• DocumentCode
    3060473
  • Title

    Respiratory parameter estimation in linear lung models

  • Author

    Saatçi, Esra ; Akan, Aydin

  • Author_Institution
    Department of Electronic Engineering, Istanbul Kultur University, BakÃ\xadrkoy, Tÿrkiye
  • fYear
    2008
  • fDate
    20-25 Aug. 2008
  • Firstpage
    307
  • Lastpage
    310
  • Abstract
    If the respiratory system is represented as a one compartment model composed of linear electrical elements, the Minimum Variance Unbiased Estimation (MVUE) is the optimum statistical method to estimate the model parameters. Two well known linear models, RIC and Viscoelastic models were chosen and their parameters were estimated by MVUE. Synthetic data simulations showed that minimum 100Hz sampling rate is required in order to have minimum variance. Estimation of lung inertance and viscoelastic tissue compliance parameters resulted in very large estimation variance, whereas the rest of the parameters were estimated successfully. Both parameter values and estimator variances have their own characterization in terms of patient discrimination for diagnostic purposes.
  • Keywords
    Elasticity; Frequency estimation; Frequency measurement; Lungs; Parameter estimation; Pressure measurement; Respiratory system; Statistical analysis; Time domain analysis; Viscosity; Algorithms; Computer Simulation; Diagnosis, Computer-Assisted; Elastic Modulus; Forced Expiratory Volume; Humans; Linear Models; Lung; Models, Biological; Respiratory Mechanics; Spirometry; Viscosity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-1814-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2008.4649151
  • Filename
    4649151