Systems and methods for generating and using projector curve sets for universal calibration for noninvasive blood glucose and other measurements

• US 9,459,203 B2
• Filed: 01/12/2016
• Issued: 10/04/2016
• Est. Priority Date: 09/29/2014
• Status: Active Grant

• Current Assignee: Zyomed Holdings, Inc.
• Original Assignee: Zyomed Corp.
• Inventors: Gulati, Sandeep, Ruchti, Timothy L., Van Antwerp, William, Smith, John L.
• Primary Examiner(s): Kim, Kiho
• Application Number:
  US14/993,905
• Publication Number:
  US 20160139043A1
• Time in Patent Office: 266 Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 5/0075 by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy A61B5/0071 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02433 for infrared radiation
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7235 Details of waveform analysis A61B5/349 takes precedence
• CPC Class Codes: A61B 5/7253 characterised by using transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G01N 21/3577 for analysing liquids, e.g. polluted water
• CPC Class Codes: G01N 21/359 using near infrared light
• CPC Class Codes: G01N 21/4795 spatially resolved investigating of object in scattering medium in vivo A61B
• CPC Class Codes: G01N 21/49 within a body or fluid
• CPC Class Codes: G01N 2201/0612 Laser diodes
• CPC Class Codes: G01N 2201/062 LED's
• CPC Class Codes: G01N 2201/067 : Electro-optic, magneto-optic, acousto-optic elements
• CPC Class Codes: G01N 2201/12 : Circuits of general importance; Signal processing
• CPC Class Codes: G01N 2201/129 : Using chemometrical methods
• CPC Class Codes: G01N 33/4833 : of solid biological material, e.g. tissue samples, cell cultures tissue in vivo A61B5/00; cell suspensions G01N33/48735
• CPC Class Codes: G01N 33/49 : Blood chemical methods for determining blood cell populations G01N33/5094; chemical analysis of blood groups or blood types G01N33/80
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 : for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A synthetic projection system determines analyte concentration, such as blood glucose concentration, from a spectral-energy change associated with an uncharacterized instance of a medium in which the analyte is likely present. The projection system is factory calibrated for different instances of the medium, without needing instance-specific training or calibration. The projection system includes a set of projector curves, each relating spectral-energy change values obtained by analyzing reference medium samples to analyte concentrations in those samples. Each projector curve also corresponds to a respective range of energy-change gradients, determined using a group of surrogate media characterized according to analyte concentrations measured using a reference system. A spectral-energy-change gradient for the uncharacterized medium may be computed to select one of the projectors curves. Analyte concentration in the uncharacterized medium can be reliably computed at a specified high level of accuracy using the spectral-energy change associated therewith and the selected curve.

Claims

1. A method for calibrating a measurement system for non-invasive analyte measurement, the method comprising the steps of:

obtaining in memory in communication with a processor, from a selected plurality of synthetic medium samples, each having a reference analyte concentration, a plurality of energy-value sets from the measurement system, each energy value in a particular energy-value set corresponding to a respective reference analyte concentration from the selected plurality of synthetic medium samples;

generating by the processor a composite projector curve using the plurality of energy value sets and the plurality of reference analyte concentrations; and

partitioning by the processor the composite projector curve into a set of non-overlapping individual projector curves according to a set of slopes of the composite projector curve, each individual projector curve being identified by a lower bound analyte concentration and an upper bound analyte concentration.

2. The method of claim 1, wherein the plurality of energy-value sets comprises a first energy-value set, each energy value in the first energy-value set corresponding to a first reference analyte concentration, the method further comprising:

excluding from the first energy-value set an energy value that is different from a mean of the energy values by a specified threshold.

3. The method of claim 1, further comprising:

obtaining from representative subjects a plurality of groups of energy value vectors from the measurement system, each energy-value-vector group corresponding to a respective analyte concentration determined using a reference invasive measurement system, and each energy-value vector in a particular group corresponding to a respective feature pair;

partitioning the plurality of groups of energy-value vectors into a plurality of projection sets, such that the analyte concentration corresponding to any energy-value-vector group in each projection set is within lower and upper bound analyte concentrations corresponding to a single respective individual projector curve from the set of individual projector curves;

computing for each energy-value-vector group in each projection set, an average of normalized absorption gradients (NAGs), each NAG corresponding to an energy-value vector that corresponds to an acceptable feature pair;

for each projector curve;

designating as a lower bound NAG a minimum of averaged NAGs of all energy-value-vector groups of the corresponding projection set; and

designating as an upper bound NAG a maximum of averaged NAGs of all energy-value-vector groups of the corresponding projection set.

4. The method of claim 3, wherein an energy-value vector comprises a plurality of energy values, each energy value corresponding to an illumination state in an illumination sequence.

5. The method of claim 4, wherein the partitioning step comprises rejecting from a group of energy-value vectors any non-monotonic energy-value vector.

6. A method for computing analyte concentration in a medium, the method comprising:

selecting by a processor a member of a projector curve set, stored in memory in communication with the processor, according to a normalized absorption gradient (NAG) value, such that the NAG value is within a range of minimum and maximum NAG values associated with that member; and

interpolating analyte concentration by the processor using a slope and an intercept of the selected member.

