Objective evaluation of nasal breathing based on rhinomanometric data

Authors

  • Андрей Леонидович Ерохин Kharkiv National University of Radio Electronics Lenina 16, Kharkov, Ukraine, 61166, Ukraine
  • Игорь Петрович Захаров Kharkiv National University of Radio Electronics Lenina 16, Kharkov, Ukraine, 61166, Ukraine
  • Алина Сергеевна Нечипоренко Kharkiv National University of Radio Electronics Lenina 16, Kharkov, Ukraine, 61166, Ukraine
  • Олег Григорьевич Гарюк Kharkiv medical academy of postgraduate education Korchagintsev 58, Kharkiv, Ukraine, 61176, Ukraine

DOI:

https://doi.org/10.15587/1729-4061.2014.26281

Keywords:

rhinomanometry, spectral analysis, modified covariance method, differential pressure, air flow rate

Abstract

Currently, there are many objective diagnostic methods for nasal breathing difficulties. The main conventional method in otolaryngological practice is active rhinomanometry. The value of nasal resistance is considered as a diagnostic parameter of active anterior rhinomanometry. However, the results of the rhinomanometric measurements depend on race, age, gender, body mass index, and growth, etc. Thus, there is no evaluated criterion of physiological norm of nasal breathing according to the data from rhinomanometric studies. This fact significantly complicates the process of diagnosis and reduces diagnostic efficiency of rhinomanometry methods. For solving this problem, it is proposed to use additional spectral estimation data of the rhinomanometric studies using the modified covariance method. For this purpose, the spectral estimation software module is added to the software and hardware for rhinomanometric studies. The use of an advanced hardware and software system for rhinomanometric studies in clinical practice allows improving the diagnostic value of the active anterior rhinomanometry method.

Author Biographies

Андрей Леонидович Ерохин, Kharkiv National University of Radio Electronics Lenina 16, Kharkov, Ukraine, 61166

Professor

Department of software engineering

Игорь Петрович Захаров, Kharkiv National University of Radio Electronics Lenina 16, Kharkov, Ukraine, 61166

Professor

Department of metrology and measurement engineering

Алина Сергеевна Нечипоренко, Kharkiv National University of Radio Electronics Lenina 16, Kharkov, Ukraine, 61166

Associate professor

Biomedical Engineering Department

Олег Григорьевич Гарюк, Kharkiv medical academy of postgraduate education Korchagintsev 58, Kharkiv, Ukraine, 61176

Associate professor

Department of otolaryngology and pediatric otolaryngology

References

  1. Segboer, C. L, Holland, C. T, Reinartz, S. M., Terreehorst, I., Gevorgyan, A., Hellings, P. W., Van Drunen, C. M., Fokkens, W. J. (2014). Quality of life and use of medication in chronic allergic and non-allergic rhinitis patients Rhinology, 52 (25), 167.
  2. Thulesius, H. L. (2012). Rhinomanometry in clinical use. A tool in the septoplasty decision making process Doctoral dissertation, clinical sciences, 67.
  3. Cole, P. (2000) Acoustic rhinometry and rhinomanometry Rhinology, 16, 29–34.
  4. Clement, P. A., Gordts, F. (2005). Standardisation Committee on Objective Assessment of the Nasal Airway Consensus report on acoustic rhinometry and rhinomanometry Rhinology, 43, 169–179.
  5. Clement, P. A. (1984). Committee report on standardization of rhinomanometry Rhinology, 22 (3), 151–155.
  6. Vogt, K., Jalowayski, A. A. (2010). 4-Phase-Rhinomanometry Basics and Practice Rhinology Supplement, 21, 1–50.
  7. Canbay, E. I., Bhatia, S. N. (1997). A Comparison of Nasal Resistance in White Caucasians and Blacks. American Journal of Rhinology, 11 (1), 73–75. doi:10.2500/105065897781446801
  8. Samolinski, B. K., Grzanka, A., Gotlib, T. (2007). Changes in Nasal Cavity Dimensions in Children and Adults by Gender and Age. The Laryngoscope, 117 (8), 1429–1433. doi:10.1097/mlg.0b013e318064e837
  9. Crouse, U., Laine-Alava, M. T. (1999). Effects of Age, Body Mass Index, and Gender on Nasal Airflow Rate and Pressures. Laryngoscope, 109 (9), 1503–1508. doi:10.1097/00005537-199909000-00027
  10. Seren, E. (2005). Frequency spectra of normal expiratory nasal sound Am J Rhinology, 19, 257–261.
  11. Marple, S. L. (1990). Digital spectral analysis with applications M.: Мir, 1990, 584.
  12. Nechyporenko, A. S. (2013). Characteristics of spectral analysis usage for an objective assessment of nasal breathing Bionics of Intelligense, 2 (81), 105–109.
  13. Broms, P., Jonson, B., Lamm, C. J. (1982). Rhinomanometry. II. A system for numerical description of nasal airway resistance. Acta Otolaryngology, 94 (1-2), 157–168.
  14. Mlynski, G., Beule, A. (2008). Diagnostik der respiratorischen Funktion der Nase. HNO, 56 (1), 81–99. doi:10.1007/s00106-007-1655-0
  15. Gritsunov, A. V. (2003). The choice of methods spectral estimation functions for modeling of microwave devices Radiotechnics, 9, 25–30.

Published

2014-07-18

How to Cite

Ерохин, А. Л., Захаров, И. П., Нечипоренко, А. С., & Гарюк, О. Г. (2014). Objective evaluation of nasal breathing based on rhinomanometric data. Eastern-European Journal of Enterprise Technologies, 4(9(70), 51. https://doi.org/10.15587/1729-4061.2014.26281

Issue

Section

Information and controlling system