Systems and methods for model-based estimation of cardiac output and total peripheral resistance

• US 8,282,564 B2
• Filed: 05/15/2008
• Issued: 10/09/2012
• Est. Priority Date: 05/16/2007
• Status: Active Grant

• Current Assignee: Massachusetts Institute of Technology
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Parlikar, Tushar A., Ranade, Gireeja V., Heldt, Thomas, Verghese, George C.
• Primary Examiner(s): VIVLEMORE, TRACY ANN
• Application Number:
  US12/121,042
• Publication Number:
  US 20080287812A1
• Time in Patent Office: 1,608 Days
• Field of Search: None
• US Class Current: 600/485
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/029 Measuring or recording blood output from the heart, e.g. minute volume A61B8/065 takes precedence

Abstract

The methods and systems for estimating cardiac output and total peripheral resistance include observing arterial blood pressure waveforms to determine intra-beat and inter-beat variability in arterial blood pressure and estimating from the variability a time constant for a lumped parameter beat-to-beat averaged Windkessel model of the arterial tree. Uncalibrated cardiac output and uncalibrated total peripheral resistance may then be calculated from the time constant. Calibrated cardiac output and calibrated total peripheral resistance may be computed using calibration data, assuming an arterial compliance that is either constant or dependent on mean arterial blood pressure. The parameters of the arterial compliance may be estimated in a least-squares manner.

Claims

1. A method for estimating beat-by-beat cardiovascular parameters and variables, comprising:

processing two or more cycles of arterial blood pressure to determine a mean arterial blood pressure over each cycle beginning at a beat onset time and an inter-beat variability in blood pressure between the two or more cycles; and

computing estimates of one or more cardiovascular parameters and variables from the mean arterial blood pressures, the inter-beat variability, and a beat-to-beat averaged Windkessel model of an arterial tree.

2. The method of claim 1, wherein the one or more cardiovascular parameters and variables include a beat-by-beat time constant of the arterial tree.

3. The method of claim 2, wherein the time constant is estimated over a data window.

4. The method of claim 2, wherein the time constant is estimated through optimization of an error criterion.

5. The method of claim 4, wherein the error criterion is least-squared error.

6. The method of claim 1, wherein the one or more cardiovascular parameters and variables include an uncalibrated beat-by-beat cardiac output.

7. The method of claim 6, further comprising computing calibrated beat-by-beat cardiac output from the uncalibrated beat-by-beat cardiac output using a calibration factor.

8. The method of claim 7, wherein the calibration factor is computed for each of the cycles.

9. The method of claim 7, wherein the calibration factor represents a lumped arterial compliance.

10. The method of claim 9, wherein the lumped arterial compliance is modeled as a function of mean arterial blood pressure.

11. The method of claim 9, wherein the lumped arterial compliance is modeled as a parameterized function of mean arterial blood pressure.

12. The method of claim 9, wherein the lumped arterial compliance is modeled as a two-parameter function of mean arterial blood pressure.

13. The method of claim 9, wherein the lumped arterial compliance is modeled as a constant.

14. The method of claim 11, 12 or 13, wherein a parameter of the lumped arterial compliance is estimated through optimization of an error criterion.

15. The method of claim 14, wherein the error criterion is least-squared error.

16. The method of claim 6, wherein the one or more cardiovascular parameters and variables include an uncalibrated beat-by-beat total peripheral resistance.

17. The method of claim 16, further comprising computing calibrated beat-by-beat total peripheral resistance from a ratio of the time constant to a lumped arterial compliance.

18. The method of claim 16, further comprising computing calibrated beat-by-beat total peripheral resistance from a ratio of mean arterial blood pressure to calibrated cardiac output.

19. The method of claim 16, further comprising computing calibrated beat-by-beat total peripheral resistance from a ratio of mean pressure to a systemic blood flow.

20. The method of claim 19, wherein the systemic blood flow is calculated as the calibrated cardiac output minus the product of lumped arterial compliance with a ratio of beat-to-beat arterial blood pressure change to beat duration.

21. The method of claim 1, wherein the arterial blood pressure is measured at a central artery of a cardiovascular system.

22. The method of claim 1, wherein the arterial blood pressure is measured at a peripheral artery of a cardiovascular system.

23. The method of claim 1, wherein the arterial blood pressure is measured using a noninvasive blood pressure device.

24. The method of claim 23, wherein the arterial blood pressure is measured using a photoplethysmographic blood pressure device.

25. The method of claim 23, wherein the arterial blood pressure is measured using a tonometric blood pressure device.

26. The method of claim 1, wherein processing the two or more cycles of arterial blood pressure includes obtaining a mean blood pressure, a diastolic blood pressure, and a systolic blood pressure for each cycle.

27. The method of claim 1, wherein processing the two or more cycles of arterial blood pressure includes obtaining the beat onset time for each cycle.

28. The method of claim 27, wherein processing the two or more cycles of arterial blood pressure includes computing a beat-to-beat arterial blood pressure change between consecutive beat onset times.

