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Dynamics of snoring sounds and its connection with obstructive sleep apnea

Author

Listed:
  • Alencar, Adriano M.
  • da Silva, Diego Greatti Vaz
  • Oliveira, Carolina Beatriz
  • Vieira, André P.
  • Moriya, Henrique T.
  • Lorenzi-Filho, Geraldo

Abstract

Snoring is extremely common in the general population and when irregular may indicate the presence of obstructive sleep apnea. We analyze the overnight sequence of wave packets — the snore sound — recorded during full polysomnography in patients referred to the Sleep Laboratory due to suspected obstructive sleep apnea. We hypothesize that irregular snore, with duration in the range between 10 and 100 s, correlates with respiratory obstructive events. We find that the number of irregular snores — easily accessible, and quantified by what we call the snore time interval index (STII) — is in good agreement with the well-known apnea–hypopnea index, which expresses the severity of obstructive sleep apnea and is extracted only from polysomnography. In addition, the Hurst analysis of the snore sound itself, which calculates the fluctuations in the signal as a function of time interval, is used to build a classifier that is able to distinguish between patients with no or mild apnea and patients with moderate or severe apnea.

Suggested Citation

  • Alencar, Adriano M. & da Silva, Diego Greatti Vaz & Oliveira, Carolina Beatriz & Vieira, André P. & Moriya, Henrique T. & Lorenzi-Filho, Geraldo, 2013. "Dynamics of snoring sounds and its connection with obstructive sleep apnea," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 271-277.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:1:p:271-277
    DOI: 10.1016/j.physa.2012.08.008
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    References listed on IDEAS

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    1. Zhang, J. & Yang, X.C. & Luo, L. & Shao, J. & Zhang, C. & Ma, J. & Wang, G.F. & Liu, Y. & Peng, C.-K. & Fang, J., 2009. "Assessing severity of obstructive sleep apnea by fractal dimension sequence analysis of sleep EEG," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4407-4414.
    2. Ishizaki, Ryuji & Shinba, Toshikazu & Mugishima, Go & Haraguchi, Hikaru & Inoue, Masayoshi, 2008. "Time-series analysis of sleep–wake stage of rat EEG using time-dependent pattern entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3145-3154.
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    Keywords

    Snore; Hurst; Time interval; OSA;
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