• DocumentCode
    3685334
  • Title

    Correlational analysis of electroencephalographic and end-tidal carbon dioxide signals during breath-hold exercise

  • Author

    Maria Sole Morelli;Nicola Vanello;Alberto Giannoni;Francesca Frijia;Valentina Hartwig;Michelangelo Maestri;Enrica Bonanni;Luca Carnicelli;Vincenzo Positano;Claudio Passino;Michele Emdin;Luigi Landini

  • Author_Institution
    Scuola Superiore Sant´Anna, 56127 Pisa, Italy
  • fYear
    2015
  • Firstpage
    6102
  • Lastpage
    6105
  • Abstract
    The central mechanism of breathing control is not totally understood. Several studies evaluated the correlation between electroencephalographic (EEG) power spectra and respiratory signals by performing resting state tasks or adopting hypercapnic/hypoxic stimuli. The observation of brain activity during voluntary breath hold tasks, might be an useful approach to highlight the areas involved in mechanism of breath regulation. Nevertheless, studies of brain activity with EEG could present some limitations due to presence of severe artifacts. When artifact rejection methods, as independent component analysis, cannot reliably clean EEG data, it is necessary to exclude noisy segments. In this study, global field power in the delta band and end-tidal CO2 were derived from EEG and CO2 signals respectively in 4 healthy subjects during a breath-hold task. The cross correlation function between the two signals was estimated taking into account the presence of missing samples. The statistical significance of the correlation coefficients at different time lags was assessed using surrogate data. Some simulations are introduced to evaluate the effect of missing data on the correlational analysis and their results are discussed. Results obtained on subjects show a significant correlation between changes in EEG power in the delta band and end-tidal CO2. Moreover, the changes in end-tidal CO2 were found to precede those of global field power. These results might help to better understand the cortical mechanisms involved in the control of breathing.
  • Keywords
    "Electroencephalography","Correlation","Brain","Correlation coefficient","Time series analysis","Biomedical monitoring","Electronic mail"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7319784
  • Filename
    7319784