DocumentCode
830602
Title
Modeling and parameter identification of the human respiratory system
Author
Wiberg, D.M. ; Bellville, J.W. ; Brovko, O. ; Maine, R. ; Tai, T.C.
Author_Institution
University of California, Los Angeles, CA, USA
Volume
24
Issue
5
fYear
1979
fDate
10/1/1979 12:00:00 AM
Firstpage
716
Lastpage
720
Abstract
The human respiratory response to breathing an excess of carbon dioxide gas is modeled on physiological grounds as an almost linear second-order system. The parameters corresponding to the gains, time constants, threshold, and noise powers are identified by both least squares and maximum likelihood methods. The purpose is both to find the site of action of drugs and to gain understanding of this part of the respiratory control system. It is concluded that the maximum likelihood method is necessary in cases where the noise is not white and when unbiased estimates of the gains and variances are essential, such as in drug studies and in some physiological modeling.
Keywords
Delay systems; Least-squares estimation; Parameter identification; Respiratory systems; maximum-likelihood (ML) estimation; Carbon dioxide; Control systems; Drugs; Humans; Least squares methods; Maximum likelihood estimation; Parameter estimation; Power system modeling; Respiratory system; White noise;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.1979.1102156
Filename
1102156
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