ALGORITHMS, SYSTEMS, AND METHODS FOR ESTIMATING CARBON DIOXIDE STORES, TRANSFORMING RESPIRATORY GAS MEASUREMENTS, AND OBTAINING ACCURATE NONINVASIVE PULMONARY CAPILLARY BLOOD FLOW AND CARDIAC OUTPUT MEASUREMENTS

• US 6,955,651 B2
• Filed: 04/11/2002
• Issued: 10/18/2005
• Est. Priority Date: 02/22/2000
• Status: Expired due to Term

• Current Assignee: Respironics Incorporated (Koninklijke Philips N.V.)
• Original Assignee: Respironics Incorporated (Koninklijke Philips N.V.)
• Inventors: Orr, Joseph A., Kück, Kai, Brewer, Lara
• Primary Examiner(s): Nasser, Robert L.
• Application Number:
  US10/121,219
• Publication Number:
  US 20020183643A1
• Time in Patent Office: 1,286 Days
• Field of Search: 600/532, 73/233, 422/84
• US Class Current: 600/532
• CPC Class Codes: A61B 5/029 Measuring or recording blood output from the heart, e.g. minute volume A61B8/065 takes precedence
• CPC Class Codes: A61B 5/0836 Measuring rate of CO2 production
• CPC Class Codes: G01N 2001/2244 Exhaled gas, e.g. alcohol detecting
• CPC Class Codes: G01N 33/497 of gaseous biological material, e.g. breath

Abstract

Methods for estimating the volume of the carbon dioxide stores of an individual'"'"'s respiratory tract include determining a carbon dioxide store volume at which a correlation between corresponding signals of carbon dioxide elimination and an indicator of the content of carbon dioxide in blood of the individual is optimized. The estimate of the volume of carbon dioxide stores, which comprises a model of the respiratory tract, or lungs, of the individual, may be used as a transformation to improve the accuracy of one or both of the carbon dioxide elimination and carbon dioxide content signals. Transformation, or filtering, algorithms are also disclosed, as are systems in which the methods and algorithms may be used. The methods, algorithms, and systems may be used to accurately and noninvasively determine one or both of the pulmonary capillary blood flow and cardiac output of the individual.

Claims

1. A method for optimizing the accuracy of at least one of a carbon dioxide elimination measurement and a carbon dioxide excretion signal obtained from an individual based on carbon dioxide stores of a respiratory tract of the individual, comprising use of the formula:

{dot over({circumflex over (V)})}_BCO₂(n)=(1−

α

){dot over (V)}_MCO₂(n)+α

{dot over({circumflex over (V)})}_BCO₂(n−

1),

where {dot over (V)}_MCO₂(n) is the carbon dioxide elimination measurement, {dot over({circumflex over (V)})}_BCO₂(n−

1) is an estimate of carbon dioxide excretion of at least one preceding or subsequent breath, {dot over({circumflex over (V)})}_BCO₂(n) is an estimate of carbon dioxide excretion of the same breath as that for which the carbon dioxide elimination measurement was obtained, and α

is a transformation coefficient based on an estimate of the carbon dioxide stores of the respiratory tract of the individual.

2. The method of claim 1, comprising estimating carbon dioxide excretion of the at least one preceding or subsequent breath ({dot over({circumflex over (V)})}_BCO₂(n)) as follows:

{dot over({circumflex over (V)})}_BCO₂(n)={dot over (V)}_MCO₂(n)+{circumflex over (V)}_A*(n)[f_ACO₂(n)−

f_ACO₂(n−

1)]RR,

where {dot over (V)}_MCO₂(n) is the carbon dioxide elimination measurement for the at least one preceding or subsequent breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the individual during the at least one preceding or subsequent breath, [f_ACO₂(n)−

f_ACO₂(n−

1)] is a difference between a fraction of carbon dioxide in alveoli of the respiratory tract of the individual for the at least one preceding or subsequent breath and a breath that immediately preceded the at least one preceding or subsequent breath, and RR is a respiratory rate of the individual.

3. The method of claim 1, comprising determining an optimal α

value by at least one of iterative searching, rote searching, gradient searching, use of a set of predetermined equations, and adaptive filtering.

