IP Library Granted Patent US 8,529,458
Granted Patent B2
US 8,529,458 · App. 12/891,795 · Granted Sep 10, 2013

Method and apparatus for assessment of fluid responsiveness

Inventors: Sunghan Kim (Los Angeles, CA); Pedro Mateo Riobo Aboy (Portland, OR); James McNames (Portland, OR)
Assignees: State of Oregon by and Through the State Board of Higher Education on Behalf of Portland State University; APDM, Inc.
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Quick Facts
Patent No.
US 8,529,458
App. No.
12/891,795
Granted
Sep 10, 2013
Kind
B2
Abstract

Methods and apparatus for determining a cardiac parameter from cardiovascular pressure signals including arterial blood pressure (ABP) and the photoplethysmographic signal to quantify the degree of amplitude modulation due to respiration and predict fluid responsiveness are disclosed. Disclosed embodiments include a method for assessing fluid responsiveness implemented in a digital computer with one or more processors comprising: (a) measuring a cardiovascular signal, and (b) computing a dynamic index predictive of fluid responsiveness from said cardiovascular signal using a nonlinear state space estimator. According to one particular embodiment, and without limitation, the nonlinear state space estimator is based on a model for cardiovascular signals such as arterial blood pressure or plethysmogram signals, and employs a marginalized particle filter to estimate a dynamic index predictive of fluid responsiveness that is substantially equivalent to a variation in pulse pressure of said cardiovascular signal.

Claims (24)

1. A method for assessing fluid responsiveness comprising:

(a) obtaining a cardiovascular signal; and

(b) computing a dynamic index predictive of fluid responsiveness from said cardiovascular signal using a hardware device with one or more processors configured for implementing a nonlinear state space estimator, said nonlinear state space estimator comprising a state space model wherein a plurality of cardiac harmonics are separately modulated by respiratory fluctuations;

whereby said dynamic index predictive of fluid responsiveness enables a practitioner to assess fluid responsiveness and guide fluid therapy.

2. The method of claim 1 , wherein said cardiovascular signal is an arterial blood pressure signal.

3. The method of claim 1 , wherein said cardiovascular signal is a plethysmographic signal.

4. The method of claim 1 , wherein said dynamic index predictive of fluid responsiveness is a nonlinear function of said cardiovascular signal.

5. The method of claim 4 , wherein said dynamic index predictive of fluid responsiveness is substantially equivalent to a variation in pulse pressure of said cardiovascular signal due to respiration.

6. The method of claim 5 , wherein said nonlinear state space estimator is based on a nonlinear state space model of cardiovascular signals.

7. The method of claim 6 , wherein said nonlinear state space estimator is a computational Bayesian estimator.

8. The method of claim 7 , wherein said computational Bayesian estimator is a sequential Monte Carlo estimator.

9. The method of claim 8 , wherein said sequential Monte Carlo estimator is a marginalized particle filter.

10. The method of claim 9 , wherein said marginalized particle filter is an a-posteriori adaptive marginalized particle filter.

11. An apparatus for assessing fluid responsiveness, comprising:

(a) a measuring unit for measuring a cardiovascular signal; and

(b) a processor configured for computing a dynamic index predictive of fluid responsiveness from said cardiovascular signal using a nonlinear state space estimator, said state space estimator comprising a state space model wherein a plurality of cardiac harmonics are separately modulated by respiratory fluctuations;

whereby said dynamic index predictive of fluid responsiveness enables a practitioner to assess fluid responsiveness and guide fluid therapy.

12. The apparatus of claim 11 , wherein said dynamic index predictive of fluid responsiveness is substantially equivalent to a variation in pulse pressure of said cardiovascular signal due to respiration.

13. The apparatus of claim 12 , wherein said nonlinear state space estimator is based on a nonlinear state space model of said cardiovascular signal.

14. The apparatus of claim 13 , wherein said nonlinear state space estimator is a computational Bayesian estimator.

15. The apparatus of claim 14 , wherein said computational Bayesian estimator is a sequential Monte Carlo estimator.

16. The apparatus of claim 15 , wherein said sequential Monte Carlo estimator is a marginalized particle filter.

17. The apparatus of claim 16 , wherein said marginalized particle filter is an a-posteriori adaptive marginalized particle filter.

18. The apparatus of claim 17 , wherein said marginalized particle filter is adapted to work on a cardiovascular signal from a spontaneously breathing patient.

Assignments (5)
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY PREVIOUSLY RECORDED AT REEL: 53536 FRAME: 581. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Mar 31, 2021
From: APDM, INC.
To: WEARABLES IP HOLDINGS, LLC
Reel/Frame 055882/0174 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNOR PREVIOUSLY RECORDED ON REEL 053508 FRAME 0688. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNOR IS APDM, INC. AND NOT ADPM, INC.. Recorded Aug 19, 2020
From: APDM, INC.
To: WEARABLES IP HOLDINGS, INC.
Reel/Frame 053536/0581 →
CHANGE OF NAME Recorded Aug 17, 2020
From: ADPM, INC.
To: WEARABLES IP HOLDINGS, LLC
Reel/Frame 053508/0688 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 14, 2020
From: PORTLAND STATE UNIVERSITY, AN INSTITUTION OF HIGHER EDUCATION IN THE STATE OF OREGON
To: APDM, INC.
Reel/Frame 054630/0219 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 22, 2011
From: KIM, SUNGHAN; MCNAMES, JAMES; RIOBO ABOY, PEDRO MATEO
To: STATE OF OREGON BY AND THROUGH THE STATE BOARD OF HIGHER EDUCATION ON BEHALF OF PORTLAND STATE UNIVERSITY; APDM, INC.
Reel/Frame 027103/0449 →
Continuity (3)
Provisional Application 61246454 · Sep 28, 2009
Provisional Application 61246456 · Sep 28, 2009
Related Publication 20110077532A1 · Mar 31, 2011