EIT Imaging of Upper Airway to Estimate Its Size and Shape Changes During Obstructive Sleep Apnea


Noninvasive continuous imaging of the upper airway during natural sleep was conducted for patients with obstructive sleep apnea (OSA) using the electrical impedance tomography (EIT) technique. A safe amount of alternating current (AC) was injected into the lower head through multiple surface electrodes. Since the air is an electrical insulator, upper airway narrowing during OSA altered internal current pathways and changed the induced voltage distribution. Since the measured voltage data from the surface of the lower head were influenced not only by upper airway narrowing but respiratory motions, head motions, and blood flows, we developed a pre-processing algorithm to extract the voltage component originated from upper airway closing and opening. Using an EIT image reconstruction algorithm, time-series of EIT images of the upper airway were produced with a temporal resolution of 50 frames per second. Applying a postprocessing algorithm to the reconstructed EIT images, we could extract quantitative information about changes in the size and shape during upper airway closing and opening. Results of the clinical studies with seven normal subjects and ten OSA patients show the feasibility of the new method for OSA phenotyping and treatment planning.

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  1. 1.

    Berry, R. B., R. Brooks, C. E. Gamaldo, S. M. Harding, C. Marcus and B. Vaughn. The AASM manual for the scoring of sleep and associated events. Rules, Terminology and Technical Specifications, Darien, Illinois, American Academy of Sleep Medicine, 2012

  2. 2.

    Chesson, A. L., R. A. Ferber, J. M. Fry, M. Grigg-Damberger, K. Hartse, T. Hurwitz, S. Johnson, M. Littner, G. Kader, and G. Rosen. Practice parameters for the indications for polysomnography and related procedures. Sleep. 20:406–422, 1997.

    Article  Google Scholar 

  3. 3.

    Engleman, H. M., and M. R. Wild. Improving CPAP use by patients with the sleep apnoea/hypopnoea syndrome (SAHS). Sleep. Med. Rev. 7:81–99, 2003.

    Article  PubMed  Google Scholar 

  4. 4.

    Frerichs, I. Electrical impedance tomography (EIT) in applications related to lung and ventilation: a review of experimental and clinical activities. Physiol. Meas. 21:R1–R21, 2000.

    Article  CAS  PubMed  Google Scholar 

  5. 5.

    Frerichs, I., M. B. P. Amato, A. H. van Kaam, D. G. Tingay, Z. Zhao, B. Grychtol, M. Bodenstein, H. Gagnon, S. H. Böhm, E. Teschner, O. Stenqvist, T. Mauri, V. Torsani, L. Camporota, A. Schibler, G. K. Wolf, D. Gommers, S. Leonhardt, and A. Adler. Chest electrical impedance tomography examination, data analysis, terminology, clinical use and recommendations: consensus statement of the TRanslational EIT developmeNt stuDy group. Thorax. 72:83–93, 2017.

    Article  PubMed  Google Scholar 

  6. 6.

    Hersi, A. S. Obstructive sleep apnea and cardiac arrhythmias. Ann. Thorac. Med. 5:10–17, 2010.

    Article  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Hoffstein, V., and J. P. Szalai. Predictive value of clinical features in diagnosing obstructive sleep apnea. Sleep. 16:118–122, 1993.

    Article  CAS  PubMed  Google Scholar 

  8. 8.

    Holder, D. Detection of cerebral ischaemia in the anaesthetised rat by impedance measurement with scalp electrodes: implications for non-invasive imaging of stroke by electrical impedance tomography. Clin. Phys. Physiol. Meas. 13:63–75, 1992.

    Article  CAS  PubMed  Google Scholar 

  9. 9.

    Holder, D. S. Electrical Impedance Tomography: Methods, History and Applications. London: IOP, 2005.

    Google Scholar 

  10. 10.

    Hua, P., E. J. Woo, J. G. Webster and W. Tompkins. Bladder fullness detection using multiple electrodes. In: Engineering in Medicine and Biology Society. Conference on Proceedings of IEEE Engineering in Medicine and Biology Society, 1988, pp. 290–291

  11. 11.

    Hyvärinen, A., J. Karhunen, and E. Oja. Independent Component Analysis. Series on Adaptive and Learning Systems for Signal Processing, Communications, and Control. Hoboken: Wiley, 2001.

    Google Scholar 

  12. 12.

    Hyvärinen, A., and E. Oja. Independent component analysis: algorithms and applications. Neural. Netw. 13:411–430, 2000.

    Article  PubMed  Google Scholar 

  13. 13.

    Isono, S., J. E. Remmers, A. Tanaka, Y. Sho, J. Sato, and T. Nishino. Anatomy of pharynx in patients with obstructive sleep apnea and in normal subjects. J. Appl. Physiol. 82:1319–1326, 1997.

    Article  CAS  PubMed  Google Scholar 

  14. 14.

    Kim, Y. E., E. J. Woo, T. I. Oh and S. W. Kim. (in press). Real-time identification of upper airway occlusion using electrical impedance tomography. J. Clin. Sleep. Med. 2018.

  15. 15.

