Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT)

  • Suzani Mohamad Samuri
  • George Panoutsos
  • Mahdi Mahfouf
  • G. H. Mills
  • M. Denaï
  • B. H. Brown
Part of the Communications in Computer and Information Science book series (CCIS, volume 273)


Electrical Impedance Tomography (EIT), and in particular its application to pulmonary measurement, has been the subject of intensive research since its development in the early 1980s by Barber and Brown. One of the relatively recent advances in EIT is the development of an absolute EIT system (aEIT) which can estimate absolute values of lung resistivity and associated lung volumes. In this paper we present a new approach based on Computational Intelligence (CI) modelling to model the ‘Resistivity - Lung Volume’ relationship that will allow more accurate lung volume estimations using data from eight (8) healthy volunteers measured simultaneously via the Sheffield aEIT system and a Spirometer. The developed models show an improved accuracy in the prediction of lung volumes, as compared with the original Sheffield aEIT system. However the inter-individual differences observed in the subject-specific modelling behaviour of the ‘Resistivity-Lung Volume’ curves suggest that a model extension is needed, whereby the modelling structure auto-calibrates to account for subject (or patient-specific) inter-parameter variability.


Electrical impedance tomography (EIT) ANFIS Data-driven modelling Lung imaging Non-invasive monitoring 


