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 7,074,196 B2
• Filed: 04/08/2005
• Issued: 07/11/2006
• Est. Priority Date: 02/22/2000
• Status: Expired due to Term

• Current Assignee: Respironics Incorporated
• Original Assignee: Respironics Incorporated
• Inventors: Orr, Joseph A., Kück, Kai, Brewer, Lara
• Primary Examiner(s): Nasser, Robert L.
• Application Number:
  US11/102,072
• Publication Number:
  US 20050177055A1
• Time in Patent Office: 459 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 obtained from a subject based on carbon dioxide stores of a respiratory tract of the subject, comprising applying a filter comprising an algorithm that employs a transformation coefficient based on carbon dioxide stores to a carbon dioxide elimination measurement of at least one breath by the subject and a carbon dioxide excretion estimate or carbon dioxide excretion signal for at least another breath.

2. The method of claim 1, wherein applying comprises applying a filter comprising an algorithm that employs a transformation coefficient based on a functional residual capacity of the subject.

3. The method of claim 1, wherein applying comprises applying a filter comprising an algorithm that employs a transformation coefficient based on a functional residual capacity of the subject and an amount of carbon dioxide that has diffused into lung tissues.

4. The method of claim 1, wherein applying comprises applying a low-pass filter.

5. The method of claim 4, wherein applying the low-pass filter comprises employing the following formula:

(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 another breath, and a is the transformation coefficient based on an estimate of the carbon dioxide stores of the respiratory tract of the subject.

6. The method of claim 1, further comprising:

estimating carbon dioxide excretion for the at least another breath.

7. The method of claim 6, wherein estimating carbon dioxide excretion for the at least another breath includes accounting for carbon dioxide stores in the respiratory tract of the subject during the at least another breath.

8. The method of claim 7, wherein accounting for carbon dioxide stores comprises accounting for functional residual capacity during the at least another breath.

9. The method of claim 7, wherein accounting for carbon dioxide stores comprises accounting for functional residual capacity and carbon dioxide within tissues of the respiratory tract during the at least another breath.

10. The method of claim 6, wherein estimating carbon dioxide excretion of the at least another breath includes employing the formula:

{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 another breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the subject during the at least another 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 subject for the at least another breath and an immediately preceding breath, and RR is a respiratory rate of the subject.

11. The method of claim 1, further comprising determining an optimal value for the transformation coefficient.

12. The method of claim 11, wherein determining the optimal value comprises at least one of iterative searching, rote searching, gradient searching, use of a set of predetermined equations, and adaptive filtering.

13. The method of claim 11, further comprising, following the act of applying the filter, adjusting the estimate of carbon dioxide excretion of the at least another breath to improve a correlation between the carbon dioxide elimination measurement and an indicator of the content of carbon dioxide in blood of the subject.

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

obtaining the respiratory signal from respiration of a subject during at least two breaths; and

applying a filter comprising an algorithm that employs a transformation coefficient based on carbon dioxide stores of a respiratory tract of the subject to the respiratory signal and measured or estimated respiratory data from another breath.

15. The method of claim 14, wherein applying the filter comprises applying a filter comprising an algorithm that employs a transformation coefficient based on functional residual capacity of the respiratory tract.

16. The method of claim 14, wherein applying the filter comprises applying a filter comprising an algorithm that employs a transformation coefficient based on functional residual capacity of the respiratory tract and carbon dioxide in tissues of the respiratory tract.

17. The method of claim 14, wherein applying the filter comprises employing an estimate of at least one of a volume of the carbon dioxide stores of the respiratory tract of the subject and a flow of carbon dioxide into or out of the carbon dioxide stores.

18. The method of claim 14, wherein obtaining the respiratory signal comprises obtaining a carbon dioxide elimination signal from respiration of the subject.

19. The method of claim 18, wherein applying the filter comprises employing the carbon dioxide elimination signal in the following algorithm:

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

1) is carbon dioxide excretion and comprises at least a part of the measured or estimated respiratory data from the another breath, and α

is the transformation coefficient.

20. The method of claim 18, further comprising:

estimating carbon dioxide excretion for the another breath.

21. The method of claim 20, wherein estimating carbon dioxide excretion for the another breath includes accounting for carbon dioxide stores in the respiratory tract of the subject during the another breath.

