SYSTEMS AND METHODS FOR ANALYZING A PHYSIOLOGICAL SENSOR SIGNAL

• US 20130079601A1
• Filed: 09/23/2011
• Published: 03/28/2013
• Est. Priority Date: 09/23/2011
• Status: Active Grant

• Current Assignee: Nellcor Puritan Bennett Ireland
• Original Assignee: Nellcor Puritan Bennett Ireland
• Inventors: Addison, Paul S., Watson, James
• Granted Patent: US 9,770,210 B2
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence

Abstract

The present disclosure relates generally to patient monitoring systems and, more particularly, to signal analysis for patient monitoring systems. In one embodiment, a method of analyzing a detector signal of a physiological patient sensor includes obtaining the detector signal from the physiological patient sensor, wherein the detector signal crosses a horizontal boundary more than once. The method also includes determining the relative time and the slope of the detector signal at each boundary crossing. The method further includes estimating the amplitude of the detector signal based, at least in part, on the determined relative time and slope of the detector signal at each boundary crossing. The method also includes determining a physiological parameter of a patient based, at least in part, on the estimate of the amplitude of the detector signal.

Claims

1. A method for analyzing a detector signal of a physiological patient sensor, comprising:

obtaining the detector signal from the physiological patient sensor, wherein the detector signal crosses a horizontal boundary more than once;

determining the relative time and the slope of the detector signal at each boundary crossing;

estimating the amplitude of the detector signal based, at least in part, on the determined relative time and slope of the detector signal at each boundary crossing; and

determining a physiological parameter of a patient based, at least in part, on the estimate of the amplitude of the detector signal.

2. The method of claim 1, wherein the horizontal boundary is a zero boundary.

3. The method of claim 1, wherein determining the relative time of the detector signal at each boundary crossing comprises determining the periodicity or the frequency of the boundary crossings.

4. The method of claim 1, wherein determining the slope of the detector signal at each boundary crossing comprises determining the derivative of the detector signal at each boundary crossing.

5. The method of claim 1, wherein estimating the amplitude of the detector signal comprises multiplying values of the determined slopes of the detector signal at two adjacent boundary crossings by the determined relative time between the two adjacent boundary crossings.

6. The method of claim 1, wherein estimating the amplitude of the detector signal comprises estimating the amplitude of the detector signal using a probabilistic or stochastic method comprising non-parametric Bayesian estimates, neural networks, or any combination thereof.

7. The method of claim 1, wherein estimating the amplitude of the detector signal comprises estimating the amplitude of the detector signal using an adaptive rule-based system comprising propositional or predicate calculus, Modal, non-monotonic, or fuzzy logic, or any combination thereof.

8. The method of claim 1, wherein determining a physiological parameter of a patient comprises determining a pulse rate, oxygen saturation, hydration level, or any combination thereof.

9. A method for analyzing a detector signal of a physiological patient sensor, comprising:

obtaining the detector signal from the physiological patient sensor, wherein the detector signal crosses a horizontal boundary a plurality of times;

determining a period of the detector signal;

determining a gradient of the detector signal at each boundary crossing; and

determining a quality estimate for the detector signal based, at least in part, on the determined period of the detector signal and the determined gradient of the detector signal at each boundary crossing.

10. The method of claim 9, comprising comparing the determined quality estimate to a threshold value.

11. The method of claim 10, comprising discarding the detector signal or using the detector signal in a weighted calculation when the determined quality estimate is less than the threshold value.

12. The method of claim 10, comprising calculating a value for a physiological parameter of a patient when the determined quality estimate is greater than or equal to the threshold value.

13. The method of claim 12, comprising determining an estimate of the amplitude of the detector signal based, at least in part on, the determined period of the detector signal and the determined gradient of the detector signal at each boundary crossing.

14. The method of claim 13, wherein calculating the value for the physiological parameter of the patient comprises calculating the value for the physiological parameter of the patient based, at least in part, on the determined estimate of the amplitude of the detector signal.

15. The method of claim 9, wherein determining the quality estimate of the detector signal comprises using a probabilistic or stochastic method comprising non-parametric Bayesian estimates, neural networks, or any combination thereof.

16. The method of claim 9, wherein determining the quality estimate of the detector signal comprises using an adaptive rule-based system comprising propositional or predicate calculus, Modal, non-monotonic, or fuzzy logic, or any combination thereof.

17. A patient monitoring system, comprising:

a patient monitor comprising a processor configured to;

receive a detector signal from a physiological sensor;

locate a portion of the detector signal between two adjacent intersections of the detector signal and a horizontal axis;

determine an amount of time between the two intersections;

determine a gradient for the detector signal at the two intersections; and

estimate the amplitude of the portion of the detector signal between the two intersections based, at least in part, on the determined amount of time between the two intersections and the determined gradients for the detector signal at the two intersections.

18. The system of claim 17, wherein the processor is configured to estimate the amplitude of the portion of the detector signal by multiplying mean, absolute values of the determined gradients of the two intersections by the amount of time between the two intersections.

19. The system of claim 17, wherein estimating the amplitude of the detector signal comprises estimating the amplitude of the detector signal using a probabilistic or stochastic method comprising non-parametric Bayesian estimates, neural networks, or any combination thereof.

20. The system of claim 17, wherein estimating the amplitude of the detector signal comprises estimating the amplitude of the detector signal using an adaptive rule-based system comprising propositional or predicate calculus, Modal, non-monotonic, or fuzzy logic, or any combination thereof.