Literature DB >> 7395193

A signal analysis approach to rat sleep scoring instrumentation.

W B Mendelson, W J Vaughn, M J Walsh, R J Wyatt.   

Abstract

Automated rat sleep analysis focuses on the statistically regular waveforms of the EEG, such as theta and delta rhythms. Such stochastic processes can be quantified in several manners. Time domain statistics such as auto- and cross-correlations produce outputs that are difficult to use and are best performed in software. Frequency domain statistics like spectral density accurately quantify the sleep state by power-frequency distributions but also require sophisticated computer processing. Continuous frequency analysis, using pass-band filtering, accurately measures signal power in an on-line fashion and employs relatively inexpensive hardware to estimate power by integrating the square of the signal. This method differs substantively from other previously reported systems which rely on signal amplitude analysis. Comparison of this system with a human scorer indicates high degrees of validity and reproducibility.

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Year:  1980        PMID: 7395193

Source DB:  PubMed          Journal:  Waking Sleeping        ISSN: 0340-0905


  3 in total

1.  Unsupervised online classifier in sleep scoring for sleep deprivation studies.

Authors:  Paul-Antoine Libourel; Alexandra Corneyllie; Pierre-Hervé Luppi; Guy Chouvet; Damien Gervasoni
Journal:  Sleep       Date:  2015-05-01       Impact factor: 5.849

2.  Sleep EEG spectral analysis in a diurnal rodent: Eutamias sibiricus.

Authors:  D J Dijk; S Daan
Journal:  J Comp Physiol A       Date:  1989       Impact factor: 1.836

3.  FASTER: an unsupervised fully automated sleep staging method for mice.

Authors:  Genshiro A Sunagawa; Hiroyoshi Séi; Shigeki Shimba; Yoshihiro Urade; Hiroki R Ueda
Journal:  Genes Cells       Date:  2013-04-28       Impact factor: 1.891

  3 in total

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