4. The method of claim 1, comprising adjusting the estimate of carbon dioxide excretion of the at least one preceding or subsequent breath to improve a correlation between the carbon dioxide elimination measurement and an indicator of the content of carbon dioxide in blood of the individual.

5. A method for improving an accuracy of a respiratory signal, comprising:

obtaining the respiratory signal from respiration of an individual during at least two breaths; and

applying a transformation based on carbon dioxide stores of a respiratory tract of the individual including carbon dioxide in lung tissues, to the respiratory signal;

wherein applying the transformation comprises employing a carbon dioxide elimination signal in the following algorithm;

{dot over({circumflex over (V)})}_BCO₂(n)=(1−

α

){dot over (V)}_MCO₂(n)+α

{dot over({circumflex over (V)})}_BCO₂(n−

1),

where {dot over (V)}_MCO₂(n) is a carbon dioxide elimination measurement, {dot over({circumflex over (V)})}_BCO₂(n−

1) is an estimate of carbon dioxide excretion of at least one preceding or subsequent breath, {dot over({circumflex over (V)})}_BCO₂(n) is an estimate of carbon dioxide excretion of the same breath as that for which the carbon dioxide elimination measurement was obtained, and α

is a transformation coefficient based on an estimate of the carbon dioxide stores of the respiratory tract of the individual.

6. The method of claim 5, wherein obtaining the respiratory signal comprises obtaining a carbon dioxide elimination signal from respiration of the individual.

7. The method of claim 6, wherein applying the transformation comprises employing an estimate of at least one of a volume of the carbon dioxide stores of the respiratory tract of the individual and a flow of carbon dioxide into or out of the carbon dioxide stores.

8. The method of claim 5, comprising estimating the carbon dioxide excretion of the at least one preceding or subsequent breath ({dot over({circumflex over (V)})}_BCO₂(n)) as follows:

{dot over({circumflex over (V)})}_BCO₂(n)={dot over (V)}_MCO₂(n)+{circumflex over (V)}_A*(n)[f_ACO₂(n)−

f_ACO₂(n−

1)]RR,

where {dot over (V)}_MCO₂(n) is the carbon dioxide elimination measurement for the at least one preceding or subsequent breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the individual during the at least one preceding or subsequent breath, [f_ACO₂(n)−

f_ACO₂(n−

1)] is the difference between the fraction of carbon dioxide in alveoli of the respiratory tract of the individual for the at least one preceding or subsequent breath and a breath that immediately preceded the at least one preceding or subsequent breath, and RR is a respiratory rate of the individual.

9. The method of claim 5, further comprising determining an optimal α

value.

10. The method of claim 9, wherein determining the optimal α

value comprises at least one of iterative searching, rote searching, gradient searching, use of a set of predetermined equations, and adaptive filtering.

22. The respiratory monitoring device of claim 5, wherein the at least one processing element is programmed to estimate carbon dioxide excretion of the at least one preceding or subsequent breath ({dot over({circumflex over (V)})}_BCO₂(n)) as follows:

 

{dot over({circumflex over (V)})}_BCO₂(n)={dot over (V)}_MCO₂(n)+{circumflex over (V)}_A*(n)[f_ACO₂(n)−

f_ACO₂(n−

1)]RR,

where {dot over (V)}_MCO₂(n) is the carbon dioxide elimination measurement for the at least one preceding or subsequent breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the individual during the at least one preceding or subsequent breath, [f_ACO₂(n)−

f_ACO₂(n−

1)] is the difference between the fraction of carbon dioxide in alveoli of the respiratory tract of the individual for the at least one preceding or subsequent breath and a breath that immediately preceded the at least one preceding or subsequent breath, and RR is a respiratory rate of the individual.

23. The respiratory monitoring device of claim 5, wherein the at least one processing element is programmed to determine an optimal α

value.

24. The respiratory monitoring device of claim 23, wherein the at least one processing element is programmed to determine the optimal α

value by at least one of iterative searching, rote searching, gradient searching, use of a set of predetermined equations, and adaptive filtering.

