Noninvasive method for estimating glucose, glycosylated hemoglobin and other blood constituents

• US 9,597,021 B1
• Filed: 01/14/2015
• Issued: 03/21/2017
• Est. Priority Date: 01/14/2014
• Status: Active Grant

• Current Assignee: Analytics For Life
• Original Assignee: Analytics For Life
• Inventors: Gupta, Sunny, Burton, Timothy, Howe-Patterson, Matthew
• Primary Examiner(s): Chen, Tse
• Assistant Examiner(s): Lee, Yoojin
• Application Number:
  US14/596,541
• Time in Patent Office: 797 Days
• US Class Current: 1/1
• 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 5/14532 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 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity

Abstract

A light based method and technique for measuring the static and average plasma glucose concentration over a prolonged period of time. More specifically, the disclosure relates to a method that utilizes mathematical analysis of appendage mobile LED flash IR light transmittance, absorption and scattering by using high resolution mobile camera data to estimate the concentration of glucose and glycated hemoglobin (HbA1c) in millimoles per liter (mmol/L).

Claims

1. A method of performing light-based tissue perfusion blood constituent analysis, using a video recording device having an objective lens and an external light source, the method comprising:

placing the video recording device such that the objective lens is completely obstructed;

covering the external light source by at least part of a soft tissue appendage by placing the appendage against a frame of the objective lens while continuously illuminated by the external light source;

operating the video recording device to capture a digital signature of absorbed, transmitted and scattered light from the soft tissue appendage to obtain power spectral density (PSD) time series data;

analyzing signals from the video recording device to determine information about blood constituents in the appendage, the analyzing comprising;

converting the PSD time series data to CMOS sectors;

placing the CMOS sectors into a scatter matrix, an absorption matrix, and a transmittance matrix;

performing one of a model-based analysis to transform the PSD time series data to a noiseless model or a signal density-based analysis to segregate a signal associated with the PSD time series data into subspaces which are quantified; and

using a genetic algorithm to determine a level of blood glucose; and

presenting the level of blood glucose in a user interface of the video recording device.

2. The method of claim 1, wherein the illumination of the soft tissue appendage is performed using a wirelessly-connected or portable light source adjacent to the objective lens which transmits a plurality of wavelengths successively and repeatedly to enhance the absorption, scattering and transmittance pattern of a blood constituent of interest.

3. The method of claim 1, wherein the video recording device comprises a smart phone, watch or a video camera.

4. The method of claim 1, wherein the external light source is an LED or laser diode.

5. The method of claim 1, wherein the external light source has predetermined specific wavelengths.

6. The method of claim 1, wherein the video recording device comprises a video camera or a smartphone.

7. The method of claim 1, wherein the model-based analysis and the signal density-based analysis uses modified matching pursuit (MMP) algorithm.

8. The method of claim 1, further comprising:

transmitting the PSD time series data to a cloud-based image analysis service; and

performing the analyzing at the cloud-based image analysis service.

9. The method of claim 1, further comprising capturing the digital signature of absorbed, transmitted and scattered light using digital video made up of CMOS images collected at 15 to 120 frames per second.

10. The method of claim 1, further comprising:

determining Red-Green-Blue (RGB) values from the PSD time series data in accordance with the relationships;

11. The method of claim 1, further comprising:

recording changes in the level of blood glucose over time; and

providing an indication of a pathological state of a subject associated with the soft tissue appendage.

12. The method of claim 1, further comprising transmitting the determination of the level of blood glucose to a medical center.

13. A video recording device, comprising:

an objective lens;

an LED light source; and

a complementary metal-oxide semiconductor (CMOS) sensor,

wherein the video recording device records video data that contains a digital signature of absorbed, transmitted and scattered light from a soft tissue appendage placed against a frame of the objective lens while continuously illuminated by the external light source,

wherein power spectral density (PSD) time series data is derived from the video data and converted to CMOS sectors,

wherein the CMOS sectors are placed into a scatter matrix, an absorption matrix, and a transmittance matrix, wherein one of a model-based analysis is performed to transform the PSD time series data to a noiseless model or a signal density-based analysis is performed to segregate a signal associated with the PSD time series data into subspaces which are quantified,

wherein a genetic algorithm is used to determine a level of blood glucose, and

wherein the level of blood glucose is presented in a user interface of the video recording device.

14. The video recording device of claim 13, wherein the model-based analysis and the signal density-based analysis uses modified matching pursuit (MMP) algorithm.

15. The video recording device of claim 13, wherein the PSD time series data is transmitted to a cloud-based image analysis service, and wherein analyzing the PSD time series data is performed at the cloud-based image analysis service.

16. A method of performing light-based tissue perfusion blood constituent analysis, comprising:

using a video recording device having an objective lens and an external light source, placing the device such that the objective lens is completely obstructed;

covering the external light source of the video recording device by at least part of a soft tissue appendage by placing the appendage against a frame of the objective lens while continuously illuminated by the external light source;

operating the video recording device to capture a digital signature of absorbed, transmitted and scattered light from the soft tissue appendage to obtain power spectral density (PSD) time series data;

transmitting the PSD time series data from the video recording device to a remote source to determine information about blood constituents in the appendage, the remote source performing;

converting the PSD time series data to CMOS sectors;

placing the CMOS sectors into a scatter matrix, an absorption matrix, and a transmittance matrix;

performing one of a model-based analysis to transform the PSD time series data to a noiseless model or a signal density-based analysis to segregate a signal associated with the PSD time series data into subspaces which are quantified; and

using a genetic algorithm to determine a level of blood glucose; and

returning the level of blood glucose the video recording device to present the level of blood glucose in a user interface of the video recording device.

17. The method of claim 16, wherein the video recording device comprises a smart phone, watch or a video camera.

18. The method of claim 16, wherein the external light source is an LED or laser diode.

19. The method of claim 16, wherein the external light source has predetermined specific wavelengths.

20. The method of claim 16, wherein the video recording device comprises a video camera or a smartphone.