Literature DB >> 8477587

Neural network model: application to automatic analysis of human sleep.

N Schaltenbrand1, R Lengelle, J P Macher.   

Abstract

We describe an approach to automatic all-night sleep analysis based on neural network models and simulated on a digital computer. First, automatic sleep stage scoring was performed using a multilayer feedforward network. Second, supervision of the automatic decision was achieved using ambiguity rejection and artifact rejection. Then, numerical analysis of sleep was carried out using all-night spectral analysis for the background activity of the EEG and sleep pattern detectors for the transient activity. Computerized analysis of sleep recordings may be considered as an essential tool to describe the sleep process and to reflect the dynamical organization of human sleep.

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Year:  1993        PMID: 8477587     DOI: 10.1006/cbmr.1993.1010

Source DB:  PubMed          Journal:  Comput Biomed Res        ISSN: 0010-4809


  5 in total

1.  Artificial neural network and wavelet based automated detection of sleep spindles, REM sleep and wake states.

Authors:  Rakesh Kumar Sinha
Journal:  J Med Syst       Date:  2008-08       Impact factor: 4.460

2.  On the robust parametric detection of EEG artifacts in polysomnographic recordings.

Authors:  H Klekowicz; U Malinowska; A J Piotrowska; D Wołyńczyk-Gmaj; Sz Niemcewicz; P J Durka
Journal:  Neuroinformatics       Date:  2009-03-24

3.  Automated Scoring of Sleep and Associated Events.

Authors:  Peter Anderer; Marco Ross; Andreas Cerny; Edmund Shaw
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 3.650

4.  Automatic Human Sleep Stage Scoring Using Deep Neural Networks.

Authors:  Alexander Malafeev; Dmitry Laptev; Stefan Bauer; Ximena Omlin; Aleksandra Wierzbicka; Adam Wichniak; Wojciech Jernajczyk; Robert Riener; Joachim Buhmann; Peter Achermann
Journal:  Front Neurosci       Date:  2018-11-06       Impact factor: 4.677

5.  Automatic and Accurate Sleep Stage Classification via a Convolutional Deep Neural Network and Nanomembrane Electrodes.

Authors:  Kangkyu Kwon; Shinjae Kwon; Woon-Hong Yeo
Journal:  Biosensors (Basel)       Date:  2022-03-02
  5 in total

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