Reliable noninvasive measurement of blood gases

• US 5,355,880 A
• Filed: 07/06/1992
• Issued: 10/18/1994
• Est. Priority Date: 07/06/1992
• Status: Expired due to Term

• Current Assignee: Sandia Corporation (Martin Marietta Corporation)
• Original Assignee: Sandia Corporation (Martin Marietta Corporation)
• Inventors: Alam, Mary K., Haaland, David M., Thomas, Edward V., Robinson, Mark R.
• Primary Examiner(s): Sykes, Angela D.
• Application Number:
  US07/910,004
• Time in Patent Office: 834 Days
• Field of Search: 128/633.4, 128/664.7, 128/635, 128/637, 356/39-41, 436/68
• US Class Current: 600/326
• CPC Class Codes: A61B 2503/40 Animals
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/14539 for measuring pH
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/1491 Heated applicators
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/416 the spleen
• CPC Class Codes: A61B 5/6826 Finger
• CPC Class Codes: A61B 5/6838 Clamps or clips
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

Methods and apparatus for, preferably, determining noninvasively and in vivo at least two of the five blood gas parameters (i.e., pH, PCO₂, [HCO₃^- ], PO₂, and O₂ sat.) in a human. The non-invasive method includes the steps of: generating light at three or more different wavelengths in the range of 500 nm to 2500 nm; irradiating blood containing tissue; measuring the intensities of the wavelengths emerging from the blood containing tissue to obtain a set of at least three spectral intensities v. wavelengths; and determining the unknown values of at least two of pH, [HCO₃^- ], PCO₂ and a measure of oxygen concentration. The determined values are within the physiological ranges observed in blood containing tissue. The method also includes the steps of providing calibration samples, determining if the spectral intensities v. wavelengths from the tissue represents an outlier, and determining if any of the calibration samples represents an outlier. The determination of the unknown values is performed by at least one multivariate algorithm using two or more variables and at least one calibration model. Preferably, there is a separate calibration for each blood gas parameter being determined. The method can be utilized in a pulse mode and can also be used invasively. The apparatus includes a tissue positioning device, a source, at least one detector, electronics, a microprocessor, memory, and apparatus for indicating the determined values.

Claims

1. A method of determining non-invasively and in vivo at least two blood gas parameters in a human, said method comprising steps of:

a. generating light at three or more different wavelengths, said wavelengths being in the range of 500 nm to 2500 nm;

b. irradiating in vivo and non-invasively blood containing tissue with said wavelengths, so that there is differential attenuation of at least some intensities of said wavelengths, said wavelength dependent differential attenuation being a function of said blood containing tissue and the direct and indirect spectral influences resulting from the unknown values of pH, HCO₃^-, PCO₂, PO₂ and O₂ saturation in said blood containing tissue;

c. measuring said intensities of said wavelengths emerging from said blood containing tissue to obtain a set of at least three spectral intensities v. wavelengths; and

d. determining said unknown values of at least two of pH, HCO₃^-, PCO₂, and a measure of oxygen concentration in said blood containing tissue from said intensities emerging from said blood containing tissue, said values being within the physiological ranges observed in blood containing tissue.

2. The method as set forth in claim 1, further including the step of determining whether said set of spectral intensities v. wavelengths from said blood containing tissue is an outlier by comparing said set of spectral intensities v. wavelengths from said blood containing tissue with a set of spectral intensities v. wavelengths obtained from irradiating calibration samples.

3. The method as set forth in claim 2, wherein said step of determining whether said set of spectral intensities v. wavelengths from said blood containing tissue represents an outlier is specific for each of said unknown blood gas parameters being measured.

4. The method as set forth in claim 2, wherein said determination of whether said set of spectral intensities v. wavelengths from said blood containing tissue represents an outlier includes the step of comparing said set of spectral intensities v. wavelengths from said blood containing tissue to said set of spectral intensities v. wavelengths from said calibration samples, to determine a measure of the magnitude of the difference between said set of spectral intensities v. wavelengths from said blood containing tissue and said set of spectral intensities v. wavelengths from said calibration samples.

5. The method as set forth in claim 4, wherein a statistical test is used to indicate the probability of said magnitude being caused by random chance, further including the step of classifying said set of spectral intensities v. wavelengths from said blood containing tissue as representing an outlier when said probability is determined to be too low.

6. The method as set forth in claim 1, further including the steps of providing calibration samples and determining whether any of said calibration samples represents an outlier.

7. The method as set forth in claim 1, further including the step of pretreatment of said set of spectral intensities v. wavelengths from said blood containing tissue.

