Systems And Methods For Processing Oximetry Signals Using Least Median Squares Techniques

• US 20110098933A1
• Filed: 10/26/2009
• Published: 04/28/2011
• Est. Priority Date: 10/26/2009
• Status: Abandoned Application

• Current Assignee: Nellcor Puritan Bennett Ireland
• Original Assignee: Nellcor Puritan Bennett Ireland
• Inventors: Ochs, James
• Application Number:
  US12/605,739
• Publication Number:
  US 20110098933A1
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 2218/08 Feature extraction

Abstract

Methods and systems are disclosed for determining information from a signal using least median squares techniques, including determining blood oxygen saturation measurements based at least in part on photoplethysmograph signals. In an embodiment, a Lissajous figure is generated based on multiple measurements and least median squares techniques may be used for one or more of: determining information, assessing measurement confidence, filtering measurements, and choosing a regression analysis technique.

Claims

1. A method for determining information from a signal, comprising:

receiving, from a first sensor, a first electronic signal;

receiving, from a second sensor, a second electronic signal;

using processor equipment for;

generating a Lissajous figure based at least in part on the first and second electronic signals,

determining information from at least the Lissajous figure based at least in part on a least median squares technique; and

outputting the information to an output device.

2. The method of claim 1, wherein the first electronic signal is a first photoplethysmograph signal and the second electronic signal is a second photoplethysmograph signal.

3. The method of claim 1, wherein the information is a blood oxygen saturation measurement.

4. The method of claim 1, wherein the least median squares technique comprises determining a least median squares regression line within the Lissajous figure.

5. The method of claim 1, wherein the least median squares technique comprises generating an error curve using a median squares error metric.

6. The method of claim 5, wherein the least median squares technique comprises generating a combined error curve by combining a plurality of error curves.

7. The method of claim 5, wherein the least median squares technique comprises determining a confidence based at least in part on the error curve.

8. The method of claim 1, wherein the least median squares technique comprises:

determining a noise characteristic; and

performing one of a plurality of regression analyses based at least in part on the noise characteristic, wherein one of the plurality of regression analyses is a least median squares regression.

9. A system for determining information from a signal, comprising:

processing equipment capable of

receiving, from a first sensor, a first electronic signal,

receiving, from a second sensor, a second electronic signal,

generating a Lissajous figure based at least in part on the first and second electronic signals, and

determining information from at least the Lissajous figure based at least in part on a least median squares technique; and

an output device, communicatively coupled to the processing equipment, for outputting the information.

10. The system of claim 9, wherein the first electronic signal is a first photoplethysmograph signal and the second electronic signal is a second photoplethysmograph signal.

11. The system of claim 9, wherein the information is a blood oxygen saturation measurement.

12. The system of claim 9, wherein the least median squares technique comprises determining a least median squares regression line within the Lissajous figure.

13. The system of claim 9, wherein the least median squares technique comprises generating an error curve using a median squares error metric.

14. The system of claim 13, wherein the least median squares technique comprises generating a combined error curve by combining a plurality of error curves.

15. The system of claim 13, wherein the least median squares technique comprises determining a confidence based at least in part on the error curve.

16. The system of claim 9, wherein the least median squares technique comprises:

determining a noise characteristic; and

performing one of a plurality of regression analyses based at least in part on the noise characteristic, wherein one of the plurality of regression analyses is a least median squares regression.

17. Computer-readable medium for use in determining information from a signal, the computer-readable medium having computer program instructions recorded thereon for:

receiving, from a first sensor, a first electronic signal;

receiving, from a second sensor, a second electronic signal;

generating a Lissajous figure based at least in part on the first and second electronic signals;

determining information from at least the Lissajous figure based at least in part on a least median squares technique; and

outputting the information to an output device.

18. The computer-readable medium of claim 17, wherein the first electronic signal is a first photoplethysmograph signal and the second electronic signal is a second photoplethysmograph signal.

19. The computer-readable medium of claim 17, wherein the information is a blood oxygen saturation measurement.

20. The computer-readable medium of claim 17, wherein the least median squares technique comprises determining a least median squares regression line within the Lissajous figure.