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Updated: May 29, 2026

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
Published on: August 2, 2017
Classification of sleep patterns by means of markov modeling and correspondence analysis
1Department of Electrical Engineering, University of Houston-University Park, Houston, TX 77004.
Abstract:
Shown is how correspondence analysis can be used to track changes in an individuals' sleep pattern. Correspondence analysis was applied to sleep stage transition matrices computed from all-night sleep of normal, obese, and apnoetic subjects. Differences between the groups, and intraindividual changes in sleep patterns could be visualized better than with a x2-based clustering approach.
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