8. The method as set forth in claim 7, wherein said pretreatment includes trimming, wavelength selection, centering, scaling, normalizing, taking first or higher order derivatives, smoothing, Fourier transforming, linearization and transformation.

9. The method as set forth in claim 1, wherein said step of determining said unknown values is performed by a multivariate algorithm using 2 or more variables and at least one calibration model, said calibration model being a function of conventionally measured blood gas parameters obtained from calibration samples and a set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with 3 or more wavelengths of light in the range of 500-2500 nm.

10. The method as set forth in claim 9, wherein said algorithm is selected from the group including PLS, PLS2, PCR, CLS, Q-matrix, ridge regression, cross-correlation, Kalman filtering, MLR, neural networks, and continuum methods.

11. The method as set forth in claim 10, wherein said multivariate algorithm is capable of utilizing more discrete spectral intensities per sample than the number of calibration samples.

12. The method as set forth in claim 11, wherein said algorithm can construct models which approximate mathematical nonlinearities.

13. The method as set forth in claim 11, wherein said algorithm can explicitly model mathematical nonlinearities.

14. The method as set forth in claim 1, wherein said determination of said unknown values is accomplished by utilizing at least two algorithms and at least two calibration models, said calibration models being a function of conventionally measured blood gas parameters obtained from calibration samples and at least one set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with 3 or more wavelengths of light in the range of 500-2500 nm.

15. The method as set forth in claim 14, wherein both of said algorithms are multivariate algorithms and wherein each of said algorithms is capable of utilizing more discrete spectral intensities per sample than the number of said calibration samples.

16. The method as set forth in claim 1, further including the step of providing separate calibration models for each of said unknown values of each blood gas parameter being determined.

17. The method as set forth in claim 1, wherein said unknown values for all 5 blood gas parameters are determined.

18. The method as set forth in claim 1 wherein one of said unknown values of pH, HCO₃^- and PCO₂, is determined with the use of the Henderson-Hasselbach equation.

19. The method as set forth in claim 1, further including the step of transmitting said wavelengths to said blood containing tissue via fiber optics.

20. The method as set forth in claim 19, further including the step of transmitting said wavelengths from said blood containing tissue via fiber optics.

21. A method of determining invasively and in vivo at least two blood gas parameters in human blood, said method comprising steps of:

a. generating light at three or more different wavelengths, said wavelengths being in the visible and infrared region;

b. irradiating blood with said wavelengths, so that there is differential attenuation of at least some intensities of said wavelengths, said wavelength dependent differential attenuation being a function of the direct and indirect influences resulting from the unknown values of pH, HCO₃^-, PCO₂, PO₂ and O₂ sat. in said blood;

c. measuring said intensities of said wavelengths from said blood to obtain a set of at least three spectral intensities v. wavelengths; and

d. determining said values of at least two of pH, HCO₃^-, PCO₂, and a measure of oxygen concentration in said blood from said intensities emerging from said blood, said values being within the ranges observed in blood.

22. The method as set forth in claim 21, further including the step of determining whether said set of spectral intensities v. wavelengths from said blood represents an outlier by comparing said set of spectral intensities v. wavelengths from said blood with a set of intensities v. wavelengths obtained from irradiating calibration samples.

23. The method as set forth in claim 21, further including the steps of providing calibration samples and determining whether any of said calibration samples represents an outlier.

24. The method as set forth in claim 21, wherein the step of determining said unknown values is performed by a multivariate algorithm using 2 or more variables and at least one calibration model, said calibration model being a function of conventionally measured blood gas parameters obtained from calibration samples and a set of intensities v. wavelengths obtained from irradiating said calibration samples with 3 or more wavelengths of light in the visible and infrared.

25. The method as set forth in claim 21, wherein said determining of said unknown values is accomplished by utilizing at least two algorithms and at least two calibration models, said calibration models being a function of conventionally measured blood gas parameters obtained from calibration samples and at least one set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with 3 or more wavelengths of light in the visible and infrared.

26. The method as set forth in claim 25, wherein both of said algorithms are multivariate algorithms and wherein each of said algorithms is capable of utilizing more discrete spectral intensities per sample than the number of said calibration samples.

