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Acoustic Analysis

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The Role of Epiglottis in Obstructive Sleep Apnea

Abstract

It has been suggested that, for patients with obstructive sleep apnea (OSA), identification of the obstruction site in the upper airway is essential in the treatment decision-making process. Due to the fact that all existing techniques for the identification of the obstruction site have drawbacks, there is a continuous search for more feasible methods. Because of the filtering effect of the upper airway on snoring sound, snoring sound parameters are considered as potential predictors of the obstruction site in the upper airway. According to previous studies, using snoring sound parameters to predict the presence of epiglottic obstruction in OSA patients with single-level obstruction can achieve a relatively high accuracy (53.1–96%) as compared with velum, oropharynx, and tongue base obstructions, even though the exact role of the epiglottis in generating snoring sound is still unclear. However, further studies are needed to explore the possibility to predict the presence of epiglottic obstruction in OSA patients with multilevel obstruction based on the acoustic analysis of snoring sound, especially of snoring sound recorded during natural sleep. At this stage, snoring sound analysis does not seem to be a viable diagnostic modality for treatment selection.

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References

  1. Jennum P, Sjøl A. Epidemiology of snoring and obstructive sleep apnoea in a Danish population, age 30-60. J Sleep Res. 1992;1:240–4. https://doi.org/10.1111/j.1365-2869.1992.tb00045.x.

    Article  CAS  PubMed  Google Scholar 

  2. Khazaie H, Negahban S, Ghadami MR, Sadeghi Bahmani D, Holsboer-Trachsler E, Brand S. Among middle-aged adults, snoring predicted hypertension independently of sleep apnoea. J Int Med Res. 2018;46:1187–96. https://doi.org/10.1177/0300060517738426.

    Article  PubMed Central  Google Scholar 

  3. Maimon N, Hanly PJ. Does snoring intensity correlate with the severity of obstructive sleep apnea? J Clin Sleep Med. 2010;6:475–8.

    Article  PubMed  PubMed Central  Google Scholar 

  4. American Academy of Sleep Medicine. International classification of sleep disorders. 3rd ed. Darien: American Academy of Sleep Medicine; 2014.

    Google Scholar 

  5. Virkkula P, Bachour A, Hytönen M, Malmberg H, Salmi T, Maasilta P. Patient- and bed partner-reported symptoms, smoking, and nasal resistance in sleep-disordered breathing. Chest. 2005;128:2176–82. https://doi.org/10.1378/chest.128.4.2176.

    Article  PubMed  Google Scholar 

  6. Acar M, Yazıcı D, Bayar Muluk N, Hancı D, Seren E, Cingi C. Is there a relationship between snoring sound intensity and frequency and OSAS severity? Ann Otol Rhinol Laryngol. 2016;125:31–6. https://doi.org/10.1177/0003489415595640.

    Article  Google Scholar 

  7. Azarbarzin A, Moussavi Z. Snoring sounds variability as a signature of obstructive sleep apnea. Med Eng Phys. 2013;35:479–85. https://doi.org/10.1016/j.medengphy.2012.06.013.

    Article  Google Scholar 

  8. Quinn S, Huang L, Ellis P, Williams J. The differentiation of snoring mechanisms using sound analysis. Clin Otolaryngol Allied Sci. 1996;21:119–23. https://doi.org/10.1111/j.1365-2273.1996.tb01313.x.

    Article  CAS  PubMed  Google Scholar 

  9. Croft CB, Pringle M. Sleep nasendoscopy: a technique of assessment in snoring and obstructive sleep apnoea. Clin Otolaryngol Allied Sci. 1991;16:504–9. https://doi.org/10.1111/j.1365-2273.1991.tb01050.x.

    Article  CAS  PubMed  Google Scholar 

  10. Kezirian E, Hohenhorst W, de Vries N. Drug-induced sleep endoscopy: the VOTE classification. Eur Arch Otorhinolaryngol. 2011;268:1233–6. https://doi.org/10.1007/s00405-011-1633-8.

