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Anal Bioanal Chem. 2018 Oct;410(25):6469-6475. doi: 10.1007/s00216-018-1244-y. Epub 2018 Jul 25.

Evaluation of accuracy dependence of Raman spectroscopic models on the ratio of calibration and validation points for non-invasive glucose sensing.

Author information

1
Laser Biomedical Research Center, G. R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
2
Department of Biological Engineering, School of Medicine, University of Missouri-Columbia, Columbia, MO, 65211, USA.
3
Department of Endocrinology, School of Medicine, University of Missouri-Columbia, Columbia, MO, 65211, USA.
4
Department of Radiology, School of Medicine, University of Missouri-Columbia, Columbia, MO, 65211, USA.
5
MU-institute of Clinical and Translational Sciences (MU-iCATS), School of Medicine, University of Missouri-Columbia, Columbia, MO, 65211, USA. upendrana@health.missouri.edu.
6
Department of Pharmacology and Physiology, School of Medicine, University of Missouri-Columbia, Columbia, MO, 65211, USA. upendrana@health.missouri.edu.
7
Laser Biomedical Research Center, G. R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. jwkang76@mit.edu.

Abstract

Optical monitoring of blood glucose levels for non-invasive diagnosis is a growing area of research. Recent efforts in this direction have been inclined towards reducing the requirement of calibration framework. Here, we are presenting a systematic investigation on the influence of variation in the ratio of calibration and validation points on the prospective predictive accuracy of spectral models. A fiber-optic probe coupled Raman system has been employed for transcutaneous measurements. Limit of agreement analysis between serum and partial least square regression predicted spectroscopic glucose values has been performed for accurate comparison. Findings are suggestive of strong predictive accuracy of spectroscopic models without requiring substantive calibration measurements. Graphical abstract.

KEYWORDS:

Diabetes; Glucose sensing; Partial least squares regression; Raman spectroscopy

PMID:
30046865
PMCID:
PMC6128756
DOI:
10.1007/s00216-018-1244-y
[Indexed for MEDLINE]
Free PMC Article

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