27. A method of determining non-invasively and in vivo at least one of pH, HCO₃^-, and PCO₂ in a human, said method comprising steps of:

a. generating light at two or more different wavelengths, said wavelengths being in the range of 500 nm to 2500 nm;

b. irradiating in vivo and non-invasively blood containing tissue with said wavelengths so that there is differential attenuation of at least some intensities of said wavelengths, said wavelength dependent differential attenuation being a function of said blood containing tissue and the unknown values of pH, HCO₃^- and PCO₂ in said blood containing tissue;

c. measuring said intensities of said wavelengths emerging from said blood containing tissue to obtain a set of at least two spectral intensities v. wavelengths;

d. generating at least one calibration model, said model being a function of conventionally measured values of at least one of pH, HCO₃^- and PCO₂, obtained from calibration samples and spectral intensities v. wavelengths obtained from irradiating said calibration samples with two or more different wavelengths of light, said wavelengths being in the range of 500 nm to 2500 nm; and

e. determining said value of at least one of pH, HCO₃^- and PCO₂ from said intensities emerging from said blood containing tissue utilizing at least one algorithm and said at least one calibration model.

28. The method as set forth in claim 27 wherein said parameter is pH.

29. The method as set forth in claim 27 wherein said parameter is HCO₃.

30. The method as set forth in claim 27 wherein said parameter is PCO₂.

31. A method of determining non-invasively and in vivo two or more blood gas parameters in arterial blood in a human, said method comprising steps of:

a. generating light at three or more different wavelengths, said wavelengths being in the range of 500 nm to 2500 nm;

b. irradiating in vivo and non-invasively blood containing tissue with said wavelengths, so that there is differential attenuation of at least some intensities of said wavelengths, said wavelength dependent differential attenuation being a function of said blood containing tissue and the direct and indirect spectral influences resulting from the unknown values of pH, HCO₃^-, PCO₂, PO₂ and O₂ sat. in said arterial blood;

c. measuring said intensities of said wavelengths emerging from said blood containing tissue during the diastolic portion of the cardiac cycle of said human to obtain a diastolic set of at least three spectral intensities v. wavelengths;

d. measuring said intensities of said wavelengths emerging from said blood containing tissue during the systolic portion of said cardiac cycle to obtain a systolic set of at least three spectral intensities v. wavelengths;

e. determining the measure of change between said diastolic and systolic sets of spectral intensities v. wavelengths; and

f. determining said unknown values of at least two of pH, HCO₃^-, PCO₂, and a measure of oxygen concentration in said arterial blood from said measure of change between said diastolic and systolic sets of spectral intensities v. wavelengths, said values being within the ranges observed in arterial blood.

32. The method as set forth in claim 31, further including the step of determining whether said set of spectral intensities v. wavelengths from said blood containing tissue represents an outlier by comparing said set of spectral intensities v. wavelengths from said blood containing tissue with a set of spectral intensities v. wavelengths obtained from radiating calibration samples.

33. The method as set forth in claim 32, wherein said step of determining whether said set of spectral intensities v. wavelengths from said blood containing tissue represents an outlier is specific for each of said unknown blood gas parameters being measured.

34. The method as set forth in claim 32, wherein said determination of whether said set of spectral intensities v. wavelengths from said blood containing tissue represents an outlier includes the step of comparing said set of spectral intensities v. wavelengths from said blood containing tissue to said set of spectral intensities v. wavelengths from said calibration samples, to determine a measure of the magnitude of the difference between said set of spectral intensities v. wavelengths from said blood containing tissue and said set of intensities v. wavelengths from said calibration samples.

35. The method as set forth in claim 34, wherein a statistical test is used to indicate the probability of said magnitude being caused by random chance, further including the step of classifying said set of spectral intensities v. wavelengths from said blood containing tissue as representing an outlier when said probability is determined to be too low.

36. The method as set forth in claim 31, further including the step of providing calibration samples and determining whether any of said calibration samples represents an outlier.

37. The method as set forth in claim 31, further including the step of pretreatment of said set of spectral intensities v. wavelengths from said blood containing tissue.

38. The method as set forth in claim 37, wherein said pretreatment includes trimming, wavelength selection, centering, scaling, normalizing, taking first or higher order derivatives, smoothing, Fourier transforming, linearization and transformation.

39. The method as set forth in claim 31, wherein said step of determining said unknown values is performed by a multivariate algorithm using 2 or more variables and at least one calibration model, said calibration model being a function of conventionally measured blood gas parameters obtained from calibration samples and a set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with 3 or more wavelengths of light in the range of 500-2500 nm.

40. The method as set forth in claim 39, wherein said algorithm is selected from the group including PLS, PLS2, PCR, CLS, Q-matrix, ridge regression, cross-correlation, Kalman filtering, MLR, neural networks, and continuum methods.

41. The method as set forth in claim 40, wherein said multivariate algorithm is capable of utilizing more discrete spectral intensities per sample than the number of calibration samples.