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  1. 1.
    Barber, D.C., Brown, B.H.: Applied potential tomography. Journal of Physics E: Scientific Instruments 17, 723–733 (1984)CrossRefGoogle Scholar
  2. 2.
    Brown, B.H.: Electrical impedance tomography EIT: a review. Journal of Medical Engineering & Technology 27(3), 97–108 (2003)CrossRefGoogle Scholar
  3. 3.
    Panoutsos, G., Mahfouf, M., Brown, B.H., Mills, G.H.: Electrical Impedance Tomography (EIT) In Pulmonary Measurement: A Review of Application and Research. In: Proceedings of the Fifth IASTED International Conference on Biomedical Engineering, BioMED 2007, pp. 221–230 (2007)Google Scholar
  4. 4.
    Denai, M.A., Mahfouf, M., Mohamad-Samuri, S., Panoutsos, G., Brown, B.H., Mills, G.H.: Absolute electrical impedance tomography (aEIT) guided ventilation therapy in critical care patients: Simulations and future trends. IEEE Transactions on Information Technology in Biomedicine 14(3), 641–649 (2010)CrossRefGoogle Scholar
  5. 5.
    Brown, B.H., Barber, D.C.: Applied potential tomography: possible clinical applications. Clinical Physics & Physiological Measurement 6(2), 109–121 (1985)CrossRefGoogle Scholar
  6. 6.
    Brown, B.H., Leathard, A.D.: Measured and expected Cole parameters from electrical impedance tomographic spectroscopy images of the human thorax. Physiological Measurement 16(Supplement 3A), 57–67 (1995)CrossRefGoogle Scholar
  7. 7.
    Brown, B.H., Primhak, R.A., Smallwood, R.H., Milnes, P., Narracott, A.J., Jackson, M.J.: Neonatal lungs-can absolute lung resistivity be determined non-invasively? Med. & Biological Eng. & Computing 40, 388–394 (2002)CrossRefGoogle Scholar
  8. 8.
    Zubal, I.G., Harrell, C.R., Smith, E.O., Rattner, Z., Gindi, G., Hoffer, P.B.: Computerized three-dimensional segmented human anatomy. Medical Physics 21(2), 299–302 (1994)CrossRefGoogle Scholar
  9. 9.
    Barber, D.C., Seagar, A.D.: Fast reconstruction of resistance images. Clinical Physics & Physiological Measurement 8(Supplement A), 47–54 (1987)CrossRefGoogle Scholar
  10. 10.
    Barber, D.C., Borsic, A.: Electrical Impedance Tomography: Methods, History and Application. Institute of Physics (2005)Google Scholar
  11. 11.
    Brown, B.H., Mills, G.H.: Indirect measurement of lung density and air volume from Electrical Impedance Tomography EIT data. In: World Congress on Medical Physics and Biomedical Engineering, Seoul, Korea (2006)Google Scholar
  12. 12.
    Harris, N.D., Suggett, A.J., Barber, D.C., Brown, B.H.: Applications of applied potential tomography APT in respiratory medicine. Clin. Phys. Physiol. Meas. 8, 155–165 (1987)CrossRefGoogle Scholar
  13. 13.
    Harris, N.D., Suggett, A.J.: Applied potential tomography: a new technique for monitoring pulmonary function. Clinical Physics & Physiological Measurement 9(Supplement A), 79–85 (1988)CrossRefGoogle Scholar
  14. 14.
    Coulombe, N., Gagnon, H., Marquis, F., Skrobik, Y., Guardo, R.: A parametric model of the relationship between EIT and total lung volume. Physiological Measurement 26, 401–411 (2005)CrossRefGoogle Scholar
  15. 15.
    Jang, J.: ANFIS: Adaptive-Network-Based Fuzzy Inference System. IEEE Trans. on Systems, Man and Cybernetic 23, 665–685 (1993)CrossRefGoogle Scholar
  16. 16.
    Sugeno, M., Kang, G.T.: Structure Identification of Fuzzy Model. Fuzzy Sets and Systems 28(1), 15–33 (1988)MathSciNetzbMATHCrossRefGoogle Scholar
  17. 17.
    Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modelling and control. IEEE Trans. Systems, Man, and Cybernetics 15(1), 132–166 (1985)CrossRefGoogle Scholar
  18. 18.
    Panoutsos, G., Mills, G.H., Wang, A., Mahfouf, M., Brown, B.H.: Initial comparisons of absolute electrical impedance tomography (EIT) lung volume estimates with Spirometry. Proceedings of the ARS Meeting Anaesthetic Research Society, British Journal of Anaesthesia 98(2), 294 (2007)Google Scholar
  19. 19.
    Panoutsos, G., Tunney, D.R., Mills, G.H., Al-Jabary, T., Mahfouf, M., Brown, B.H.: Electrical Impedance Tomography: an evaluation of its ability to detect changes in lung volume and expansion during single lung ventilation. Proceedings of the ARS Meeting Anaesthetic Research Society, British Journal of Anaesthesia 100(4), 584 (2008)Google Scholar
  20. 20.
    Mohammad-Samuri, S., Denai, M.A., Panoutsos, G., Mahfouf, M., Linkens, D.A., Meekings, T., Mills, G.H., Brown, B.H.: The Sheffield Mk3.5 Absolute Resistivity aEIT System - Review of Recent Updates and Future Trends. In: 10th International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT), Manchester, UK, June 16-19 (2009)Google Scholar
  21. 21.
    Hepper, N.G.G., Fowlwer, W.S., Helmholz Jr., H.F.: Relationship of Height to Lung Volume in Healthy Men. Journal of the Americam College of Chest Physicians 37, 314–320 (1960)Google Scholar
  22. 22.
    Chiu, S.: Fuzzy Model Identification Based on Cluster Estimation. Journal of Intelligent and Fuzzy Systems 2(3) (1994)Google Scholar
  23. 23.
    Momamad-Samuri, S., Mahfouf, M., Denaï, M., Ross, J.J., Mills, G.H.: Absolute EIT Coupled To a Blood Gas Physiological Model For The Assessment of Lung Ventilation In Critical Care Patients. In: 21st Meeting of European Society for Computing and Technology in Anaesthesia in Intensive Care (ESCTAIC), Amsterdam, Netherland, October 6-9 (2010)Google Scholar
  24. 24.
    Hinz, J., Hahn, G., Neumann, P., Mohrenweiser, P., Hellige, G., Burchardi, H.: End-expiratory Lung Impedance Change Enables Bedside Monitoring of End-Expiratory Lung Volume Change. Journal of Intensive Care Medicine 29(1), 37–43 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Suzani Mohamad Samuri
    • 1
  • George Panoutsos
    • 1
  • Mahdi Mahfouf
    • 1
  • G. H. Mills
    • 2
  • M. Denaï
    • 3
  • B. H. Brown
    • 4
  1. 1.Department of Automatic Control and Systems EngineeringUniversity of SheffieldSheffieldU.K.
  2. 2.Department of Critical Care and AnaesthesiaNorthern General HospitalSheffieldU.K.
  3. 3.School of Science and Eng.Teesside UniversityMiddlesbroughU.K.
  4. 4.Department of Medical PhysicsRoyal Hallamshire HospitalSheffieldU.K.

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