Advertisement

Journal of Mechanical Science and Technology

, Volume 29, Issue 7, pp 2803–2815 | Cite as

Statistical calibration of a finite element model for human middle ear

  • Dooho LeeEmail author
  • Tae-Soo Ahn
Article

Abstract

A Finite element (FE) model of a human middle ear is developed, assessed, and updated using a statistical approach. The model consists of three ossicles (malleus, incus, and stapes), a tympanic membrane, tendons, and ligaments. The uncertainty of the model input parameters associated with the material properties and boundary conditions are considered in order to assess the validity of the model. The variation of the umbo displacement transfer function (UDTF) as a result of the uncertainty of the model input parameters is estimated and compared with those from experiments. Using the analysis of variance (ANOVA) with a three-level orthogonal array, the most important calibration parameters, which are composed of stiffness-related and density variables, are selected. Furthermore, a metric for statistical calibration is introduced. Through minimizing the calibration metric, the calibration parameters are updated in order to enhance the performance of the middle ear FE model. The proposed statistical calibration framework effectively improves the middle ear FE model performance.

Keywords

Sound transfer function Middle ear Statistical calibration approach FE model validation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    S. E. Voss, J. J. Rosowski, S. N. Merchant and W. T. Peake, Acoustic responses of the human middle ear, Hearing Research, 150 (2000) 43–69.CrossRefGoogle Scholar
  2. [2]
    R. Aibara, J. T. Welsh, S. Puria and R. L. Goode, Human middle-ear sound transfer function and cochlear input impedance, Hearing Research, 152 (2001) 100–109.CrossRefGoogle Scholar
  3. [3]
    J. Pascal, A. Bourgeade, M. Lagier and C. Legros, Linear and nonlinear model of the human middle ear, The Journal of the Acoustical Society of America, 104 (1998) 1509–1516.CrossRefGoogle Scholar
  4. [4]
    G. Volandri, F. Di Puccio, P. Forte and S. Manetti, Modeloriented review and multi-body simulation of the ossicular chain of the human middle ear, Medical Engineering & Physics (2012).Google Scholar
  5. [5]
    T. Koike, H. Wada and T. Kobayashi, Modeling of the human middle ear using the finite-element method, The Journal of the Acoustical Society of America, 111 (2002) 1306–1317.zbMATHCrossRefGoogle Scholar
  6. [6]
    R. Gan, B. Reeves and X. Wang, Modeling of sound transmission from ear canal to cochlea, Annals of Biomedical Engineering, 35 (2007) 2180–2195.CrossRefGoogle Scholar
  7. [7]
    R. Z. Gan, Q. Sun, B. Feng and M. W. Wood, Acousticstructural coupled finite element analysis for sound transmission in human ear—Pressure distributions, Medical Engineering & Physics, 28 (2006) 395–404.CrossRefGoogle Scholar
  8. [8]
    C.-F. Lee, P.-R. Chen, W.-J. Lee, J.-H. Chen and T.-C. Liu, Three-dimensional reconstruction and modeling of middle ear biomechanics by high-resolution computed tomography and finite element analysis, The Laryngoscope, 116 (2006) 711–716.CrossRefGoogle Scholar
  9. [9]
    T.-S. Ahn, M.-J. Baek and D. Lee, Experimental measurement of tympanic membrane response for finite element model validation of a human middle ear, Springer Plus, 2 (2013) 527.CrossRefGoogle Scholar
  10. [10]
    Y. M. Gal, M.-J. Baek and D. Lee, Finite element analysis of sound transfer characteristics for middle ear, Transactions of the Korean Society of Mechanical Engineers A, 35 (2011) 1563–1571.CrossRefGoogle Scholar
  11. [11]
    T. G. Trucano, L. P. Swiler, T. Igusa, W. L. Oberkampf and M. Pilch, Calibration, validation, and sensitivity analysis: What’s what, Reliability Engineering & System Safety, 91 (2006) 1331–1357.CrossRefGoogle Scholar
  12. [12]
    B. D. Youn, B. C. Jung, Z. Xi, S. B. Kim and W. R. Lee, A hierarchical framework for statistical model calibration in engineering product development, Computer Methods in Applied Mechanics and Engineering, 200 (2011) 1421–1431.CrossRefGoogle Scholar
  13. [13]
    K. Campbell, Statistical calibration of computer simulations, Reliability Engineering & System Safety, 91 (2006) 1358–1363.CrossRefGoogle Scholar
  14. [14]
    M. C. Kennedy and A. O’Hagan, Bayesian calibration of computer models, Journal of the Royal Statistical Society, Series B (Statistical Methodology), 63 (2001) 425–464.zbMATHMathSciNetCrossRefGoogle Scholar
  15. [15]