42. The method as set forth in claim 41, wherein said algorithm can construct models which approximate mathematical nonlinearities.

43. The method as set forth in claim 41, wherein said algorithm can explicitly model mathematical nonlinearities.

44. The method as set forth in claim 31, wherein said determining of said unknown values is accomplished by utilizing at least two algorithms and at least two calibration models, said calibration models being a function of conventionally measured blood gas parameters obtained from calibration samples and at least one set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with 3 or more wavelengths of light in the range of 500-2500 nm.

45. The method as set forth in claim 44, wherein both of said algorithms are multivariate algorithms and wherein each of said algorithms is capable of utilizing more discrete spectral intensities per sample than the number of said calibration samples.

46. The method as set forth in claim 31, further including the step of providing separate calibration models for each blood gas parameter being determined.

47. The method as set forth in claim 31, wherein said unknown values for all 5 blood gas parameters are determined.

48. The method as set forth in claim 31, wherein one of said unknown values of pH, and PCO₂ is determined with the use of the Henderson-Hasselbach equation.

49. A quantitative analysis instrument for noninvasive measurement of blood gas parameters present in blood containing tissue in a human, said instrument comprising:

a. a device for positioning said blood containing tissue;

b. a source of at least three different wavelengths of light positioned relative to said tissue positioning device, to direct light into said blood containing tissue, said wavelengths being in the range of 500 to 2500 nm;

c. at least one detector positioned relative to said tissue positioning device for measuring the spectral intensities of at least a portion of said light emerging from said blood containing tissue at, at least, three wavelengths of said light;

d. electronics, a microprocessor and memory means for processing said measured spectral intensities to determine at least two of pH, PCO₂, HCO₃^-, and a measure of oxygen saturation at values within the physiological ranges observed in said blood containing tissue; and

e. means for indicating said determined values of said blood gas parameters.

50. The analysis instrument of claim 49, further including a first optical means for introducing said light on one side of said tissue and further including a second optical means on the other side of said tissue for directing said light emerging from said blood containing tissue to said detector.

51. The analysis instrument of claim 49, further including at least one optical means positioned on one side of said blood containing tissue for introducing said light into said tissue and for directing said light emerging from said one side of said blood containing tissue to said detector.

52. A quantitative analysis instrument for noninvasive measurement of blood gas parameters present in blood containing tissue in a human, said instrument comprising:

a. a device for positioning said blood containing tissue;

b. a source of at least three different wavelengths of light positioned relative to said tissue positioning device to direct light into said blood containing tissue, said wavelengths being in the range of 500 to 2500 nm;

c. at least one detector positioned relative to said tissue positioning device for measuring the spectral intensities of at least a portion of said light emerging from said blood containing tissue at, at least, three wavelengths of said light;

d. electronics, a microprocessor and memory means including a multivariate algorithm and a calibration model for processing said measured spectral intensities to determine at least two of pH, PCO₂, HCO₃^-, and a measure of oxygen saturation at values within the physiological ranges observed in said blood containing tissue, said algorithm using at least two variables, said model being a function of conventionally measured blood gas parameters obtained from calibration samples and a set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with at least three wavelengths of light in the range of 500-2500 nm; and

e. means for indicating said determined values of said blood gas parameters.

53. The analysis instrument of claim 52, wherein said algorithm is selected from the group including PLS, PLS2, PCR, CLS, Q-matrix, ridge regression, cross-correlation, Kalman filtering, MLR, neural networks, and continuum methods.

54. A quantitative analysis instrument for noninvasive measurement of blood gas parameters present in blood containing tissue of a human, said instrument comprising:

a. a device for positioning said blood containing tissue;

b. a source of at least three different wavelengths of light positioned relative to said tissue positioning device, to direct light into said blood containing tissue, said wavelengths being in the range of 500 to 2500 nm;

c. at least one detector positioned relative to said tissue positioning device for measuring the spectral intensities of at least a portion of said light emerging from said blood containing tissue at, at least, three wavelengths of said light;

d. electronics, a microprocessor and memory means including a multivariate algorithm and a calibration model for processing said measured spectral intensities to determine at least two of pH, PCO₂, HCO₃^-, and a measure of oxygen saturation at values being within the physiological ranges observed in said blood containing tissue, said algorithm using at least two variables, said algorithm being capable of utilizing more discrete spectral intensities per sample than the number of calibration samples used to generate said model, said model being a function of conventionally measured blood gas parameters obtained from said calibration samples and a set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with at least three wavelengths of light in the range of 500-2500 nm; and

e. means for indicating said determined values of said blood gas parameters.

