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Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses

Environmental carbon dioxide (CO(2)) could affect various mental and physiological activities in humans, but its effect on daytime sleepiness is still controversial. In a randomized and counterbalanced crossover study with twelve healthy volunteers, we applied a combinational approach using classica...

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Autores principales: Jin, Rui Nian, Inada, Hitoshi, Négyesi, János, Ito, Daisuke, Nagatomi, Ryoichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9327715/
https://www.ncbi.nlm.nih.gov/pubmed/35762237
http://dx.doi.org/10.1111/ina.13055
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author Jin, Rui Nian
Inada, Hitoshi
Négyesi, János
Ito, Daisuke
Nagatomi, Ryoichi
author_facet Jin, Rui Nian
Inada, Hitoshi
Négyesi, János
Ito, Daisuke
Nagatomi, Ryoichi
author_sort Jin, Rui Nian
collection PubMed
description Environmental carbon dioxide (CO(2)) could affect various mental and physiological activities in humans, but its effect on daytime sleepiness is still controversial. In a randomized and counterbalanced crossover study with twelve healthy volunteers, we applied a combinational approach using classical frequentist and Bayesian statistics to analyze the CO(2) exposure effect on daytime sleepiness and electroencephalogram (EEG) signals. Subjective sleepiness was measured by the Japanese Karolinska Sleepiness Scale (KSS‐J) by recording EEG during CO(2) exposure at different concentrations: Normal (C), 4000 ppm (Moderately High: MH), and 40 000 ppm (high: H). The daytime sleepiness was significantly affected by the exposure time but not the CO(2) condition in the classical statistics. On the other hand, the Bayesian paired t‐test revealed that the CO(2) exposure at the MH condition might induce daytime sleepiness at the 40‐min point compared with the C condition. By contrast, EEG was significantly affected by a short exposure to the H condition but not exposure time. The Bayesian analysis of EEG was primarily consistent with results by the classical statistics but showed different credible levels in the Bayes’ factor. Our result suggested that the EEG may not be suitable to detect objective sleepiness induced by CO(2) exposure because the EEG signal was highly sensitive to environmental CO(2) concentration. Our study would be helpful for researchers to revisit whether EEG is applicable as a judgment indicator of objective sleepiness.
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spelling pubmed-93277152022-07-30 Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses Jin, Rui Nian Inada, Hitoshi Négyesi, János Ito, Daisuke Nagatomi, Ryoichi Indoor Air Original Articles Environmental carbon dioxide (CO(2)) could affect various mental and physiological activities in humans, but its effect on daytime sleepiness is still controversial. In a randomized and counterbalanced crossover study with twelve healthy volunteers, we applied a combinational approach using classical frequentist and Bayesian statistics to analyze the CO(2) exposure effect on daytime sleepiness and electroencephalogram (EEG) signals. Subjective sleepiness was measured by the Japanese Karolinska Sleepiness Scale (KSS‐J) by recording EEG during CO(2) exposure at different concentrations: Normal (C), 4000 ppm (Moderately High: MH), and 40 000 ppm (high: H). The daytime sleepiness was significantly affected by the exposure time but not the CO(2) condition in the classical statistics. On the other hand, the Bayesian paired t‐test revealed that the CO(2) exposure at the MH condition might induce daytime sleepiness at the 40‐min point compared with the C condition. By contrast, EEG was significantly affected by a short exposure to the H condition but not exposure time. The Bayesian analysis of EEG was primarily consistent with results by the classical statistics but showed different credible levels in the Bayes’ factor. Our result suggested that the EEG may not be suitable to detect objective sleepiness induced by CO(2) exposure because the EEG signal was highly sensitive to environmental CO(2) concentration. Our study would be helpful for researchers to revisit whether EEG is applicable as a judgment indicator of objective sleepiness. John Wiley and Sons Inc. 2022-06-13 2022-06 /pmc/articles/PMC9327715/ /pubmed/35762237 http://dx.doi.org/10.1111/ina.13055 Text en © 2022 The Authors. Indoor Air published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Articles
Jin, Rui Nian
Inada, Hitoshi
Négyesi, János
Ito, Daisuke
Nagatomi, Ryoichi
Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses
title Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses
title_full Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses
title_fullStr Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses
title_full_unstemmed Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses
title_short Carbon dioxide effects on daytime sleepiness and EEG signal: A combinational approach using classical frequentist and Bayesian analyses
title_sort carbon dioxide effects on daytime sleepiness and eeg signal: a combinational approach using classical frequentist and bayesian analyses
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9327715/
https://www.ncbi.nlm.nih.gov/pubmed/35762237
http://dx.doi.org/10.1111/ina.13055
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