11. A method for improving an accuracy of a respiratory signal, comprising:

obtaining a carbon dioxide elimination signal from respiration of an individual during at least two breaths; and

applying a transformation based on carbon dioxide stores of a respiratory tract of the individual to the respiratory signal, the transformation employing the following algorithm;

{dot over({circumflex over (V)})}_BCO₂(n)=(1−

α

){dot over (V)}_MCO₂(n)+α

{dot over({circumflex over (V)})}_BCO₂(n−

1),

 

where {dot over (V)}_MCO₂(n) is a carbon dioxide elimination measurement, {dot over({circumflex over (V)})}_BCO₂(n−

1) is an estimate of carbon dioxide excretion of at least one preceding or subsequent breath, {dot over({circumflex over (V)})}_BCO₂(n) is an estimate of carbon dioxide excretion of the same breath as that for which the carbon dioxide elimination measurement was obtained, and α

is a transformation coefficient based on an estimate of the carbon dioxide stores of the respiratory tract of the individual.

12. The method of claim 11, comprising estimating the carbon dioxide excretion of the at least one preceding or subsequent breath ({dot over({circumflex over (V)})}_BCO₂(n)) as follows:

{dot over({circumflex over (V)})}_BCO₂(n)={dot over (V)}_MCO₂(n)+{circumflex over (V)}_A*(n)[f_ACO₂(n)−

f_ACO₂(n−

1)]RR,

where {dot over (V)}_MCO₂(n) is the carbon dioxide elimination measurement for the at least one preceding or subsequent breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the individual during the at least one preceding or subsequent breath, [f_ACO₂(n)−

f_ACO₂(n−

1)] is the difference between the fraction of carbon dioxide in alveoli of the respiratory tract of the individual for the at least one preceding or subsequent breath and a breath that immediately preceded the at least one preceding or subsequent breath, and RR is a respiratory rate of the individual.

13. The method of claim 11, further comprising determining an optimal α

value.

14. The method of claim 13, wherein determining the optimal α

value comprises at least one of iterative searching, rote searching, gradient searching, use of a set of predetermined equations, and adaptive filtering.

15. A respiratory monitoring device configured to optimize the accuracy of at least one of a carbon dioxide elimination measurement and a carbon dioxide excretion signal obtained from an individual based on carbon dioxide stores of a respiratory tract of the individual, comprising at least one processing element programmed to employ the formula:

{dot over({circumflex over (V)})}_BCO₂(n)=(1−

α

){dot over (V)}_MCO₂(n)+α

{dot over({circumflex over (V)})}_BCO₂(n−

1),

where {dot over (V)}_MCO₂(n) is the carbon dioxide elimination measurement, {dot over({circumflex over (V)})}_BCO₂(n−

1) is an estimate of carbon dioxide excretion of at least one preceding or subsequent breath, {dot over({circumflex over (V)})}_BCO₂(n) is an estimate of carbon dioxide excretion of the same breath as that for which the carbon dioxide elimination measurement was obtained, and α

is a transformation coefficient based on an estimate of the carbon dioxide stores of the respiratory tract of the individual.

16. The respiratory monitoring device of claim 15, wherein the at least one processing element is configured to estimate carbon dioxide excretion of the at least one preceding or subsequent breath ({dot over({circumflex over (V)})}_BCO₂(n)) as follows:

{dot over({circumflex over (V)})}_BCO₂(n)={dot over (V)}_MCO₂(n)+{circumflex over (V)}_A*(n)[f_ACO₂(n)−

f_ACO₂(n−

1)]RR,

where {dot over (V)}_MCO₂(n) is the carbon dioxide elimination measurement for the at least one preceding or subsequent breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the individual during the at least one preceding or subsequent breath, [f_ACO₂(n)−

f_ACO₂(n−

1)] is a difference between a fraction of carbon dioxide in alveoli of the respiratory tract of the individual for the at least one preceding or subsequent breath and a breath that immediately preceded the at least one preceding or subsequent breath, and RR is a respiratory rate of the individual.

17. The respiratory monitoring device of claim 15, wherein the at least one processing element is configured to determine an optimal α

value by at least one of iterative searching, rote searching, gradient searching, use of a set of predetermined equations, and adaptive filtering.

