Apparatus and method for blood pressure pulse waveform contour analysis

• US 6,689,069 B2
• Filed: 05/28/2002
• Issued: 02/10/2004
• Est. Priority Date: 03/20/1998
• Status: Expired due to Fees

• Current Assignee: Hypertension Diagnostics, Inc.
• Original Assignee: Hypertension Diagnostics, Inc.
• Inventors: Bratteli, Christopher W., Morgan, Dennis J., Cohn, Jay N., Finkelstein, Stanley M.
• Primary Examiner(s): NATNITHITHADHA, NAVIN
• Assistant Examiner(s): Astorino, Michael
• Application Number:
  US10/157,551
• Publication Number:
  US 20030023173A1
• Time in Patent Office: 623 Days
• Field of Search: 600/485, 600/481, 600/486, 600/490, 600/492, 600/493, 600/494, 600/495, 600/496, 600/500, 600/502, 128/898
• US Class Current: 600/485
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02108 from analysis of pulse wave characteristics
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: A61B 7/00 Instruments for auscultation
• CPC Class Codes: A61B 7/045 Detection of Korotkoff sounds A61B5/0225 takes precedence; measuring blood pressure A61B5/021

Abstract

Methods and apparatus for processing an arterial blood pressure waveform to extract clinically useful information on the state of the cardiovascular system are disclosed herein. In order to obtain the parameters of the modified Windkessel model, the diastolic portion of a subject'"'"'s blood pressure waveform is scanned over a plurality of ranges and the range that produces the best fit of data and lowest error estimates are selected. In addition, multiple empirically determined starting values of the ‘A’ parameters are used to find the best fit of the model data to the actual arterial blood pressure waveform data.

Claims

1. Apparatus for analyzing measured pulse waveform and for identifying a diastolic portion of a digitized arterial blood pressure waveform comprising a computer programmed to carry out the method of:

analyzing diastolic portions of each of a plurality of individual beats, including;

a) selecting a point representative of the onset of diastole;

b) selecting a point representative of the end of diastole; and

c) fitting a curve to the selected diastolic portions; and

, determining resultant values as a weighted average of the values from the analysis of the analyzed diastolic portions based on their error estimates and quality of curve fit.

2. Apparatus according to claim 1, wherein the a) selecting of the point representative of the end of diastole further includes locating the point where the waveform ceases monotonic decay.

3. The apparatus of claim 1, wherein the a) selecting of the point representative of the onset of diastole further includes

a1) identifying a near-notch region of the waveform around the dicrotic notch; and

a2) selecting a point on the waveform within the near-notch region as the onset of diastole.

4. The apparatus of claim 1, wherein the c) fitting a curve to the selected diastolic portion further includes selecting a plurality of independent models (i.e., final ‘

A’

parameter sets generated from curve fitting) for each of the Windkessel model component based on minimizing the coefficient of variation (CV) of the components'"'"' measures.

5. The apparatus of claim 4, wherein the c) fitting a curve to the selected diastolic portion further includes using a set of empirically determined initial ‘

A’

parameters.

6. The apparatus of claim 4, wherein the analyzing a diastolic portion of each of a plurality of individual beats further includes selecting beats for analysis based on heart rate variability.

7. The apparatus of claim 1, wherein the c) fitting a curve to the selected diastolic portion further includes using a set of empirically determined initial ‘

A’

parameters.

8. The apparatus of claim 1, wherein the analyzing a diastolic portion of each of a plurality of individual beats further includes selecting beats for analysis based on heart rate variability.

9. A computerized method for identifying a diastolic portion of a digitized arterial blood pressure waveform comprising:

analyzing in a diastolic portion of each of a plurality of individual beats, including;

a) selecting a point representative of the onset of diastole;

b) selecting a point representative of the end of diastole; and

c) fitting a curve to the selected diastolic portion; and

determining resultant values as a weight average of the values from the analysis of the analyzed diastolic portions based on their error estimates and quality of curve fit.

10. The method of claim 9, wherein the a) selecting of the point representative of the onset of diastole further includes

a1) identifying a near-notch region of the waveform around the dicrotic notch;

a2) selecting a point on the waveform within the near-notch region as the onset of diastole.

11. The method of claim 9, wherein the a) selecting of the point representative of the end of diastole further includes locating the point where the waveform ceases monotonic decay.

12. The method of claim 9, wherein the a) selecting of the point representative of the onset of diastole further includes

a1) identifying a near-notch region of the waveform around the dicrotic notch;

and

a2) selecting a point on the waveform within the near-notch region as the onset of diastole.

13. The method of claim 9, wherein the c) fitting a curve to the selected diastolic portion further includes selecting a plurality of independent models (i.e., final ‘

A’

parameter sets generated from curve fitting) for each of the Windkessel model component based on minimizing the coefficient of variation (CV) of the components'"'"' measures.

14. The method of claim 13, wherein the c) fitting a curve to the selected diastolic portion further includes using a set of empirically determined initial ‘

A’

parameters.

15. The method of claim 13, wherein the analyzing a diastolic portion of each of a plurality of individual beats further includes selecting beats for analysis based on heart rate variability.

16. The method of claim 9, wherein the c) fitting a curve to the selected diastolic portion further includes using a set of empirically determined initial ‘

A’

parameters.

17. The method of claim 9, wherein the analyzing a diastolic portion of each of a plurality of individual beats further includes selecting beats for analysis based on heart rate variability.