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Pharyngeal wall vibration detection using an artificial neural network

  • K. Behbehani
  • F. Lopez
  • F. -C. Yen
  • E. A. Lucas
  • J. R. Burk
  • J. P. Axe
  • F. Kamangar
Article

Abstract

An artificial-neural-network-based detector of pharyngeal wall vibration (PWV) is presented. PWV signals the imminent occurrence of obstructive sleep apnoea (OSA) in adults who suffer from OSA syndrome. Automated detection of PWV is very important in enhancing continuous positive airway pressure (CPAP) therapy by allowing automatic adjustment of the applied airway pressure by a procedure called automatic positive airway pressure (APAP) therapy. A network with 15 inputs, one output, and two hidden layers, each with two Adaline nodes, is used as part of a PWV detection scheme. The network is initially trained using nasal mask pressure data from five positively diagnosed OSA patients. The performance of the ANN-based detector is evaluated using data from five different OSA patients. The results show that on the average it correctly detects the presence of PWV events at a rate of ≅92% and correctly distinguishes normal breaths ≅98% of the time. Further, the ANN-based detector accuracy is not affected by the pressure level required for therapy.

Keywords

Apnoea detection Neural network Obstructive sleep apnoea 

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References

  1. Acebo, C., Watson, R. K., Bakos, L., andThoman, E. B. (1991): ‘Sleep and apnoea in the elderly: reliability and validity of 24-hour recordings in the home’,Sleep,14, (1), pp. 56–64Google Scholar
  2. Axe, J. R., Behbehani, K., Burk, J. R., Lucas, E. A., andYen, F. C. (1993): ‘Methods and apparatus for controlling sleep disorder breathing’, US patent number 5,203,343Google Scholar
  3. Behbehani, K., andKang, T. (1990): ‘A microprocessor-based sleep apnoea device’. Proceedings of 11th Annual International Conference of IEEE Engineering in Medicine and Biology, Seattle, Washington State, pp. 332–333Google Scholar
  4. Behbehani, K., Yen, F. C., Axe, J., Burk, J., andLucas, E. (1993): ‘Adaptive positive airway pressure (APAP) therapy for obstructive sleep apnoea’. Proceedings of the 15th IEEE Conference in Medicine and Biology, pp. 970–971Google Scholar
  5. Behbehani, K., Yen, F.-C., Burk, J. R., Lucas, E. A., andAxe, J. R. (1995): ‘Automatic control of airway pressure for treatment of obstructive sleep apnoea’,IEEE Trans. Biomed. Eng.,42, (10), pp. 1007–1016CrossRefGoogle Scholar
  6. Berthon-Jones, M. (1993): ‘Feasibility of a self-setting CPAP machine’,Sleep,16, pp. S120-S123Google Scholar
  7. Berry, R. B., andBlock, A. J. (1984): ‘Positive nasal airway pressure eliminates snoring as well as obstructive sleep apnoea’,Chest,85, (1), pp. 15–20Google Scholar
  8. Burk, J. R., Lucas, E. A., Axe, J. R., Behbehani, K., andYen, F. (1992): ‘Auto-CPAP in the treatment of obstructive sleep apnoea; a new approach’. 1992 Annual Meeting Abstracts, Association of Professional Sleep Societies, 6th Annual Meeting, p. 61Google Scholar
  9. Daniels, B., andHarris, C. (1989): ‘Technical tidings: a simple device for detection of snoring’,APSS Newsletter,4 (1), p. 37Google Scholar
  10. Fairbanks, D. N. F., Fujita, S., Ikematsu, T., andSimmons, F. B. (1987): ‘Snoring and obstructive sleep apnoea’, (Raven Press, New York)Google Scholar
  11. Hoffstein, V., Chaban, R., andRubinstein, I. (1988): ‘Snoring and upper airway properties’,Chest,94, (1), pp. 87–89Google Scholar
  12. Hoffstein, V., Wright, N., Zamel, N., andBradley, T. D. (1991): ‘Pharyngeal function and snoring characteristics in apenic and nonapenic snorers’,Am. Rev. Respir. Dis.,143, pp. 1294–1299Google Scholar
  13. Kerby, G. R., Mayer, L. S., andPingleton, S. K. (1987): ‘Nocturnal positive pressure ventilation via nasal mask’,Am. Rev. Resp. Dis.,135, pp. 738–740Google Scholar
  14. Listro, G., Stanescu, D., andVeriter, C. (1991): ‘Pattern of simulated snoring is different through mouth and nose’,J. Appl. Phy.,70, (6), pp. 2736–2741Google Scholar
  15. Lugaresi, E., Cirignotta, F., Coccagna, G., andPiana, C. (1980): ‘Some epidemiological data on snoring and cardiocirculatory disturbances’,Sleep,3, pp. 221–224Google Scholar
  16. Martin, R. J. (1990): ‘Cardiorespiratory disorders during sleep’, (Futura Publishing Company, Mount Kisto, NY)Google Scholar
  17. Metes, A., Ohki, M., Cole, P., Haight, J. S. J., andHoffstien, V. (1991): ‘Snoring, apnoea and nasal resistance in men and women’,J. Otolaryngology,20, (1), pp. 57–61Google Scholar
  18. Pasterkamp, H., Kraman, S. S., DeFrain, P. D., andWodicka, G. R. (1993): ‘Measurement of respiratory acoustical signals: comparison of sensors’,Chest,104, pp. 1518–1525Google Scholar
  19. Perez-Guerra, F. (1987): ‘The treatment of obstructive sleep apnoea’,Texas Med.,83, pp. 30–33Google Scholar
  20. Rechtschaffen A., andKales A. (1968): ‘A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects’ (US Government Printing Office (National Institutes of Health Publication No. 204, Bethesda, MD)Google Scholar
  21. Stoohs, R., andGuilleminault, C. (1992): ‘MESAM 4: an ambulatory device for the detection of patients at risk for obstructive sleep apnoea syndrome (OSAS)’,Chest,101, pp. 1221–1227Google Scholar
  22. Stoohs, R., Skrobal, A., andGuilleminault, C. (1993): ‘Does snoring intensity predict flow limitations of respiratory effort during sleep’,Respiration Phys.,92, pp. 27–38CrossRefGoogle Scholar
  23. Yen, F. C. (1991): ‘Real-time detection of obstructive sleep apnoea using airway pressure’. Masters Thesis, Biomedical Engineering, The University of Texas at ArlingtonGoogle Scholar
  24. Young, T., Palta, M., Dempsey, J., Skatrud, J., Weber, S., andBadr, S. (1993): ‘Prevalence and correlates of sleep disordered breathing in the Wisconsin sleep cohort study’,New England J. Med.,328, pp. 1230–1235CrossRefGoogle Scholar

Copyright information

© IFMBE 1997

Authors and Affiliations

  • K. Behbehani
    • 1
  • F. Lopez
    • 1
  • F. -C. Yen
    • 1
  • E. A. Lucas
    • 2
  • J. R. Burk
    • 2
  • J. P. Axe
    • 3
  • F. Kamangar
    • 4
  1. 1.Biomedical EngineeringUniversity of Texas at ArlingtonArlingtonUSA
  2. 2.All Saints Sleep Disorders CenterFort WorthTexasUSA
  3. 3.J.P. Axe IDArlingtonUSA
  4. 4.Computer Science and EngineeringUniversity of Texas at ArlingtonUSA

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