A Rapidly Converging Algorithm for Estimating Respiratory Mechanical Parameters in a Five-Element Model

A rapidly converging algorithm for computing values for respiratory mechanical parameters from forced random noise independance data was developed and verified. The algorithm, which was based on a five-element Mead-type model, minimized the sum of squared differences between the model's respons...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 1983-10, Vol.BME-30 (10), p.675-679
Main Authors: Eyles, J. G., Pimmel, R. L.
Format: Article
Language:English
Subjects:
Airway Resistance
Biological and medical sciences
Cardiology
Computers
Digital filters
Epilepsy
Frequency dependence
Frequency estimation
Heart rate
Humans
Investigative techniques of ocular function and vision
Investigative techniques, diagnostic techniques (general aspects)
Lung Compliance
Medical sciences
Parameter estimation
Pediatrics
Respiration
Spectral analysis
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Summary:A rapidly converging algorithm for computing values for respiratory mechanical parameters from forced random noise independance data was developed and verified. The algorithm, which was based on a five-element Mead-type model, minimized the sum of squared differences between the model's response and experimental data, while imposing a nonnegativity constraint on the parameter values. It yielded parameter values that showed excellent agreement with values obtained previously using standard nonlinear regression analysis, but required much less computer time, 10 s versus 1 h. When this algorithm is coupled with the forced random impedance data collection techniques, it provides a rapid noninvasive method for estimating respiratory inertance, central resistance, peripheral resistance, and airway compliance. The problem of estimating peripheral compliance was not solved by this algorithm.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.1983.325071