18. The respiratory monitoring device of claim 15, wherein the at least one processing element is configured to adjust the estimate of carbon dioxide excretion of the at least one preceding or subsequent breath to improve a correlation between the carbon dioxide elimination measurement and an indicator of the content of carbon dioxide in blood of the individual.

19. A respiratory monitoring device configured to improve an accuracy of a respiratory signal, comprising:

at least one sensor for obtaining the respiratory signal from respiration of an individual during at least two breaths; and

at least one processing element programmed to apply a transformation based on carbon dioxide stores of a respiratory tract of the individual, including carbon dioxide in tissues of the lungs, to the respiratory signal;

wherein the at least one processing element is configured to apply the following transformation to the carbon dioxide elimination signal;

{dot over({circumflex over (V)})}_BCO₂(n)=(1−

α

){dot over (V)}_MCO₂(n)+α

{dot over({circumflex over (V)})}_BCO₂(n−

1),

where {dot over (V)}_MCO₂(n) is a carbon dioxide elimination measurement, {dot over({circumflex over (V)})}_BCO₂(n−

1) is an estimate of carbon dioxide excretion of at least one preceding or subsequent breath, {dot over({circumflex over (V)})}_BCO₂(n) is an estimate of carbon dioxide excretion of the same breath as that for which the carbon dioxide elimination measurement was obtained, and α

is a transformation coefficient based on an estimate of the carbon dioxide stores of the respiratory tract of the individual.

20. The respiratory monitoring device of claim 19, wherein the at least one sensor is configured to obtain a carbon dioxide elimination signal from respiration of the individual.

21. The respiratory monitoring device of claim 20, wherein the transformation that the at least one processing element is programmed to apply employs an estimate of at least one of a volume of the carbon dioxide stores of the respiratory tract of the individual and a flow of carbon dioxide into or out of the carbon dioxide stores.

25. A respiratory monitoring device configured to improve an accuracy of a respiratory signal, comprising:

at least one sensor for obtaining a carbon dioxide elimination signal from respiration of an individual during at least two breaths; and

at least one processing element for applying a transformation based on carbon dioxide stores of a respiratory tract of the individual to the respiratory signal, the transformation including the following algorithm;

{dot over({circumflex over (V)})}_BCO₂(n)=(1−

α

){dot over (V)}_MCO₂(n)+α

{dot over({circumflex over (V)})}_BCO₂(n−

1),

where {dot over (V)}_MCO₂(n) is a carbon dioxide elimination measurement, {dot over({circumflex over (V)})}_BCO_2(n−

1) is an estimate of carbon dioxide excretion of at least one preceding or subsequent breath, {dot over({circumflex over (V)})}_BCO₂(n) is an estimate of carbon dioxide excretion of the same breath as that for which the carbon dioxide elimination measurement was obtained, and α

is a transformation coefficient based on an estimate of the carbon dioxide stores of the respiratory tract of the individual.

26. The respiratory monitoring device of claim 25, wherein the transformation with which the at least one processing element is programmed estimates carbon dioxide excretion of the at least one preceding or subsequent breath ({dot over({circumflex over (V)})}_BCO₂(n)) as follows:

{dot over({circumflex over (V)})}_BCO₂(n)={dot over (V)}_MCO₂(n)+{circumflex over (V)}_A*(n)[f_ACO₂(n)−

f_ACO₂(n−

1)]RR,

where {dot over (V)}_MCO₂(n) is the carbon dioxide elimination measurement for the at least one preceding or subsequent breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the individual during the at least one preceding or subsequent breath, [f_ACO₂(n)−

f_ACO₂(n−

1)] is the difference between the fraction of carbon dioxide in alveoli of the respiratory tract of the individual for the at least one preceding or subsequent breath and a breath that immediately preceded the at least one preceding or subsequent breath, and RR is a respiratory rate of the individual.

27. The respiratory monitoring device of claim 25, wherein the at least one processing element is programmed to determine an optimal α

value.

28. The respiratory monitoring device of claim 27, wherein the at least on processing element is programmed to determine the optimal α

value by at least one of iterative searching, rote searching, gradient searching, use of a set of predetermined equations, and adaptive filtering.