    Y. Xiong, W. Chen, K.-L. Tsui and D. W. Apley, A better understanding of model updating strategies in validating engineering models, Computer Methods in Applied Mechanics and Engineering, 198 (2009) 1327–1337.CrossRefGoogle Scholar
  16. [16]
    H. B. Henninger, S. P. Reese, A. E. Anderson and J. A. Weiss, Validation of computational models in biomechanics, Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 224 (2010) 801–812.CrossRefGoogle Scholar
  17. [17]
    A. E. Anderson, B. J. Ellis and J. A. Weiss, Verification, validation and sensitivity studies in computational biomechanics, Computer Methods in Biomechanics and Biomedical Engineering, 10 (2007) 171–184.zbMATHCrossRefGoogle Scholar
  18. [18]
    D. Lee and T.-S. Ahn, A boundary element model for acoustic responses in the ear canal and its statistical validation and updating, Journal of Mechanical Science and Technology, 28 (2014) 1203–1217.CrossRefGoogle Scholar
  19. [19]
    S. Nishihara and R. L. Goode, Measurement of tympanic membrane vibration in 99 human ears, in: H.t. KB (Ed.) Middle ear mechanics in research and otosurgery, Department of Oto-Rhino-Laryngology, Dresden, University of Technology, Dresden, Germany (1996) 91–93.Google Scholar
  20. [20]
    C. J. Roy and W. L. Oberkampf, A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing, Computer Methods in Applied Mechanics and Engineering, 200 (2011) 2131–2144.MathSciNetCrossRefGoogle Scholar
  21. [21]
    T. Cheng, C. Dai and R. Gan, Viscoelastic properties of human tympanic membrane, Annals of Biomedical Engineering, 35 (2007) 305–314.CrossRefGoogle Scholar
  22. [22]
    S. M. Hesabgar, H. Marshall, S. K. Agrawal, A. Samani and H. M. Ladak, Measuring the quasi-static Young’s modulus of the eardrum using an indentation technique, Hearing Research, 263 (2010) 168–176.CrossRefGoogle Scholar
  23. [23]
    J. Aernouts, J. A. M. Soons and J. J. J. Dirckx, Quantification of tympanic membrane elasticity parameters from in situ point indentation measurements: Validation and preliminary study, Hearing Research, 263 (2010) 177–182.CrossRefGoogle Scholar
  24. [24]
    X. Zhang and R. Z. Gan, Dynamic properties of human tympanic membrane- experimental measurement and modelling analysis, International Journal of Experimental and Computational Biomechanics, 1 (2010) 252–270.CrossRefGoogle Scholar
  25. [25]
    N. Ghadarghadar, S. K. Agrawal, A. Samani and H. M. Ladak, Estimation of the quasi-static Young’s modulus of the eardrum using a pressurization technique, Computer Methods and Programs in Biomedicine, 110 (2013) 231–239.CrossRefGoogle Scholar
  26. [26]
    R. Z. Gan, F. Yang, X. Zhang and D. Nakmali, Mechanical properties of stapedial annular ligament, Medical Engineering & Physics, 33 (2011) 330–339.CrossRefGoogle Scholar
  27. [27]
    B. Youn, Z. Xi and P. Wang, Eigenvector dimension reduction (EDR) method for sensitivity-free probability analysis, Structural and Multidisciplinary Optimization, 37 (2008) 13–28.MathSciNetCrossRefGoogle Scholar
  28. [28]
    B. C. Jung, D. Lee, B. D. Youn and S. Lee, A statistical characterization method for damping material properties and its application to structural-acoustic system design, The Journal of Mechanical Science and Technology, 25 (2011) 1893–1904.zbMATHCrossRefGoogle Scholar
  29. [29]
    S. Wang, W. Chen and K.-L. Tsui, Bayesian validation of computer models, Technometrics, 51 (2009) 439–451.MathSciNetCrossRefGoogle Scholar
  30. [30]
    R. Roy, A primer on the Taguchi method, Van Norstrand Reinhold, New York (1990).Google Scholar
  31. [31]
    L. Qi, C. S. Mikhael and W. R. J. Funnell, Application of the Taguchi method to sensitivity analysis of a middle-ear finite-element model, Proc. 28th Ann. Conf. Can. Med. Biol. Eng. Soc. (2004) 153–156.Google Scholar
  32. [32]
    The Mathworks Inc., Optimization toolbox user’s guide: For Use with MATLAB, The Mathworks Inc., Natick, MA 01760-2098, USA (2000).Google Scholar
  33. [33]
    S. Van der Jeught, J. J. Dirckx, J. R. Aerts, A. Bradu, A. G. Podoleanu and J. A. Buytaert, Full-field thickness distribution of human tympanic membrane obtained with optical coherence tomography, JARO, 14 (2013) 483–494.CrossRefGoogle Scholar
  34. [34]
    W. L. Oberkampf and C. J. Roy, Verification and validation in scientific computing, Cambridge University Press, Cambridge (2010).CrossRefGoogle Scholar

Copyright information

© The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringDongeui UniversityBusanKorea
  2. 2.SEGI Engineering Inc.BusanKorea

Personalised recommendations