Based on Phase Coupling.Disrupted directed connectivity along the cingulate cortex determines vigilance after sleep deprivation.Guidelines for the recording and evaluation of pharmaco-sleep studies in man: the International Pharmaco-EEG Society (IPEG).Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals.Unsupervised Estimation of Mouse Sleep Scores and Dynamics Using a Graphical Model of Electrophysiological Measurements.FASTER: an unsupervised fully automated sleep staging method for mice.Finite dimensional structure of the GPI discharge in patients with Parkinson's disease.Analysis of absence seizure generation using EEG spatial-temporal regularity measures.Double-layered models can explain macro and micro structure of human sleep.Combination of heterogeneous EEG feature extraction methods and stacked sequential learning for sleep stage classification.Artificial neural network based approach to EEG signal simulation.Assessment of feature selection and classification approaches to enhance information from overnight oximetry in the context of apnea diagnosis.Application of empirical mode decomposition (emd) for automated detection of epilepsy using EEG signals.Cerebrovascular pattern improved by ozone autohemotherapy: an entropy-based study on multiple sclerosis patients.Early prediction of medication refractoriness in children with idiopathic epilepsy based on scalp EEG analysis.Graph theoretical analysis of organization of functional brain networks in ADHD.Automated diagnosis of normal and alcoholic EEG signals.Span: spike pattern association neuron for learning spatio-temporal spike patterns.Testing of information condensation in a model reverberating spiking neural network.Application of higher order cumulant features for cardiac health diagnosis using ECG signals.Automated diagnosis of epilepsy using CWT, HOS and texture parameters.A new parametric feature descriptor for the classification of epileptic and control EEG records in pediatric population.Automatic detection of epileptic EEG signals using higher order cumulant features.Classification of epilepsy using high-order spectra features and principle component analysis.An end-to-end framework for real-time automatic sleep stage classification.Comparison of walking parameters obtained from the young, elderly and adults with support.EEG-Based Automatic Sleep Staging Using Ontology and Weighting Feature Analysis
P2860
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P2860
Analysis and automatic identification of sleep stages using higher order spectra.
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年学术文章
@wuu
2010年学术文章
@zh
2010年学术文章
@zh-cn
2010年学术文章
@zh-hans
2010年学术文章
@zh-my
2010年学术文章
@zh-sg
2010年學術文章
@yue
2010年學術文章
@zh-hant
name
Analysis and automatic identification of sleep stages using higher order spectra.
@en
Analysis and automatic identification of sleep stages using higher order spectra.
@nl
type
label
Analysis and automatic identification of sleep stages using higher order spectra.
@en
Analysis and automatic identification of sleep stages using higher order spectra.
@nl
prefLabel
Analysis and automatic identification of sleep stages using higher order spectra.
@en
Analysis and automatic identification of sleep stages using higher order spectra.
@nl
P2093
P2860
P1476
Analysis and automatic identification of sleep stages using higher order spectra.
@en
P2093
Eric Chern-Pin Chua
Kuang Chua Chua
Lim Choo Min
Toshiyo Tamura
U Rajendra Acharya
P2860
P304
P356
10.1142/S0129065710002589
P577
2010-12-01T00:00:00Z