A sleep model and an observer using the Lotka–Volsterra equation for real-time estimation of sleep

Yosuke Kurihara, Kajiro Watanabe, Hiroshi Tanaka

Research output: Contribution to journalArticlepeer-review

Abstract

This paper describes a novel method that estimates sleep behaviors in a real-time manner. A Luenberger-type observer was employed, which requires a dynamic model of the sleep as a priori information about the sleep stages. A reasonable sleep model is essential in this approach. The classic Lotka–Voltera equation with interpretations associated with the sleep was built and an observer was developed. The observer using heartbeat rhythm and body movement as input signals estimated and compensated the sleep depths, which shows better results than the original inputs in the standpoint of the percentage of δ-waves in total brainwaves, used as a reference. The observer compensated for phase-shift errors and non-cyclic errors of the sleep cycle. The correlation between the reference and the compensated sleep cycle behavior was 0.79, whereas that between the reference and the measurement itself was 0.65. The application of the observer improved the accuracy of the sleep cycle measurement.

Original languageEnglish
Pages (from-to)132-139
Number of pages8
JournalArtificial Life and Robotics
Volume21
Issue number1
DOIs
Publication statusPublished - 2016 Mar 1

Keywords

  • Heartbeat
  • Lotka–Volterra equation
  • Observer
  • Sleep cycle
  • Ultradian rhythm

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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