Augmented RIC model of respiratory systems

• US 20080139956A1
• Filed: 12/06/2006
• Published: 06/12/2008
• Est. Priority Date: 12/06/2006
• Status: Active Grant

• Current Assignee: Texas Christian University
• Original Assignee: Texas Christian University
• Inventors: Diong, Billy Ming
• Granted Patent: US 8,100,836 B2
• Time in Patent Office: Days
• US Class Current: 600/533
• CPC Class Codes: A61B 5/085 Measuring impedance of respiratory organs or lung elasticity
• CPC Class Codes: G09B 23/288 for artificial respiration or heart massage

Abstract

The present invention generally relates to an apparatus and method analyzing the respiratory characteristics of a human respiratory system from impulse oscillometry data, through the use of a linear network of electrical components. The present invention offers an improved alternative to the RIC respiratory circuit model, with an addition of a peripheral resistance to account for the resistance presented by the respiratory system'"'"'s small airways and of a capacitor to account for extrathoracic compliance. After air pressure and air flow measurements are obtained from the subject by performing Impulse Oscillometry System testing, a graphical representation of a mechanical impedance characteristic may be derived. This allows for the estimation and adjustment of parameter values of the linear network whose components correlate to the resistances, compliances and inertances inherent in the respiratory system. Additionally, the linear network of electrical components may be configured as a virtual network represented in graphical form wherein the parameter values are estimated and adjusted according to program instructions operating on a computer system. The linear network of electrical components serves to provide parametric means for detection, diagnosis and treatment of various pathologies in the human respiratory system.

Claims

1. A method for analyzing the respiratory characteristics of a human respiratory system from impulse oscillometry data, comprising the steps of:

obtaining a mechanical impedance characteristic for the respiratory system from measured impulse oscillometry data values, taken at a plurality of test frequencies, of air pressure and air flow at the entrance to the respiratory system of a human subject;

applying a linear network analogue of the human respiratory system having a first resistance, a first inductance and a first capacitance connected in series between first and second terminals, a second resistance connected across the first capacitance, and a second capacitance connected between the first and second terminals, wherein each such electrical component represents a parameter value of the respiratory system; and

estimating parameter values of the linear network analogue of electrical components to produce an electrical impedance analogue that matches the measured mechanical impedance characteristic within a predetermined tolerance over the frequency range of at least 5 to 35 Hz. and wherein the compliance parameter values are less than 10 liter/cmH₂O.

2. The method of claim 1, wherein the step of obtaining comprises:

coupling an impulse oscillometry device to the subject;

generating a predetermined sequence of impulse test signals at the plurality of test frequencies;

measuring air pressure and air flow parameters for each of the sequence of impulse test signals; and

deriving a graphical representation of a mechanical impedance characteristic from the measured impulse oscillometry data.

3. The method of claim 1, wherein the step of applying comprises:

defining the correspondence of the electrical components as;

the first resistance represents the central resistance of the airways;

the first inductance represents the inertance of the lungs;

the first capacitance represents the compliance of the alveoli;

the second resistance represents the peripheral resistance of the compliance of the alveoli; and

the second capacitance represents the extrathoracic compliance in the upper airways of the respiratory system.

4. The method of claim 1, wherein the step of estimating comprises:

making initial estimates of the parameter values using a random number generator; and

adjusting the initial estimates of the parameter values to conform the complex impedance between the first and second terminals to the mechanical impedance characteristic obtained from the impulse oscillometry measurements.

5. The method of claim 4, wherein the step of estimating further includes the step of:

expressing the predetermined tolerance as an error criterion selected from the group consisting of the methods of absolute value, least squares, minimax, and maximum likelihood.

6. The method of claim 5, wherein the error criterion is a least squares method defined as the weighted sum of the squared differences between the estimated parameters and the measured sample values wherein the sum is weighted by the frequency of occurrence of the sample values.

7. The method of claim 1, wherein computational processing is applied to the estimated parameter values of the linear network analogue for performing detection, diagnosis and treatment of respiratory pathologies.

8. The method of claim 1, wherein the method includes the effects of peripheral resistance of the small airways and of extrathoracic compliance of the respiratory system.

9. The method of claim 1, wherein the measurements of the air pressure and the air flow rate at the entrance to the respiratory system are obtained using impulse oscillometry.

10. A respiratory impedance model for use in analyzing impulse oscillometry data for a human subject, comprising:

a linear network of electrical components connected in series between first and second terminals including a first resistance, a first inductance and a first capacitance respectively corresponding to the central resistance of the airways, the lung inertance and the alveoli compliance of a human respiratory system;

a second resistance component connected directly across the first capacitance component and corresponding to the peripheral resistance of the alveoli in the small airways of the lungs; and

a second capacitance component connected between the first and second terminals corresponding to an extrathoracic compliance parameter of the human respiratory system.

11. The respiratory impedance model of claim 10, wherein the linear network is configured as an assembly of physical components supported on a frame.

12. The respiratory impedance model of claim 11, wherein each of the physical components is adjustable within a range of parameter values.

13. The respiratory impedance model of claim 10, wherein the first and second terminals are connectable to a signal generator and an instrument for measuring complex impedance.

14. The respiratory impedance model of claim 10, wherein the linear network is configured as a virtual network represented in graphical form and wherein the parameter values are estimated according to program instruction operating on a computer.

15. The respiratory impedance model of claim 10, wherein the linear network is configured as a virtual network represented in graphical form and wherein the parameter values are adjusted according to program instructions operating on a computer system.