    Article  PubMed  Google Scholar 

  11. Strollo P, Soose R, Maurer J, de Vries N, Cornelius J, Froymovich O, Hanson R, Padhya T, Steward D, Gillespie B, Woodson T, Van de Heyning P, Goetting M, Vanderveken O, Feldman N, Knaack L, Strohl K, STAR Trial Group. Upper-airway stimulation for obstructive sleep apnea. N Engl J Med. 2014;370:139–49. https://doi.org/10.1056/NEJMoa1308659.

    Article  CAS  Google Scholar 

  12. Op de Beeck S, Dieltjens M, Verbruggen A, Vroegop A, Wouters K, Hamans E, Willemen M, Verbraecken J, De Backer W, Van de Heyning P, Braem M, Vanderveken O. Phenotypic labelling using drug-induced sleep endoscopy improves patient selection for mandibular advancement device outcome: a prospective study. J Clin Sleep Med. 2019;15:1089–99. https://doi.org/10.5664/jcsm.7796.

    Article  Google Scholar 

  13. Chong KB, De Vito A, Vicini C. Drug-induced sleep endoscopy in treatment options selection. Sleep Med Clin. 2019;14:33–40. https://doi.org/10.1016/j.jsmc.2018.11.001.

    Article  Google Scholar 

  14. Viana A, Zhao C, Rosa T, Couto A, Neves DD, Araújo-Melo MH, Capasso R. The effect of sedating agents on drug-induced sleep endoscopy findings. Laryngoscope. 2019;129:506–13. https://doi.org/10.1002/lary.27298.

    Article  CAS  Google Scholar 

  15. Razek A. Diagnostic role of magnetic resonance imaging in obstructive sleep apnea syndrome. J Comput Assist Tomogr. 2015;39:565–71. https://doi.org/10.1097/RCT.0000000000000243.

    Article  PubMed  Google Scholar 

  16. Genta P, Sands S, Butler J, Loring S, Katz E, Demko B, Kezirian E, White D, Wellman A. Airflow shape is associated with the pharyngeal structure causing OSA. Chest. 2017;152:537–46. https://doi.org/10.1016/j.chest.2017.06.017.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Hudgel DW. Variable site of airway narrowing among obstructive sleep apnea patients. J Appl Physiol. 1986;61:1403–9. https://doi.org/10.1152/jappl.1986.61.4.1403.

    Article  CAS  PubMed  Google Scholar 

  18. Han D, Ye J, Wang J, Yang Q, Lin Y, Wang J. Determining the site of airway obstruction in obstructive sleep apnea with airway pressure measurements during sleep. Laryngoscope. 2002;112:2081–5. https://doi.org/10.1097/00005537-200211000-00032.

    Article  Google Scholar 

  19. Titze IR. Principles of vocal production. Englewood Cliffs: Prentice-Hall; 1994.

    Google Scholar 

  20. Pevernagie D, Aarts RM, De Meyer M. The acoustics of snoring. Sleep Med Rev. 2010;14:131–44. https://doi.org/10.1016/j.smrv.2009.06.002.

    Article  PubMed  Google Scholar 

  21. Agrawal S, Stone P, McGuinness K, Morris J, Camilleri A. Sound frequency analysis and the site of snoring in natural and induced sleep. Clin Otolaryngol Allied Sci. 2002;27:162–6. https://doi.org/10.1046/j.1365-2273.2002.00554.x.

    Article  CAS  PubMed  Google Scholar 

  22. Gürpınar B, Saltürk Z, Kumral T, Civelek S, Izel O, Uyar Y. Analysis of snoring to determine the site of obstruction in obstructive sleep apnea syndrome. Sleep Breath. 2020;25:1427. https://doi.org/10.1007/s11325-020-02252-5.

