Fractional order model parameters for the respiratory input impedance in healthy and in asthmatic children

This paper provides an evaluation of a fractional order model for the respiratory input impedance, using two groups of subjects, respectively healthy and asthmatic children. The purpose is to verify if the model is able to deliver statistically meaningful parameter values in order to classify the tw...

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Published inComputer methods and programs in biomedicine Vol. 101; no. 3; pp. 315 - 323
Main Authors Ionescu, Clara, Desager, Kristine, De Keyser, Robin
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ireland Ltd 01.03.2011
Elsevier
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ISSN0169-2607
1872-7565
1872-7565
DOI10.1016/j.cmpb.2010.11.010

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Summary:This paper provides an evaluation of a fractional order model for the respiratory input impedance, using two groups of subjects, respectively healthy and asthmatic children. The purpose is to verify if the model is able to deliver statistically meaningful parameter values in order to classify the two groups. The data are gathered with the non-invasive lung function test of forced oscillations technique, by means of a multisine signal within the 4–48 Hz frequency range. Based on our previous work, a fractional order model for this range of frequencies is obtained. Additional parameters are proposed to evaluate the two groups. The results indicate that the model was unable to detect significant changes between the asthmatic children with normal spirometry results (as result of medication) and the healthy children. Due to medication intake during the hours prior to the exam, bronchial challenge did not modify substantially the respiratory parameters. Our findings correspond to similar studies reported in the specialized literature. Combined model parameters, such as the tissue damping and the tissue elastance were significantly different in the two groups ( p < 0.01). Two extra indexes are introduced: the quality factor and the power factor, providing significantly different results between the two groups ( p ≪ 0.01). We conclude that the model can be used in the respective frequency range to characterize the two groups efficiently.
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ISSN:0169-2607
1872-7565
1872-7565
DOI:10.1016/j.cmpb.2010.11.010