Literature DB >> 12531163

Computer based sleep recording and analysis.

Thomas Penzel1, Regina Conradt.   

Abstract

Sleep analysis is based on polysomnography. Modern polysomnographic systems are computer based. Visual and automatic analysis of sleep and respiration is supported by most computer based systems. Four functions can be distinguished in computer based polysomnography: recording, documentation during the recording, automatic and visual analysis and report generation. This review compiles the minimal requirements for digital sleep recording, documentation, analysis and reporting. The basic principles of automatic sleep analysis are reported. The requirements and the basic principles for the analysis of non-electroencephalography (EEG) signals, such as respiration, snoring, oxygen saturation, electrocardiography (ECG) and options are reported. New developments in sleep EEG processing are discussed to enlighten how computer based sleep analysis can add quantative parameters to the rules for visual sleep staging established by Rechtschaffen and Kales 30 years ago. This helps to extend our understanding of sleep.

Entities:  

Year:  2000        PMID: 12531163     DOI: 10.1053/smrv.1999.0087

Source DB:  PubMed          Journal:  Sleep Med Rev        ISSN: 1087-0792            Impact factor:   11.609


  22 in total

1.  Automatic analysis of electro-encephalogram sleep spindle frequency throughout the night.

Authors:  E Huupponen; S L Himanen; J Hasan; A Värri
Journal:  Med Biol Eng Comput       Date:  2003-11       Impact factor: 2.602

2.  Estimation of sleep stages by an artificial neural network employing EEG, EMG and EOG.

Authors:  M Emin Tagluk; Necmettin Sezgin; Mehmet Akin
Journal:  J Med Syst       Date:  2009-04-08       Impact factor: 4.460

3.  Identification of deep sleep and awake with computational EEG measures.

Authors:  Eero Huupponen; Antti Kulkas; Antti Saastamoinen; Mirja Tenhunen; Sari-Leena Himanen
Journal:  J Med Syst       Date:  2010-01-06       Impact factor: 4.460

4.  Anteroposterior difference in EEG sleep depth measure is reduced in apnea patients.

Authors:  Eero Huupponen; Antti Saastamoinen; Atte Joutsen; Jussi Virkkala; Jarmo Alametsä; Joel Hasan; Alpo Värri; Sari-Leena Himanen
Journal:  J Med Syst       Date:  2005-10       Impact factor: 4.460

5.  Sleep depth oscillations: an aspect to consider in automatic sleep analysis.

Authors:  Eero Huupponen; Sari-Leena Himanen; Joel Hasan; Alpo Värri
Journal:  J Med Syst       Date:  2003-08       Impact factor: 4.460

6.  An open-source hardware and software system for acquisition and real-time processing of electrophysiology during high field MRI.

Authors:  Patrick L Purdon; Hernan Millan; Peter L Fuller; Giorgio Bonmassar
Journal:  J Neurosci Methods       Date:  2008-08-05       Impact factor: 2.390

7.  Characterizing sleep structure using the hypnogram.

Authors:  Bruce J Swihart; Brian Caffo; Karen Bandeen-Roche; Naresh M Punjabi
Journal:  J Clin Sleep Med       Date:  2008-08-15       Impact factor: 4.062

Review 8.  Computer-Assisted Diagnosis of the Sleep Apnea-Hypopnea Syndrome: A Review.

Authors:  Diego Alvarez-Estevez; Vicente Moret-Bonillo
Journal:  Sleep Disord       Date:  2015-07-21

9.  Evaluation of automated and semi-automated scoring of polysomnographic recordings from a clinical trial using zolpidem in the treatment of insomnia.

Authors:  Vladimir Svetnik; Junshui Ma; Keith A Soper; Scott Doran; John J Renger; Steve Deacon; Ken S Koblan
Journal:  Sleep       Date:  2007-11       Impact factor: 5.849

10.  Automatic analysis of single-channel sleep EEG: validation in healthy individuals.

Authors:  Christian Berthomier; Xavier Drouot; Maria Herman-Stoïca; Pierre Berthomier; Jacques Prado; Djibril Bokar-Thire; Odile Benoit; Jérémie Mattout; Marie-Pia d'Ortho
Journal:  Sleep       Date:  2007-11       Impact factor: 5.849

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