22. The method of claim 21, wherein accounting for carbon dioxide stores comprises accounting for functional residual capacity during the another breath.

23. The method of claim 21, wherein accounting for carbon dioxide stores comprises accounting for functional residual capacity and carbon dioxide within tissues of the respiratory tract during the another breath.

24. The method of claim 20, wherein estimating carbon dioxide excretion of the another breath includes employing the formula:

{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 another breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the subject during the another 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 subject for the another breath and an immediately preceding breath, and RR is a respiratory rate of the subject.

25. The method of claim 14, further comprising determining an optimal value for the transformation coefficient.

26. The method of claim 25, wherein determining the optimal value comprises at least one of iterative searching, rote searching, gradient searching, use of a set of predetermined equations, and adaptive filtering.

27. The method of claim 25, further comprising, following the act of applying the filter, adjusting the estimate of carbon dioxide excretion of the at least another breath to improve a correlation between the carbon dioxide elimination measurement and an indicator of the content of carbon dioxide in blood of the subject.

28. A respiratory monitoring device configured to optimize the accuracy of a respiratory signal obtained from at least one breath by a subject by accounting for carbon dioxide stores of a respiratory tract of the subject, comprising:

at least one processing element programmed to apply a filter comprising an algorithm that employs a transformation coefficient based on carbon dioxide stores of a respiratory tract of the subject to the respiratory signal and measured or estimated respiratory data from another breath.

29. The respiratory monitoring device of claim 28, wherein the at least one processing element is programmed to apply a filter comprising an algorithm that employs a transformation coefficient based on functional residual capacity of the respiratory tract.

30. The respiratory monitoring device of claim 28, wherein the at least one processing element is programmed to apply a filter comprising an algorithm that employs a transformation coefficient based on functional residual capacity of the respiratory tract and carbon dioxide in tissues of the respiratory tract.

31. The respiratory monitoring device of claim 28, wherein the at least one processing element is programmed to apply a filter comprising an algorithm that comprises an estimate of at least one of a volume of the carbon dioxide stores of the respiratory tract of the subject and a flow of carbon dioxide into or out of the carbon dioxide stores.

32. The respiratory monitoring device of claim 28, further comprising:

at least one sensor for obtaining the respiratory signal.

33. The respiratory monitoring device of claim 32, wherein the at least one sensor is used to obtain a carbon dioxide elimination signal from respiration of the subject.

34. The respiratory monitoring device of claim 33, wherein the at least one processing element is programmed to apply the following algorithm to the carbon dioxide elimination signal:

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

1) is carbon dioxide excretion and comprises at least a part of the measured or estimated respiratory data from the another breath, and α

is the transformation coefficient.

35. The respiratory monitoring device of claim 33, wherein the at least one processing element is also programmed to estimate carbon dioxide excretion for the another breath.

36. The respiratory monitoring device of claim 35, wherein, in estimating carbon dioxide excretion for the another breath, the at least one processing element is programmed to account for carbon dioxide stores in the respiratory tract of the subject during the another breath.

37. The respiratory monitoring device of claim 36, wherein the at least one processing element is programmed to account for carbon dioxide stores comprising functional residual capacity during the another breath.

38. The respiratory monitoring device of claim 37, wherein the at least one processing element is programmed to account for carbon dioxide stores further comprising carbon dioxide within tissues of the respiratory tract during the another breath.

39. The respiratory monitoring device of claim 35, wherein the at least one processing element is programmed to apply formula to the carbon dioxide elimination measurement for the another breath:

{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 another breath, {circumflex over (V)}_A*(n) is an estimate of a volume of the carbon dioxide stores of the respiratory tract of the subject during the another 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 subject for the another breath and an immediately preceding breath, and RR is a respiratory rate of the subject.

40. The respiratory monitoring device of claim 28, wherein the at least one processing element is programmed to determine an optimal value for the transformation coefficient.

41. The respiratory monitoring device of claim 40, wherein the at least one processing element is programmed to conduct at least one of an iterative search, a rote search, a gradient search, a set of predetermined equations, and adaptive filtering to determine the optimal value.

42. The respiratory monitoring device of claim 40, wherein the at least one processing element is programmed to adjust the estimate of carbon dioxide excretion of the at least another breath to improve a correlation between the carbon dioxide elimination measurement and an indicator of the content of carbon dioxide in blood of the subject following application of the filter.