7. The method of claim 6, further comprising:

receiving for a feature pair, a respective net renormalized spectral energy gain (NRSEG) value for each one of a plurality of illumination states; and

designating the feature pair as acceptable feature pair, if the respective NRSEG values are monotonic across the illumination states, and rejecting the feature pair, otherwise.

8. The method of claim 6, further comprising:

receiving for a first acceptable feature pair, a respective net renormalized spectral energy gain (NRSEG) value for each one of a plurality of illumination states;

computing a first absorption gradient (AG) across the illumination states using the NRSEG values associated with the first acceptable feature pair; and

computing the NAG by applying to the first AG a first weight corresponding to the first acceptable feature pair.

9. The method of claim 8, further comprising:

receiving for a second acceptable feature pair, a respective net renormalized spectral energy gain (NRSEG) value for each one of the plurality of illumination states;

computing a second absorption gradient (AG) across the illumination states using the NRSEG values associated with the second acceptable feature pair; and

computing the NAG by applying to the second AG a second weight corresponding to the second acceptable feature pair and averaging the first and second weighted AGs.

10. A system for calibrating a measurement system for non-invasive analyte measurement, the system comprising:

a first processor; and

a first memory in electrical communication with the first processor, the first memory comprising instructions which, when executed by a processing unit comprising at least one of the first processor and a second processor, and in electronic communication with a memory module comprising at least one of the first memory and a second memory, program the processing unit to;

obtain from a selected plurality of synthetic medium samples, each having a reference analyte concentration, a plurality of energy-value sets from the measurement system, each energy value in a particular energy-value set corresponding to a respective reference analyte concentration from the selected plurality of synthetic medium samples;

generate a composite projector curve using the plurality of energy value sets and the plurality of reference analyte concentrations; and

partition the composite projector curve into a set of non-overlapping individual projector curves according to a set of slopes of the composite projector curve, each individual projector curve being identified by a lower bound analyte concentration and an upper bound analyte concentration.

11. The system of claim 10, wherein the plurality of energy-value sets comprises a first energy-value set, each energy value in the first energy-value set corresponding to a first reference analyte concentration, wherein the instructions further program the processing unit to:

exclude from the first energy-value set an energy value that is different from a mean of the energy values by a specified threshold.

12. The system of claim 10, wherein the instructions further program the processing unit to:

obtain from representative subjects a plurality of groups of energy value vectors from the measurement system, each energy-value-vector group corresponding to a respective analyte concentration determined using a reference invasive measurement system, and each energy-value vector in a particular group corresponding to a respective feature pair;

partition the plurality of groups of energy-value vectors into a plurality of projection sets, such that the analyte concentration corresponding to any energy-value-vector group in each projection set is within lower and upper bound analyte concentrations corresponding to a single respective individual projector curve from the set of individual projector curves;

compute for each energy-value-vector group in each projection set, an average of normalized absorption gradients (NAGs), each NAG corresponding to an energy-value vector that corresponds to an acceptable feature pair;

for each projector curve;

designate as a lower bound NAG a minimum of averaged NAGs of all energy-value-vector groups of the corresponding projection set; and

designate as an upper bound NAG a maximum of averaged NAGs of all energy-value-vector groups of the corresponding projection set.

13. The system of claim 12, wherein an energy-valued vector comprises a plurality of energy values, each energy value corresponding to an illumination state in an illumination sequence.

14. The system of claim 13, wherein to partition the composite projector curve, the instructions further program the processing unit to reject from a group of energy-value vectors any non-monotonic energy-value vector.

15. A system of computing analyte concentration in a medium, the system comprising:

a first processor; and

a first memory in electrical communication with the first processor, the first memory comprising instructions which, when executed by a processing unit comprising at least one of the first processor and a second processor, and in electronic communication with a memory module comprising at least one of the first memory and a second memory, program the processing unit to;

select a member of a projector curve set according to a normalized absorption gradient (NAG) value, such that the NAG value is within a range of minimum and maximum NAG values associated with that member; and

interpolate analyte concentration using a slope and an intercept of the selected member.

16. The system of claim 15, wherein the instructions further program the processing unit to:

receive for a feature pair, a respective net renormalized spectral energy gain (NRSEG) value for each one of a plurality of illumination states; and

designate the feature pair as acceptable feature pair, if the respective NRSEG values are monotonic across the illumination states, and rejecting the feature pair, otherwise.

17. The system of claim 15, wherein the instructions further program the processing unit to:

receive for a first acceptable feature pair, a respective net renormalized spectral energy gain (NRSEG) value for each one of a plurality of illumination states;

compute a first absorption gradient (AG) across the illumination states using the NRSEG values associated with the first acceptable feature pair; and

compute the NAG by applying to the first AG a first weight corresponding to the first acceptable feature pair.

18. The system of claim 17, wherein the instructions further program the processing unit to:

receive for a second acceptable feature pair, a respective net renormalized spectral energy gain (NRSEG) value for each one of the plurality of illumination states;

compute a second absorption gradient (AG) across the illumination states using the NRSEG values associated with the second acceptable feature pair; and

compute the NAG by applying to the second AG a second weight corresponding to the second acceptable feature pair and averaging the first and second weighted AGs.