Literature DB >> 34672216

Noninvasive Glucose Monitoring: In God We Trust-All Others Bring Data.

David C Klonoff1, Kevin T Nguyen2, Nicole Y Xu2, Mark A Arnold3.   

Abstract

Entities:  

Keywords:  device; glucose; infrared; noninvasive; optical

Mesh：

Substances：

Year:  2021        PMID： 34672216      PMCID： PMC8655290          DOI： 10.1177/19322968211046326

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN： 1932-2968


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  16 in total

1.  Noninvasive glucose sensing.

Authors:  Mark A Arnold; Gary W Small
Journal:  Anal Chem       Date:  2005-09-01       Impact factor: 6.986

2.  Influence of glucose concentration on light scattering in tissue-simulating phantoms.

Authors:  M Kohl; M Cope; M Essenpreis; D Böcker
Journal:  Opt Lett       Date:  1994-12-15       Impact factor: 3.776

Review 3.  Spectroscopic and clinical aspects of noninvasive glucose measurements.

Authors:  O S Khalil
Journal:  Clin Chem       Date:  1999-02       Impact factor: 8.327

4.  Noninvasive glucose monitoring: increasing accuracy by combination of multi-technology and multi-sensors.

Authors:  Ilana Harman-Boehm; Avner Gal; Alexander M Raykhman; Eugene Naidis; Yulia Mayzel
Journal:  J Diabetes Sci Technol       Date:  2010-05-01

5.  Pendra goes Dutch: lessons for the CE mark in Europe.

Authors:  I M E Wentholt; J B L Hoekstra; A Zwart; J H DeVries
Journal:  Diabetologia       Date:  2005-05-04       Impact factor: 10.122

6.  Non-Invasive Glucose Monitoring Using Optical Sensor and Machine Learning Techniques for Diabetes Applications.

Authors:  Maryamsadat Shokrekhodaei; David P Cistola; Robert C Roberts; Stella Quinones
Journal:  IEEE Access       Date:  2021-05-11       Impact factor: 3.367

Review 7.  Review of Non-invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone.

Authors:  Maryamsadat Shokrekhodaei; Stella Quinones
Journal:  Sensors (Basel)       Date:  2020-02-25       Impact factor: 3.576

Review 8.  Products for Monitoring Glucose Levels in the Human Body With Noninvasive Optical, Noninvasive Fluid Sampling, or Minimally Invasive Technologies.

Authors:  Trisha Shang; Jennifer Y Zhang; Andreas Thomas; Mark A Arnold; Beatrice N Vetter; Lutz Heinemann; David C Klonoff
Journal:  J Diabetes Sci Technol       Date:  2021-06-13

9.  The accuracy of a non-invasive glucose monitoring device does not depend on clinical characteristics of people with type 2 diabetes mellitus.

Authors:  Tamar Lin; Yulia Mayzel; Karnit Bahartan
Journal:  J Drug Assess       Date:  2018-01-11

10.  Utility of Big Data in Predicting Short-Term Blood Glucose Levels in Type 1 Diabetes Mellitus Through Machine Learning Techniques.

Authors:  Ignacio Rodríguez-Rodríguez; Ioannis Chatzigiannakis; José-Víctor Rodríguez; Marianna Maranghi; Michele Gentili; Miguel-Ángel Zamora-Izquierdo
Journal:  Sensors (Basel)       Date:  2019-10-16       Impact factor: 3.576
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