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Investigation of non-uniform airflow signal oscillation during high frequency chest compression.

Sohn K, Warwick WJ, Lee YW, Lee J, Holte JE - Biomed Eng Online (2005)

Bottom Line: The simulation results indicated that lung capacitance or the inertance of air is also not a factor in the non-uniformity of HFCC airflow signals.Although not perfect, our circuit analogue model allows us to effectively simulate the nonlinear characteristics of the respiratory system.We found that the amplitudes of HFCC airflow signals behave as a function of spontaneous airflow signals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA. sohn0015@umn.edu

ABSTRACT

Background: High frequency chest compression (HFCC) is a useful and popular therapy for clearing bronchial airways of excessive or thicker mucus. Our observation of respiratory airflow of a subject during use of HFCC showed the airflow oscillation by HFCC was strongly influenced by the nonlinearity of the respiratory system. We used a computational model-based approach to analyse the respiratory airflow during use of HFCC.

Methods: The computational model, which is based on previous physiological studies and represented by an electrical circuit analogue, was used for simulation of in vivo protocol that shows the nonlinearity of the respiratory system. Besides, airflow was measured during use of HFCC. We compared the simulation results to either the measured data or the previous research, to understand and explain the observations.

Results and discussion: We could observe two important phenomena during respiration pertaining to the airflow signal oscillation generated by HFCC. The amplitudes of HFCC airflow signals varied depending on spontaneous airflow signals. We used the simulation results to investigate how the nonlinearity of airway resistance, lung capacitance, and inertance of air characterized the respiratory airflow. The simulation results indicated that lung capacitance or the inertance of air is also not a factor in the non-uniformity of HFCC airflow signals. Although not perfect, our circuit analogue model allows us to effectively simulate the nonlinear characteristics of the respiratory system.

Conclusion: We found that the amplitudes of HFCC airflow signals behave as a function of spontaneous airflow signals. This is due to the nonlinearity of the respiratory system, particularly variations in airway resistance.

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HFCC airflow signals are demonstrated as a function of spontaneous airflow signals based on the same simulation data shown in fig. 8. Nonlinear airway resistance (a, c, and d) produces the non-uniform amplitudes of HFCC airflow signals.
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Figure 9: HFCC airflow signals are demonstrated as a function of spontaneous airflow signals based on the same simulation data shown in fig. 8. Nonlinear airway resistance (a, c, and d) produces the non-uniform amplitudes of HFCC airflow signals.

Mentions: We used the simulation results to investigate how the nonlinearity of airway resistance, lung capacitance, and inertance of air characterized the respiratory airflow. The simulation was repeated after setting one of the three properties as a linear constant value. Fig. 7 compares the linear values with the nonlinear values of the three properties. The linear values are means of the nonlinear values during the simulation. Fig. 8 presents the simulation results of the lung model under the imaginary assumptions. Fig. 8 (a) is normal respiratory airflow at 15 Hz, and fig. 6 (b) and fig. 8 (a) are from the same simulation data. Fig. 8 (b) demonstrates the predicted airflow signals at the mouth with linear airway resistance, which indicates the amplitudes of HFCC airflow signals do not vary significantly. Fig. 8 (c) is the airflow when lung capacitance is set to a linear value. Just like fig. 8 (a), HFCC airflow signals are the largest when spontaneous airflow signals are close to zero. Therefore, it can be presumed that the nonliearity of lung capacitance does not play a role in the non-uniformity of HFCC airflow signals. And neither is inertance of air. Fig. 8 (d), which shows the simulation data with linear inertance of air, is almost identical to fig. 8 (a). This indicates that the inertance of air is also not a factor in the non-uniformity of HFCC airflow signals. Fig. 9 shows the HFCC airflow signals as a function of spontaneous airflow signals based on the same simulation data shown in fig. 8. Fig. 8 (a), (c), and 8 (d) indicate that larger spontaneous airflow signals result in smaller oscillations of HFCC airflow signals whereas HFCC airflow signals do not seem to be related to spontaneous airflow signals in fig. 8 (b).