    Article  PubMed  Google Scholar 

  23. Koo S, Kwon S, Kim Y, Moon J, Kim Y, Jung S. Acoustic analysis of snoring sounds recorded with a smartphone according to obstruction site in OSAS patients. Eur Arch Otorhinolaryngol. 2017;274:1735–40. https://doi.org/10.1007/s00405-016-4335-4.

    Article  PubMed  Google Scholar 

  24. Eberhard Z, Hugo F. Psychoacoustics-facts and models. 2nd ed. Berlin: Springer; 1999.

    Google Scholar 

  25. Huang Z, Aarab G, Ravesloot MJL, Zhou N, Bosschieter PFN, van Selms MKA, den Haan C, de Vries N, Lobbezoo F, Hilgevoord AAJ. Prediction of the obstruction sites in the upper airway in sleep-disordered breathing based on snoring sound parameters: a systematic review. Sleep Med. 2021;88:116–33. https://doi.org/10.1016/j.sleep.2021.10.015.

    Article  Google Scholar 

  26. Won T, Kim S, Lee W, Han D, Kim D, Kim J, Rhee C, Lee C. Acoustic characteristics of snoring according to obstruction site determined by sleep videofluoroscopy. Acta Otolaryngol. 2012;132(Suppl 1):S13–20. https://doi.org/10.3109/00016489.2012.660733.

    Article  Google Scholar 

  27. Qian K, Janott C, Pandit V, Zhang Z, Heiser C, Hohenhorst W, Herzog M, Hemmert W, Schuller B. Classification of the excitation location of snore sounds in the upper airway by acoustic multifeature analysis. IEEE Trans Biomed Eng. 2017;64:1731–41. https://doi.org/10.1109/TBME.2016.2619675.

    Article  PubMed  Google Scholar 

  28. Qian K, Janott C, Deng J, Heiser C, Hohenhorst W, Herzog M, Cummins N, Schuller B. Snore sound recognition: on wavelets and classifiers from deep nets to kernels. Conf Proc IEEE Eng Med Biol Soc. 2017;2017:3737–40. https://doi.org/10.1109/EMBC.2017.8037669.

    Article  Google Scholar 

  29. Schmitt M, Janott C, Pandit V, Qian K, Heiser C, Hemmert W, Schuller B. A bag-of-audio-words approach for snore sounds’ excitation localisation. Speech Communication; 12. Paderborn: ITG Symposium; 2016.

    Google Scholar 

  30. Qian K, Schmitt M, Janott C, Zhang Z, Heiser C, Hohenhorst W, Herzog M, Hemmert W, Schuller B. A bag of wavelet features for snore sound classification. Ann Biomed Eng. 2019;47:1000–11. https://doi.org/10.1007/s10439-019-02217-0.

    Article  Google Scholar 

  31. Amiriparian S, Gerczuk M, Ottl S, Cummins N, Freitag M, Pugachevskiy S, Baird A, Schuller B. Snore sound classification using image-based deep Spectrum features. In: Proceedings INTERSPEECH 2017, 18th Annual Conference of the International Speech Communication Association, Stockholm, Sweden, ISCA, August; 2017. p. 3512–6. https://doi.org/10.21437/Interspeech.2017-434.

  32. Vesperini F, Galli A, Gabrielli L, Principi E, Squartini S. Snore sounds excitation localization by using scattering transform and deep neural Networks. In: 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil; 2018. https://doi.org/10.1109/IJCNN.2018.8489576.

  33. Sun J, Hu X, Chen C, Peng S, Ma Y. Amplitude spectrum trend-based feature for excitation location classification from snore sounds. Physiol Meas. 2020;41:085006. https://doi.org/10.1088/1361-6579/abaa34.

    Article  PubMed Central  Google Scholar 

  34. Sun J, Hu X, Peng S, Peng C, Ma Y. Automatic classification of excitation location of snoring sounds. J Clin Sleep Med. 2021;17:1031–8. https://doi.org/10.5664/jcsm.9094.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Lee E, Cho J. Meta-analysis of obstruction site observed with drug-induced sleep endoscopy in patients with obstructive sleep apnea. Laryngoscope. 2019;129:1235–43. https://doi.org/10.1002/lary.27320.