    Lee, K., E. J. Woo, and J. K. Seo. A fidelity-embedded regularization method for robust electrical impedance tomography. IEEE Trans. Med. Imaging. 37:1970–1977, 2018.

    Article  PubMed  Google Scholar 

  16. 16.

    Martinsen, O. G., and S. Grimnes. Bioimpedance and bioelectricity basics. London: Academic Press, 2015.

    Google Scholar 

  17. 17.

    Oh, T. I., H. Wi, D. Y. Kim, P. J. Yoo, and E. J. Woo. A fully parallel multi-frequency EIT system with flexible electrode configuration: KHU Mark2. Physiol. Meas. 32:835–849, 2011.

    Article  PubMed  Google Scholar 

  18. 18.

    Otero, A., P. Félix, J. Presedo, and C. Zamarrón. An evaluation of indexes as support tools in the diagnosis of sleep apnea. Ann. Biomed. Eng. 40:1825–1834, 2012.

    Article  PubMed  Google Scholar 

  19. 19.

    Pham, L. V., and A. R. Schwartz. The pathogenesis of obstructive sleep apnea. J. Thorac. Dis. 7:1358–1372, 2015.

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Pulletz, S., H. R. van Genderingen, G. Schmitz, G. Zick, D. Schädler, J. Scholz, N. Weiler, and I. Frerichs. Comparison of different methods to define regions of interest for evaluation of regional lung ventilation by EIT. Physiol. Meas. 27:S115–S127, 2006.

    Article  PubMed  Google Scholar 

  21. 21.

    Remmers, J., W. DeGroot, E. Sauerland, and A. Anch. Pathogenesis of upper airway occlusion during sleep. J. Appl. Physiol. 44:931–938, 1978.

    Article  CAS  PubMed  Google Scholar 

  22. 22.

    Romsauerova, A., A. McEwan, L. Horesh, R. Yerworth, R. Bayford, and D. S. Holder. Multi-frequency electrical impedance tomography (EIT) of the adult human head: initial findings in brain tumours, arteriovenous malformations and chronic stroke, development of an analysis method and calibration. Physiol. Meas. 27:S147–S161, 2006.

    Article  CAS  PubMed  Google Scholar 

  23. 23.

    Schlebusch, T., S. Nienke, S. Leonhardt, and M. Walter. Bladder volume estimation from electrical impedance tomography. Physiol. Meas. 35:1813–1823, 2014.

    Article  CAS  PubMed  Google Scholar 

  24. 24.

    Seo, J. K., and E. J. Woo. Nonlinear Inverse Problems in Imaging. Hoboken: Wiley, 2012.

    Google Scholar 

  25. 25.

    Veasey, S. C. Obstructive sleep apnea: re-evaluating our index of severity. Sleep. Med. 7:5–6, 2006.

    Article  PubMed  Google Scholar 

  26. 26.

    Walsh, J. H., M. S. Leigh, A. Paduch, K. J. Maddison, D. L. Philippe, J. J. Armstrong, D. D. Sampson, D. R. Hillman, and P. R. Eastwood. Evaluation of pharyngeal shape and size using anatomical optical coherence tomography in individuals with and without obstructive sleep apnoea. J. Sleep. Res. 17:230–238, 2008.

    Article  PubMed  Google Scholar 

  27. 27.

    Wellman, A., D. J. Eckert, A. S. Jordan, B. A. Edwards, C. L. Passaglia, A. C. Jackson, S. Gautam, R. L. Owens, A. Malhotra, and D. P. White. A method for measuring and modeling the physiological traits causing obstructive sleep apnea. J. Appl. Physiol. 110:1627–1637, 2011.

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Wellman, A., B. A. Edwards, S. A. Sands, R. L. Owens, S. Nemati, J. Butler, C. L. Passaglia, A. C. Jackson, A. Malhotra, and D. P. White. A simplified method for determining phenotypic traits in patients with obstructive sleep apnea. J. Appl. Physiol. 114:911–922, 2013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Wi, H., H. Sohal, A. L. McEwan, E. J. Woo, and T. I. Oh. Multi-frequency electrical impedance tomography system with automatic self-calibration for long-term monitoring. IEEE Trans. Biomed. Circuits. Syst. 8:119–128, 2014.

    Article  PubMed  Google Scholar 

  30. 30.

    Zinchuk, A. V., M. J. Gentry, J. Concato, and H. K. Yaggi. Phenotypes in obstructive sleep apnea: a definition, examples and evolution of approaches. Sleep. Med. Rev. 35:113–123, 2017.

    Article  PubMed  Google Scholar 

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This work was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant Number: HI17C0984) and the National Research Foundation (NRF-2017R1A2B2002169) in Republic of Korea.

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Correspondence to Eung Je Woo.

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Ayoub, G., Kim, Y.E., Oh, T.I. et al. EIT Imaging of Upper Airway to Estimate Its Size and Shape Changes During Obstructive Sleep Apnea. Ann Biomed Eng 47, 990–999 (2019). https://doi.org/10.1007/s10439-019-02210-7

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  • Obstructive sleep apnea (OSA)
  • Upper airway
  • Electrical impedance tomography (EIT)
  • Upper airway size
  • Upper airway shape