Skip to main content
  • More from ADA
    • Diabetes
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care
  • Subscribe
  • Log in
  • My Cart
  • Follow ada on Twitter
  • RSS
  • Visit ada on Facebook
Diabetes Care

Advanced Search

Main menu

  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • Special Article Collections
    • ADA Standards of Medical Care
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • Special Article Collections
    • ADA Standards of Medical Care
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcasts
    • Diabetes Core Update
    • Special Podcast Series: Therapeutic Inertia
    • Special Podcast Series: Influenza Podcasts
    • Special Podcast Series: SGLT2 Inhibitors
    • Special Podcast Series: COVID-19
  • Submit
    • Submit a Manuscript
    • Journal Policies
    • Instructions for Authors
    • ADA Peer Review
  • More from ADA
    • Diabetes
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care

User menu

  • Subscribe
  • Log in
  • My Cart

Search

  • Advanced search
Diabetes Care
  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • Special Article Collections
    • ADA Standards of Medical Care
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • Special Article Collections
    • ADA Standards of Medical Care
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcasts
    • Diabetes Core Update
    • Special Podcast Series: Therapeutic Inertia
    • Special Podcast Series: Influenza Podcasts
    • Special Podcast Series: SGLT2 Inhibitors
    • Special Podcast Series: COVID-19
  • Submit
    • Submit a Manuscript
    • Journal Policies
    • Instructions for Authors
    • ADA Peer Review
Brief Reports

Body Metabolism Provides a Foundation for Noninvasive Blood Glucose Monitoring

  1. Jae B. Ko, PHD1,
  2. Ok K. Cho, MD2,
  3. Yoon O. Kim, PHD2 and
  4. Kazuo Yasuda, PHD3
  1. 1KJ Office, Palisades Park, New Jersey
  2. 2PhiScience, Schwerte, Germany
  3. 3Hitachi, Tokyo, Japan
  1. Address correspondence to Ok K. Cho, PhiScience, Konrad-Zuse-Strasse 6, 58239 Schwerte, Germany. E-mail: cho-phiscience{at}versanet.de
Diabetes Care 2004 May; 27(5): 1211-1212. https://doi.org/10.2337/diacare.27.5.1211
PreviousNext
  • Article
  • Figures & Tables
  • Info & Metrics
  • PDF
Loading

The metabolic oxidation of glucose in the human body, also known as cellular respiration, provides most of the energy necessary for cellular activities. Several authors (1–4) have suggested that the relationship between blood glucose concentration and physiological parameters relates to metabolism. Until now, this phenomenon has not been utilized to calculate blood glucose concentration (5–7). Here we describe the noninvasive measurements of glucose concentration in the blood by taking into account the body heat generated by glucose oxidation and local oxygen supply. We arrived at this concept from observing that the circadian rhythm of the human body conforms to the subtle balance seen among metabolic heat, local oxygen supply, and glucose concentration. We have developed a system that integrates both thermal and spectroscopic sensors, which simultaneously measures these related parameters and subsequently physicochemically derives the concentration of blood glucose. Our discovery shows that blood glucose concentration can be accurately and reliably measured by this novel, noninvasive technique.

RESEARCH DESIGN AND METHODS

Our concept is based on following function equation:

[GLU] = F (heat generated, Hb, HbO2, and blood flow rate)

where [GLU] represents the concentration of glucose and F is a function of a set of metabolic parameters found in the subject’s fingertip [heat generated, hemoglobin concentration (Hb), oxyhemoglobin (HbO2), blood flow rate, and their composites]. These metabolic parameter values are, in turn, interdependent among each other.

Possibly a reverse relation, (GLU) = F (heat generated, Hb, HbO2, and blood flow rate), can be observed. This is probably the case if the observed change in temperature, in energy balance, or in the blood flow rate, respectively, is caused by the other parameters, by the change of environmental temperature (room temperature), or by metabolic disorders.

The parameters are measured by the experimental setup shown in Fig. 1A. Thermal measurements from a finger’s surface are obtained from three temperature sensors. Before the measurement, moisture or wetness on the finger was carefully wiped out to avoid a negative effect.

A pyroelectric detector (D1) inside the device measures the radiation temperature of the finger. Thermistors (D2 and D3) are connected to a thin gold plate and a cylindrical material, on which the finger is placed for the contact temperature measurement. The measurement time is ∼10 s. Before and after finger placement, the ambient temperatures are measured for baseline correction.

The supplied oxygen amount is estimated by using blood flow rate, Hb, and HbO2. The blood flow rate is primarily obtained by the delayed thermal conductivity being measured with the thermistor (D3). Hb and HbO2 are measured by spectroscopic measurement via a modified diffuse reflection method. Wavelengths of 470, 535, 660, 810, 880, and 950 nm are produced by six light-emitting diodes (L1 to L6, respectively) and measured by three photodiodes (D4 to D6). Optical fibers lead light from the light-emitting diodes to the subject’s finger. These three detectors are arranged to measure the specular (D4) and diffuse reflection (D5) on the top, just inside, and through the skin surface (D6). The concentrations of Hb and HbO2 are calculated using the values of multiple components obtained by the three detectors multiplied by the six wavelengths, and the results are corrected for individual skin roughness, thickness, and chromogen. As a final step in the processing of these values, all possible regressions and stepwise elimination (8–10) are applied and a calibration function is performed.

RESULTS

Figure 1B shows a regression analysis involving 35 data points (29 from diabetic patients and 6 from nondiabetic volunteers) by the noninvasive method against a glucose oxidase enzymatic amperometry for whole-blood samples as the reference method. Each data point represents that the noninvasive measurement and the capillary blood collection for glucose oxidase measurement were simultaneously performed at random timing for each patient. Blood glucose concentration was measured over a range of 50 to 400 mg/dl. The coefficient of correlation (r) was 0.96, and precision obtained was 10 mg/dl by duplicate measurements. Additionally, for healthy fasting people, repeatability of the noninvasive method was measured five times within 20 min. The mean was 100 mg/dl and the SD 6 mg/dl.