Investigation of non-uniform airflow signal oscillation during high frequency chest compression.

Sohn K, Warwick WJ, Lee YW, Lee J, Holte JE - Biomed Eng Online (2005)

HFCC airflow signals are demonstrated as a function of spontaneous airflow signals based on the same simulation data shown in fig. 8. Nonlinear airway resistance (a, c, and d) produces the non-uniform amplitudes of HFCC airflow signals.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1173124&req=5

Figure 9: HFCC airflow signals are demonstrated as a function of spontaneous airflow signals based on the same simulation data shown in fig. 8. Nonlinear airway resistance (a, c, and d) produces the non-uniform amplitudes of HFCC airflow signals.
Mentions: We used the simulation results to investigate how the nonlinearity of airway resistance, lung capacitance, and inertance of air characterized the respiratory airflow. The simulation was repeated after setting one of the three properties as a linear constant value. Fig. 7 compares the linear values with the nonlinear values of the three properties. The linear values are means of the nonlinear values during the simulation. Fig. 8 presents the simulation results of the lung model under the imaginary assumptions. Fig. 8 (a) is normal respiratory airflow at 15 Hz, and fig. 6 (b) and fig. 8 (a) are from the same simulation data. Fig. 8 (b) demonstrates the predicted airflow signals at the mouth with linear airway resistance, which indicates the amplitudes of HFCC airflow signals do not vary significantly. Fig. 8 (c) is the airflow when lung capacitance is set to a linear value. Just like fig. 8 (a), HFCC airflow signals are the largest when spontaneous airflow signals are close to zero. Therefore, it can be presumed that the nonliearity of lung capacitance does not play a role in the non-uniformity of HFCC airflow signals. And neither is inertance of air. Fig. 8 (d), which shows the simulation data with linear inertance of air, is almost identical to fig. 8 (a). This indicates that the inertance of air is also not a factor in the non-uniformity of HFCC airflow signals. Fig. 9 shows the HFCC airflow signals as a function of spontaneous airflow signals based on the same simulation data shown in fig. 8. Fig. 8 (a), (c), and 8 (d) indicate that larger spontaneous airflow signals result in smaller oscillations of HFCC airflow signals whereas HFCC airflow signals do not seem to be related to spontaneous airflow signals in fig. 8 (b).

Bottom Line: The simulation results indicated that lung capacitance or the inertance of air is also not a factor in the non-uniformity of HFCC airflow signals.Although not perfect, our circuit analogue model allows us to effectively simulate the nonlinear characteristics of the respiratory system.We found that the amplitudes of HFCC airflow signals behave as a function of spontaneous airflow signals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA. sohn0015@umn.edu

ABSTRACT

Background: High frequency chest compression (HFCC) is a useful and popular therapy for clearing bronchial airways of excessive or thicker mucus. Our observation of respiratory airflow of a subject during use of HFCC showed the airflow oscillation by HFCC was strongly influenced by the nonlinearity of the respiratory system. We used a computational model-based approach to analyse the respiratory airflow during use of HFCC.

Methods: The computational model, which is based on previous physiological studies and represented by an electrical circuit analogue, was used for simulation of in vivo protocol that shows the nonlinearity of the respiratory system. Besides, airflow was measured during use of HFCC. We compared the simulation results to either the measured data or the previous research, to understand and explain the observations.

Results and discussion: We could observe two important phenomena during respiration pertaining to the airflow signal oscillation generated by HFCC. The amplitudes of HFCC airflow signals varied depending on spontaneous airflow signals. We used the simulation results to investigate how the nonlinearity of airway resistance, lung capacitance, and inertance of air characterized the respiratory airflow. The simulation results indicated that lung capacitance or the inertance of air is also not a factor in the non-uniformity of HFCC airflow signals. Although not perfect, our circuit analogue model allows us to effectively simulate the nonlinear characteristics of the respiratory system.

Conclusion: We found that the amplitudes of HFCC airflow signals behave as a function of spontaneous airflow signals. This is due to the nonlinearity of the respiratory system, particularly variations in airway resistance.

Show MeSH