Approximate entropy of human respiratory movement during eye-closed waking and different sleep stages

Naoto Burioka, Germaine G Cornelissen-Guillaume, Franz Halberg, Daniel T. Kaplan, Hisashi Suyama, Takanori Sako, Eiji Shimizu

Research output: Contribution to journalArticlepeer-review

76 Scopus citations


Study objective: The breath-to-breath variability of respiratory parameters changes with sleep stage. This study investigates any alteration in the approximate entropy (ApEn) of respiratory movement as a gauge of complexity in respiration, by stage of consciousness, in the light of putative brain interactions. Participants: Eight healthy men, who were between the ages of 23 and 29 years, were investigated. Measurements and results: The signals of chest wall movement and EEG were recorded from 10:30 PM to 6:00 AM. After analog-to-digital conversion, the ApEn of respiratory movement (3 min) and EEG (20 s) were computed. Surrogate data were tested for nonlinearity in the original time series. The most impressive reduction in the ApEn of respiratory movement was associated with stage IV sleep, when the ApEn of the EEG was also statistically significantly decreased. A statistically significant linear relation is found between the ApEn of both variables. Surrogate data indicated that respiratory movement had nonlinear properties during all stages of consciousness that were investigated. Conclusion: Respiratory movement and EEG signals are more regular during stage IV sleep than during other stages of consciousness. The change in complexity described by the ApEn of respiration depends in part on the ApEn of the EEG, suggesting the involvement of nonlinear dynamic processes in the coordination between brain and lungs.

Original languageEnglish (US)
Pages (from-to)80-86
Number of pages7
Issue number1
StatePublished - 2003

Bibliographical note

Funding Information:
This study was supported by grant 11-KOU-179 from the Ministry of Education, Science, Sports, and Culture, Japan.


  • Approximate entropy
  • Complexity
  • EEG
  • Nonlinear
  • Respiration
  • Sleep


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