CONCLUSIONS

We have shown that the physiological parameters of glucose oxidative metabolism can be measured by various modalities and that blood glucose concentration can be accurately and reliably physicochemically derived. Therefore, it is possible to reproducibly measure glucose concentration by this novel, noninvasive manner. Studies are ongoing to further evaluate the clinical utility of this innovative, noninvasive, glucose measurement method, which could provide important public health benefits for the increasing diabetic population.

Figure 1—
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1—

A: The experimental setup. B: Regression analysis involving 35 data points (29 from diabetic patients and 6 from healthy volunteers) by the noninvasive method against a glucose oxidase (GOD) enzymatic amperometry for whole-blood samples as the reference method. n = number of measurements. c, blood glucose concentration; r, coefficient of correlation.

Footnotes

  • J.B.K. and K.Y. have received consulting fees from Hitachi.

    • Accepted February 9, 2004.
    • Received September 11, 2003.
  • DIABETES CARE

References

  1. ↵
    Seaman GVF, Engel R, Swank RL, Hissen W: Circadian periodicity in some physicochemical parameters of circulating blood. Nature 207:833–835, 1965
    OpenUrlCrossRefPubMedWeb of Science
  2. Hillson RM, Hockaday TDR: Facial and sublingual temperature changes following intravenous glucose injection in diabetes. Diabete Metab (Paris) 8:15–19, 1982
    OpenUrl
  3. Cho OK, Holzgreve B, inventors: Process and device for detecting the exchange of heat between the human body and the invented device and its correlation to the glucose concentration in human blood. U.S. patent 5 924 996, 1999
  4. ↵
    Cho OK, Holzgreve B, inventors: Process and device for non-invasive determination of glucose concentration in parts of the human body. U.S. patent 5 795 305, 1998
  5. ↵
    Waynant RW, Chenault VM: Overview of non-invasive fluid glucose measurement using optical techniques to maintain glucose control in diabetes mellitus. IEEE Lasers Electro-optics Soc Newsletter, 1998, p. 3–6
  6. Khalil OS: Spectroscopic and clinical aspects of noninvasive glucose measurements. Clin Chem 45:165–177, 1999
    OpenUrlAbstract/FREE Full Text
  7. ↵
    Klonoff DC: Noninvasive blood glucose monitoring. Diabetes Care 20:433–437, 1997
    OpenUrlAbstract/FREE Full Text
  8. ↵
    Seber GAF: Linear Regression Analysis. New York, John Wiley & Sons, 1977
  9. Hocking RR: The analysis and selection of variables in linear regression. In Biometrics. 32:1–49, 1976
    OpenUrlCrossRefWeb of Science
  10. ↵
    Walls R, Weeks D: A note on the variance of a predicted response in regression. Am Stat 23:24–26, 1969
    OpenUrl
PreviousNext
Back to top
Diabetes Care: 27 (5)

In this Issue

May 2004, 27(5)
  • Table of Contents
  • About the Cover
  • Index by Author
Sign up to receive current issue alerts
View Selected Citations (0)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word about Diabetes Care.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Body Metabolism Provides a Foundation for Noninvasive Blood Glucose Monitoring
(Your Name) has forwarded a page to you from Diabetes Care
(Your Name) thought you would like to see this page from the Diabetes Care web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Body Metabolism Provides a Foundation for Noninvasive Blood Glucose Monitoring
Jae B. Ko, Ok K. Cho, Yoon O. Kim, Kazuo Yasuda
Diabetes Care May 2004, 27 (5) 1211-1212; DOI: 10.2337/diacare.27.5.1211

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Add to Selected Citations
Share

Body Metabolism Provides a Foundation for Noninvasive Blood Glucose Monitoring
Jae B. Ko, Ok K. Cho, Yoon O. Kim, Kazuo Yasuda
Diabetes Care May 2004, 27 (5) 1211-1212; DOI: 10.2337/diacare.27.5.1211
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • RESEARCH DESIGN AND METHODS
    • RESULTS
    • CONCLUSIONS
    • Footnotes
    • References
  • Figures & Tables
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More in this TOC Section

  • Combination Therapy With Fenofibrate and Rosiglitazone Paradoxically Lowers Serum HDL Cholesterol
  • β-Cell Transplantation Restores Metabolic Control and Quality of Life in a Patient With Subcutaneous Insulin Resistance
  • Hematocrit and the Incidence of Type 2 Diabetes in the Pima Indians
Show more Brief Reports

Similar Articles

Navigate

  • Current Issue
  • Standards of Care Guidelines
  • Online Ahead of Print
  • Archives
  • Submit
  • Subscribe
  • Email Alerts
  • RSS Feeds

More Information

  • About the Journal
  • Instructions for Authors
  • Journal Policies
  • Reprints and Permissions
  • Advertising
  • Privacy Policy: ADA Journals
  • Copyright Notice/Public Access Policy
  • Contact Us

Other ADA Resources

  • Diabetes
  • Clinical Diabetes
  • Diabetes Spectrum
  • Scientific Sessions Abstracts
  • Standards of Medical Care in Diabetes
  • BMJ Open - Diabetes Research & Care
  • Professional Books
  • Diabetes Forecast

 

  • DiabetesJournals.org
  • Diabetes Core Update
  • ADA's DiabetesPro
  • ADA Member Directory
  • Diabetes.org

© 2021 by the American Diabetes Association. Diabetes Care Print ISSN: 0149-5992, Online ISSN: 1935-5548.