    Article  CAS  PubMed  Google Scholar 

  36. Rabelo F, Kupper D, Sander H, Fernandes R, Valera F. Polysomnographic evaluation of propofol-induced sleep in patients with respiratory sleep disorders and controls. Laryngoscope. 2013;123:2300–5. https://doi.org/10.1002/lary.23664.

    Article  CAS  PubMed  Google Scholar 

  37. Murphy M, Bruno M, Riedner B, Boveroux P, Noirhomme Q, Landsness E, Brichant J, Phillips C, Massimini M, Laureys S, Tononi G, Boly M. Propofol anesthesia and sleep: a high-density EEG study. Sleep. 2011;34:283–91A. https://doi.org/10.1093/sleep/34.3.283.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Jones T, Ho M, Earis J, Swift A, Charters P. Acoustic parameters of snoring sound to compare natural snores with snores during ‘steady-state’ propofol sedation. Clin Otolaryngol. 2006;31:46–52. https://doi.org/10.1111/j.1749-4486.2006.01136.x.

    Article  CAS  PubMed  Google Scholar 

  39. Salamanca F, Leone F, Bianchi A, Bellotto R, Costantini F, Salvatori P. Surgical treatment of epiglottis collapse in obstructive sleep apnoea syndrome: epiglottis stiffening operation. Acta Otorhinolaryngol Ital. 2019;39:404–8. https://doi.org/10.14639/0392-100X-N0287.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Elsobki A, Cahali M, Kahwagi M. LwPTL: a novel classification for upper airway collapse in sleep endoscopies. Braz J Otorhinolaryngol. 2019;85:379–87. https://doi.org/10.1016/j.bjorl.2019.01.010.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Quinn SJ, Daly N, Ellis PD. Observation of the mechanism of snoring using sleep nasendoscopy. Clin Otolaryngol Allied Sci. 1995;20:360–4. https://doi.org/10.1111/j.1365-2273.1995.tb00061.x.

    Article  CAS  PubMed  Google Scholar 

  42. Xu H, Jia R, Yu H, Gao Z, Huang W, Peng H, Yang Y, Zhang L. Investigation of the source of snoring sound by drug-induced sleep nasendoscopy. ORL J Otorhinolaryngol Relat Spec. 2015;77:359–65. https://doi.org/10.1159/000439597.

    Article  CAS  Google Scholar 

  43. Sung CM, Kim HC, Yang HC. The clinical characteristics of patients with an isolate epiglottic collapse. Auris Nasus Larynx. 2020;47:450–7. https://doi.org/10.1016/j.anl.2019.10.009.

    Article  Google Scholar 

  44. Saunders NA, Vandeleur T, Deves J, Salmon A, Gyulay S, Crocker B, Hensley M. Uvulopalatopharyngoplasty as a treatment for snoring. Med J Aust. 1989;150:177–82. https://doi.org/10.5694/j.1326-5377.1989.tb136420.x.

    Article  CAS  PubMed  Google Scholar 

  45. Azarbarzin A, Marques M, Sands SA, Op de Beeck S, Genta PR, Taranto-Montemurro L, de Melo CM, Messineo L, Vanderveken OM, White DP, Wellman A. Predicting epiglottic collapse in patients with obstructive sleep apnoea. Eur Respir J. 2017;50:1700345. https://doi.org/10.1183/13993003.00345-2017.

    Article  PubMed  PubMed Central  Google Scholar 

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Huang, Z., Lobbezoo, F., Aarab, G., de Vries, N., Hilgevoord, A.A.J. (2023). Acoustic Analysis. In: Delakorda, M., de Vries, N. (eds) The Role of Epiglottis in Obstructive Sleep Apnea. Springer, Cham. https://doi.org/10.1007/978-3-031-34992-8_10

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  • DOI: https://doi.org/10.1007/978-3-031-34992-8_10

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