Abstract
Parametric characterization of nitric oxide (NO) gas exchange using a two-compartment model of the lungs is a potentially promising, non-invasive technique to characterize inflammatory lung diseases. Currently, this techniques is limited to single breath maneuvers, including pre-expiratory breath-hold, which is cumbersome for children and individuals with compromised lung function. The current study extends the two-compartment model to parametric characterization of NO gas exchange from tidal breathing data. We assess the potential to estimate up to six flow-independent parameters, and study alternate breathing patterns by varying breathing frequency and inspiratory/expiratory flow rate ratio at constant alveolar ventilation rate. We identify three, easily characterized flow-independent parameters, which include maximum airway flux, steady state alveolar concentration, and airway volume (uncertainty < 10%). Rapid inhalation followed by slow (long duration) exhalation facilitates estimates of all flow-independent parameters. Our results demonstrate the potential of parametric analysis of tidal breathing data to characterize NO pulmonary exchange.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1489-1490 |
| Number of pages | 2 |
| Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
| Volume | 2 |
| State | Published - Dec 1 2002 |
| Event | Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States Duration: Oct 23 2002 → Oct 26 2002 |
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Keywords
- Airways
- Diffusing capacity
- NO
- Parameter estimation
- Tidal breathing
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics
Cite this
Characterizing nitric oxide exchange dynamics during tidal breathing : Theory. / Conderelli, P.; George, Steven.
In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 2, 01.12.2002, p. 1489-1490.Research output: Contribution to journal › Conference article
}
TY - JOUR
T1 - Characterizing nitric oxide exchange dynamics during tidal breathing
T2 - Theory
AU - Conderelli, P.
AU - George, Steven
PY - 2002/12/1
Y1 - 2002/12/1
N2 - Parametric characterization of nitric oxide (NO) gas exchange using a two-compartment model of the lungs is a potentially promising, non-invasive technique to characterize inflammatory lung diseases. Currently, this techniques is limited to single breath maneuvers, including pre-expiratory breath-hold, which is cumbersome for children and individuals with compromised lung function. The current study extends the two-compartment model to parametric characterization of NO gas exchange from tidal breathing data. We assess the potential to estimate up to six flow-independent parameters, and study alternate breathing patterns by varying breathing frequency and inspiratory/expiratory flow rate ratio at constant alveolar ventilation rate. We identify three, easily characterized flow-independent parameters, which include maximum airway flux, steady state alveolar concentration, and airway volume (uncertainty < 10%). Rapid inhalation followed by slow (long duration) exhalation facilitates estimates of all flow-independent parameters. Our results demonstrate the potential of parametric analysis of tidal breathing data to characterize NO pulmonary exchange.
AB - Parametric characterization of nitric oxide (NO) gas exchange using a two-compartment model of the lungs is a potentially promising, non-invasive technique to characterize inflammatory lung diseases. Currently, this techniques is limited to single breath maneuvers, including pre-expiratory breath-hold, which is cumbersome for children and individuals with compromised lung function. The current study extends the two-compartment model to parametric characterization of NO gas exchange from tidal breathing data. We assess the potential to estimate up to six flow-independent parameters, and study alternate breathing patterns by varying breathing frequency and inspiratory/expiratory flow rate ratio at constant alveolar ventilation rate. We identify three, easily characterized flow-independent parameters, which include maximum airway flux, steady state alveolar concentration, and airway volume (uncertainty < 10%). Rapid inhalation followed by slow (long duration) exhalation facilitates estimates of all flow-independent parameters. Our results demonstrate the potential of parametric analysis of tidal breathing data to characterize NO pulmonary exchange.
KW - Airways
KW - Diffusing capacity
KW - NO
KW - Parameter estimation
KW - Tidal breathing
UR - http://www.scopus.com/inward/record.url?scp=0036911488&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0036911488&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:0036911488
VL - 2
SP - 1489
EP - 1490
JO - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
SN - 1557-170X
ER -