Parameter Estipiates in a Five-Element Respiratory Mechanical Model

Using four sets of forced random noise impedance data from each of five normal subjects and five patients with obstructuve lung disease, we computed parameter estimates for a three-element series model and a five-element parallel compartment model. For normal subjects, the five-element model provide...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 1982-06, Vol.BME-29 (6), p.460-463
Main Authors: Eyles, J. G., Pimmel, R. L., Fullten, J. M., Bromberg, P. A.
Format: Article
Language:English
Subjects:
Concurrent computing
Diseases
Frequency estimation
Frequency measurement
Immune system
Impedance measurement
Iterative algorithms
Lungs
Parameter estimation
Respiratory system
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Summary:Using four sets of forced random noise impedance data from each of five normal subjects and five patients with obstructuve lung disease, we computed parameter estimates for a three-element series model and a five-element parallel compartment model. For normal subjects, the five-element model provided no better fit to the impedance data than did the simple series model. Estimates obtained from normal subjects using this three-element model were reasonable and reproducible within 25 percent. For all subjects with lung disease, the five-element model provided a significantly (p 0.05) better fit than the three-element model. Estimates for parameters representing central inertance and resistance, airway compliance, and peripheral resistance were reasonable and reproducible-within 18 percent. However, estimates for the compliance of the lung and chest wall were more variable since measured impedance appeared to be insensitive to this parameter in the frequency range used.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.1982.324974