Skip to main content
Log in

Removal of Interference Signals Due to Water from in vivo Near-Infrared (NIR) Spectra of Blood Glucose by Region Orthogonal Signal Correction (ROSC)

  • Published:
Analytical Sciences Aims and scope Submit manuscript

Abstract

A novel chemometric method, region orthogonal signal correction (ROSC), is proposed and applied to pretreat near-infrared (NIR) spectra of blood glucose measured in vivo. Water is the most serious interference component in such kinds of noninvasive measurements, because it shows very high absorbance in the spectra. In the present study, the spectra of blood glucose in the range of 1212–1889 nm are used, in which the absorption of water around 1440 nm is very high. ROSC aims at removing the interference signal due to water from the spectra by selecting a set of spectra with a special region of 1404–1454 nm that mainly contain information about the variation of the interference component, water, and calculating the orthogonal components to the concentrations of glucose that will be removed. The difference between ROSC and orthogonal signal correction (OSC) is that ROSC uses a special region of spectra for the estimation of scores and loading weights of orthogonal components to pretreat the spectra in other regions, while OSC only uses one fixed region of spectra to calculate loadings, scores and weights of OSC components and removes the OSC components in the same region. A clear advantage of ROSC is that it is more interpretable than OSC, because one can select a spectral region to remove the variation of a special component such as water. Another chemometric method, moving window partial least squares (MWPLSR), is also used to select informative regions of glucose from the NIR spectra of blood glucose measured in vivo, leading to improved PLS models. Results of the application of ROSC demonstrate that ROSC-pretreated spectra including the whole spectral region of 1212–1889 nm or an informative region of 1600–1730 nm selected by MWPLSR provide very good performance of the PLS models. Especially, the later region yields a model with RMSECV of 15.8911 mg/dL for four PLS components. ROSC is a potential chemometric technique in the pretreatment of various spectra.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. R. Marbach, T. Koschinsky, F. A. Gries, and H. M. Heise, Appl. Spectrosc., 1993, 47, 875.

    Article  CAS  Google Scholar 

  2. J. J. Burmeister and M. A. Arnold, Clin. Chem., 1999, 45, 1621.

    Article  CAS  Google Scholar 

  3. M. A. Arnold and G. W. Small, Anal. Chem., 1990, 62, 1457.

    Article  CAS  Google Scholar 

  4. A. Samann, Ch. Fishbacher, K. U. Jagemann, K. Danzer, J. Schuler, L. Papenkordt, and U. A. Muller, Exp. Clin. Endocrinol. Diabetes, 2000, 108, 406.

    Article  Google Scholar 

  5. M. R. Robinson, R. P. Eaton, D. M. Haaland, G. W. Koepp, E. V. Thomas, B. R. Stallard, and P. L. Robinson, Clin. Chem., 1992, 38, 1618.

    Article  CAS  Google Scholar 

  6. H. M. Heise, A. Bittner, and R. J. Marbach, Near Infrared Spectrosc., 1998, 6, 349.

    Article  CAS  Google Scholar 

  7. H. M. Heise, R. Marbach, T. H. Koschinsky, and F. A. Gries, Artif. Org., 1994, 18, 439.

    Article  CAS  Google Scholar 

  8. R. Marbach and H. M. Heise, Appl. Optics, 1995, 34, 610.

    Article  CAS  Google Scholar 

  9. K. U. Jagemann, C. Fischbacher, K. Danzer, U. A. Muller, and B. Mertes, Z. Phys. Chem., 1995, 191S, 179.

    Article  Google Scholar 

  10. C. Fischbacher, K. U. Jagemann, K. Danzer, U. A. Muller, L. Papenkrodt, and J. Schuler, Fresenius J. Anal. Chem., 1997, 359, 78.

    Article  CAS  Google Scholar 

  11. K. Maruo, M. Tsurugi, M. Tamura, and Y. Ozaki, Appl. Spectrosc., 2003, 57, 1236.

    Article  CAS  Google Scholar 

  12. K. Maruo, M. Tsurugi, J. Chin, T. Ota, H. Arimoto, Y. Yamada, M. Tamura, M. Ishii, and Y. Ozaki, IEEE J. Sel. Top. Quantum Electron., 2003, 9, 322.

    Article  CAS  Google Scholar 

  13. G. Yoon, A. K. Amerov, K. J. Jeon, and Y. J. Kim, Appl. Optics, 2002, 41, 1469.

    Article  CAS  Google Scholar 

  14. S. Wold, H. Antti, F. Lindgren, and J. Ohman, Chemom. Intell. Lab. Syst., 1998, 44, 175.

    Article  CAS  Google Scholar 

  15. J. Sjoblom, O. Svensson, M. Josefson, H. Kullberg, and S. Wold, Chemom. Intell. Lab. Syst., 1998, 44, 229.

    Article  CAS  Google Scholar 

  16. T. Fearn, Chemom. Intell. Lab. Syst., 2000, 50, 47.

    Article  CAS  Google Scholar 

  17. B. M. Wise and N. B. Gallagher, http://www.eigenvector.com/MATLAB/OSC.html.

  18. J. H. Jiang, R. J. Berry, H. W. Siesler, and Y. Ozaki, Anal. Chem., 2002, 74, 3555.

    Article  CAS  Google Scholar 

  19. J. A. Westerhuis, S. Jong, and A. K. Smilde, Chemom. Intell. Lab. Syst., 2001, 56, 13.

    Article  CAS  Google Scholar 

  20. S. Kasemsumran, Y. P. Du, K. Murayama, M. Huehne, and Y. Ozaki, Analyst, 2003, 128, 1471.

    Article  CAS  Google Scholar 

  21. Y. P. Du, Y. Z. Liang, J. H. Jiang, R. J. Berry, and Y. Ozaki, Anal. Chim. Acta, 2003, 501, 183.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Du, Y.P., Liang, Y.Z., Kasemsumran, S. et al. Removal of Interference Signals Due to Water from in vivo Near-Infrared (NIR) Spectra of Blood Glucose by Region Orthogonal Signal Correction (ROSC). ANAL. SCI. 20, 1339–1345 (2004). https://doi.org/10.2116/analsci.20.1339

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2116/analsci.20.1339

Navigation