55. A quantitative analysis instrument for noninvasive measurement of two or more blood gas parameters present in blood containing tissue of a human, said instrument comprising:

a. a device for positioning said blood containing tissue;

b. a source of at least three different wavelengths of light positioned relative to said tissue positioning device, to direct light into said blood containing tissue, said wavelengths being in the range of 500 to 2500 nm;

c. at least one detector positioned relative to said tissue positioning device for measuring the spectral intensities of at least three wavelengths of said light emerging from said blood containing tissue during the diastolic portion of the cardiac cycle of said human, to obtain a diastolic set of spectral intensities v. wavelengths, and for measuring the spectral intensities of at least three wavelengths of said light emerging from said blood containing tissue during the systolic portion of the cardiac cycle of said human, to obtain a systolic set of spectral intensities v. wavelengths;

d. memory means for storing said diastolic set of spectral intensities v. wavelengths and said systolic set of spectral intensities v. wavelengths;

e. electronics, a microprocessor and said memory means for processing said diastolic and systolic sets of spectral intensities to determine a measure of change between said diastolic and systolic sets, to obtain a blood specific set of spectral intensities v. wavelengths, said memory means including a multivariate algorithm and a multivariate calibration model, said electronics, said microprocessor and said memory means processing said blood specific set of spectral intensities v. wavelengths to determine at least two of pH, PCO₂, HCO₃^-, and a measure of oxygen saturation at values within the physiological ranges observed in said blood, said algorithm using at least two variables, said model being a function of conventionally measured blood gas parameters obtained from calibration samples and a set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with at least three wavelengths of light in the range of 500-2500 nm; and

f. means for indicating said determined values of said blood gas parameters.

56. The analysis instrument of claim 55, wherein said algorithm is selected from the group including PLS, PLS2, PCR, CLS, Q-matrix, ridge regression, cross-correlation, Kalman filtering, MLR, neural networks, and continuum methods.

57. The analysis instrument of claim 56, wherein said algorithm is capable of utilizing more discrete spectral intensities per sample than the number of calibration samples used to generate said model.

58. The analysis instrument of claim 55, further including a first optical means for introducing said light on one side of said tissue and further including a second optical means on the other side of said tissue for directing said light emerging from said blood containing tissue to said detector.

59. The analysis instrument of claim 55, further including at least one optical means positioned on one side of said blood containing tissue for introducing said light into said tissue and for directing said light emerging from said one side of said blood containing tissue to said detector.

60. The analysis instrument as set forth in claim 55, wherein said electronics, said microprocessor and said memory means including said algorithm and said calibration model for processing said spectral intensities includes means to determine all four of pH, PCO₂, HCO₃^-, and a measure of oxygen saturation at values being within the physiological ranges observed in said blood containing tissue.

61. A quantitative analysis instrument for invasive and in vivo measurement of blood gas parameters present in blood in human, said instrument comprising:

a. a source of at least three different wavelengths of light optically coupled to said blood to direct light into said blood, said wavelengths being in the visible, near infrared, and infrared regions of the spectrum;

b. at least one detector optically coupled to said blood for measuring the spectral intensities of at least a portion of said light emerging from said blood at, at least, three wavelengths of light;

c. electronics, a microprocessor and memory means for processing said spectral intensities to determine at least two of pH, PCO₂, HCO₃^-, and a measure of oxygen saturation at values being within the physiological ranges observed in said blood; and

d. means for indicating said determined values of said blood gas parameters.

62. A quantitative analysis instrument for invasive and in vivo measurement of blood gas parameters present in blood in a human, comprising:

a. a source of at least three different wavelengths of light optically coupled to said blood to direct light into said blood, said wavelengths being in the visible, near infrared, and infrared regions of the spectrum;

b. at least one detector optically coupled to said blood for measuring the spectral intensities of at least a portion of said light emerging from said blood at, at least, three wavelengths of light;

c. electronics, a microprocessor and memory means, said memory means including a multivariate algorithm and a multivariate calibration model, for processing said spectral intensities to determine at least two of pH, PCO₂, HCO₃^-, and a measure of oxygen saturation at values within the physiological ranges observed in said blood, said algorithm using at least two variables, said algorithm being capable of utilizing more discrete spectral intensities per sample than the number of calibration samples used to generate said model, said model being a function of conventionally measured blood gas parameters obtained from said calibration samples and a set of spectral intensities v. wavelengths obtained from irradiating said calibration samples with at least three wavelengths of light in the visible, near infrared, and infrared regions of the spectrum; and

d. means for indicating said determined values of said blood gas parameters.