29. The method of claim 28, wherein processing the two or more cycles of arterial blood pressure includes estimating pulse pressure in each cycle as a proportionality constant multiplied by a difference between mean pressure and diastolic pressure in each cycle.

30. The method of claim 29, wherein the proportionality constant in each cycle is fixed.

31. The method of claim 1, wherein processing the two or more cycles of arterial blood pressure includes obtaining a beat duration for each cycle.

32. A system for estimating beat-to-beat cardiac output comprising:

a blood pressure measuring device;

a processor;

a display;

a user interface; and

a memory storing computer executable instructions, which when executed by the processor cause the processor to;

receive two or more cycles of arterial blood pressure from the blood pressure device;

analyze the two or more cycles of arterial blood pressure to determine a mean arterial blood pressure over each cycle beginning at a beat onset time and an inter-beat variability in blood pressure between the two or more cycles;

compute estimates of one or more cardiovascular system parameters and variables from the mean arterial blood pressures, the inter-beat variability, and a beat-to-beat averaged Windkessel model of an arterial tree; and

display the estimates.

33. The system of claim 32, wherein the blood pressure measuring device is a noninvasive blood pressure measuring device.

34. The system of claim 33, wherein the noninvasive blood pressure measuring device is a photoplethysmographic blood pressure measuring device.

35. The system of claim 32, wherein the noninvasive blood pressure measuring device is a tonometric blood pressure measuring device.

36. The system of claim 32, wherein the arterial blood pressure is measured at a central artery of a cardiovascular system.

37. The system of claim 32, wherein the arterial blood pressure is measured at a peripheral artery of a cardiovascular system.

38. The system of claim 32, wherein the one or more cardiovascular parameters and variables include a beat-by-beat time constant of the arterial tree.

39. The system of claim 38, wherein the time constant is estimated over a data window.

40. The system of claim 38, wherein the time constant is estimated through optimization of an error criterion.

41. The system of claim 39, wherein the error criterion is least-squared error.

42. The system of claim 32, wherein the one or more cardiovascular parameters and variables include an uncalibrated beat-by-beat cardiac output.

43. The system of claim 32, further comprising computer executable instructions which, when executed by the processor, cause the processor to compute calibrated beat-by-beat cardiac output from the uncalibrated beat-by-beat cardiac output using a calibration factor.

44. The system of claim 43, further comprising computer executable instructions which, when executed by the processor, cause the processor to compute the calibration factor for each of the cycles.

45. The system of claim 43, wherein the calibration factor represents a lumped arterial compliance.

46. The system of claim 45, wherein the lumped arterial compliance is modeled as a function of mean arterial blood pressure.

47. The system of claim 45, wherein the lumped arterial compliance is modeled as a parameterized function of mean arterial blood pressure.

48. The system of claim 45, wherein the lumped arterial compliance is modeled as a two-parameter function of mean arterial blood pressure.

49. The system of claim 45, wherein the lumped arterial compliance is modeled as a constant.

50. The system of claim 47, 48, or 49, wherein a parameter of the lumped arterial compliance is estimated through optimization of an error criterion.

51. The system of claim 50, wherein the error criterion is least-squared error.

52. The system of claim 32, wherein the one or more cardiovascular parameters and variables include an uncalibrated beat-by-beat total peripheral resistance.

53. The system of claim 52, further comprising computer executable instructions which, when executed by processor, cause the processor to compute calibrated beat-by-beat total peripheral resistance from a ratio of the time constant to a lumped arterial compliance.

54. The system of claim 52, further comprising computer executable instructions which, when executed by the processor, cause the processor to compute calibrated beat-by-beat total peripheral resistance from a ratio of mean arterial blood pressure to calibrated cardiac output.

55. The system of claim 52, further comprising computer executable instructions which, when executed by the processor, cause the processor to compute calibrated beat-by-beat total peripheral resistance from a ratio of mean pressure to a systemic blood flow.

56. The system of claim 55, wherein the systemic blood flow is calibrated cardiac output minus the product of lumped arterial compliance with a ratio of beat-to-beat arterial blood pressure change to beat duration.

57. The system of claim 32, wherein analyzing the two or more cycles of arterial blood pressure includes obtaining a mean blood pressure, a diastolic blood pressure, and a systolic blood pressure for each cycle.

58. The system of claim 32, wherein analyzing the two or more cycles of arterial blood pressure includes obtaining the beat onset time for each cycle.

59. The system of claim 58, wherein analyzing the two or more cycles of arterial blood pressure includes computing a beat-to-beat arterial blood pressure change between consecutive beat onset times.

60. The system of claim 58, wherein analyzing the two or more cycles of arterial blood pressure includes estimating pulse pressure in each cycle as a proportionality constant multiplied by a difference between mean pressure and diastolic pressure in each cycle.

61. The system of claim 60, wherein the proportionality constant in each cycle is fixed.

62. The system of claim 32, wherein analyzing the two or more cycles of arterial blood pressure includes obtaining a beat duration for each cycle.