METHOD FOR DATA REDUCTION AND CALIBRATION OF AN OCT-BASED PHYSIOLOGICAL MONITOR

• US 20130060108A1
• Filed: 11/02/2012
• Published: 03/07/2013
• Est. Priority Date: 08/11/2004
• Status: Active Grant

• Current Assignee: Masimo Corporation
• Original Assignee: GLT Acquisition Corporation
• Inventors: Schurman, Matthew J., Shakespeare, Walter J., Bennett, William Henry
• Granted Patent: US 9,078,560 B2
• Time in Patent Office: Days
• US Class Current: 600/316
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 5/0066 Optical coherence imaging
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/1545 comprising means for indicating vein or arterial entry
• CPC Class Codes: A61B 5/441 Skin evaluation, e.g. for skin disorder diagnosis
• CPC Class Codes: A61B 5/72 Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence

Abstract

The present invention relates to a method and system for estimating blood analyte levels using a noninvasive optical coherence tomography (OCT) based physiological monitor. An algorithm correlates OCT-based estimated blood analyte data with actual blood analyte data determined by other methods, such as invasively. OCT-based data is fit to the obtained blood analyte measurements to achieve the best correlation. Once the algorithm has generated sets of estimated blood analyte levels, it may refine the number of sets by applying one or more mathematical filters. The OCT-based physiological monitor can be calibrated using an Intensity Difference plot or the Pearson Product Moment Correlation method.

Claims

1. A method for generating calibrating data for an optical coherence tomography (OCT) device, the method comprising:

computing intensity differences between at least two OCT scans of biological tissue to generate an intensity difference plot;

selecting, based on the intensity difference plot, portions of the at least two OCT scans correlating with at least two blood analyte measurements, the at least two blood analyte measurements obtained independently from the at least two OCT scans; and

generating, using a processor, calibration data for an OCT device based in part on the selected portions of the OCT scans.

2. The method of claim 1, further comprising:

using the calibration data to calibrate subsequent OCT scans; and

estimating blood analyte concentrations from the subsequent OCT scans.

3. The method of claim 1, wherein the at least two blood analyte measurements differ in concentration values by at least about 40 mg/dL.

4. The method of claim 1, wherein said selecting, based on the intensity difference plot, the portion of each of the OCT scans comprises identifying regions of the OCT scans that have large changes in intensity.

5. The method of claim 1, wherein said selecting, based on the intensity difference plot, the portion of each of the OCT scans comprises identifying regions where intensity differences correlate with blood analyte level changes.

6. The method of claim 1, wherein said selecting, based on the intensity difference plot, the portion of each of the OCT scans comprises identifying regions where intensity differences correlate with blood vessels.

7. The method of claim 1, wherein said selecting, based on the intensity difference plot, the portion of each of the OCT scans comprises using data of the intensity difference plot corresponding to a peak-to-valley pattern to obtain the selected portion and the selected depth of the OCT scans.

8. The method of claim 1, wherein said selecting, based on the intensity difference plot, the portion of each of the OCT scans comprises identifying a multitude of selected portions and selected depths for the OCT scans.

9. The method of claim 8, wherein the step of identifying the multitude of selected portions and selected depths comprises constructing an analyte vector grid, an entry of the analyte vector grid being associated with a measure of a change in a slope between two OCT scans at one selected portion and one selected depth

10. Non-transitory computer-readable storage having stored thereon instructions that, when executed, direct a computing system to perform operations comprising:

computing intensity differences between at least two OCT scans of biological tissue to generate an intensity difference plot;

selecting, based on the intensity difference plot, a portion of the at least two OCT scans correlating with at least two blood analyte measurements, the at least two blood analyte measurements obtained independently from the at least two OCT scans; and

generating calibration data for an OCT device using the selected portions of the OCT scans.

11. The non-transitory computer-readable storage of claim 10, wherein the wavelength of light is within a range of about 770 nm to about 1400 nm.

12. The non-transitory computer-readable storage of claim 10, wherein the measuring OCT sensor is configured to scan a two dimensional surface area of the biological tissue and interferometrically scan in a depth dimension.

13. The non-transitory computer-readable storage of claim 12, wherein scanning the two dimensional surface area further comprises averaging data from scanning the two dimensional surface area to obtain at least one OCT scan associated with each blood analyte measurement.

14. An apparatus generating calibrating data for an optical coherence tomography (OCT) device, the apparatus comprising:

a processor configured to;

select at least two OCT scans from a plurality of OCT scans based in part on at least two blood analyte measurements, the at least two blood analyte measurements obtained independently from the at least two OCT scans;

compute intensity differences between the at least two OCT scans of biological tissue; and

generate, using a processor, calibration data for an OCT device based in part on the computed intensity differences between the at least two OCT scans.

15. The apparatus of claim 14, wherein the processor is configured to generate the calibration data by selecting portions of each of the OCT scans that have large changes in intensity and generating the calibration data based in part on the selected portions of the OCT scans.

16. The apparatus of claim 14, wherein the processor is configured to generate the calibration data by selecting portions of each of the OCT scans where intensity differences correlate with blood analyte level changes and generating the calibration data based in part on the selected portions of the OCT scans.

17. The apparatus of claim 14, wherein the processor is configured to generate the calibration data by selecting portions of each of the OCT scans where intensity differences correlate with blood vessels and generating the calibration data based in part on the selected portions of the OCT scans.

18. A method for generating calibrating data for an optical coherence tomography (OCT) device, comprising:

identifying at least one discontinuity in data associated with OCT scans of biological tissue;

selecting, based on the at least one discontinuity, portions of each of the OCT scans correlating with blood analyte measurements obtained independently from the OCT scans; and

determining, using a processor, calibration data for an OCT device using the selected portions of the OCT scans.

19. The method of claim 18, wherein identifying the at least one discontinuity comprises generating a second derivative plot from the obtained OCT scans and identifying the at least one discontinuity based on the second derivative plot.

20. The method of claim 18, wherein the at least one discontinuity correlates with a location of a tissue interface transition.

21. The method of claim 18, wherein the at least one discontinuity corresponds to changes in blood analyte levels.

22. The method of claim 18, further comprising constructing an analyte vector grid using at least one identified selected depth.