• DocumentCode
    1477190
  • Title

    Chemometric Approach for Improving VCSEL-Based Glucose Predictions

  • Author

    Fard, Sahba Talebi ; Chrostowski, Lukas ; Kwok, Ezra ; Amann, Markus-Christian

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
  • Volume
    57
  • Issue
    3
  • fYear
    2010
  • fDate
    3/1/2010 12:00:00 AM
  • Firstpage
    578
  • Lastpage
    585
  • Abstract
    Optical methods are one of the painless and promising techniques that can be used for blood glucose predictions for diabetes patients. The use of thermally tunable vertical cavity surface-emitting lasers (VCSELs) as the light source to obtain blood absorption spectra, along with the multivariate technique partial least squares for analysis and glucose estimation, has been demonstrated. With further improvements by using data preprocessing and two VCSELs, we have achieved a clinically acceptable level in the physiological range in buffered solutions. The results of previous experiments conducted using white light showed that increasing the number of wavelength intervals used in the analysis improves the accuracy of prediction. The average prediction error, using absorption spectra from one VCSEL in aqueous solution, is about 1.2 mM. This error is reduced to 0.8 mM using absorption spectra from two VCSELs. This result confirms that increasing the number of VCSELs improves the accuracy of prediction.
  • Keywords
    bio-optics; biochemistry; blood; buffer layers; diseases; laser applications in medicine; laser cavity resonators; least squares approximations; organic compounds; patient monitoring; spectrochemical analysis; surface emitting lasers; absorption spectra; blood absorption spectra; blood glucose predictions; buffered solutions; chemometric approach; data preprocessing; diabetes patients; improving VCSEL-based glucose predictions; multivariate technique partial least squares; thermally tunable vertical cav?? ity surface-emitting lasers; Absorption; Accuracy; Blood; Chemical lasers; Diabetes; Optical buffering; Optical surface waves; Sugar; Tunable circuits and devices; Vertical cavity surface emitting lasers; Chemometrics for glucose prediction; optical glucose monitoring; real-time glucose monitoring; Blood Glucose; Humans; Lasers; Magnetic Resonance Spectroscopy; Models, Biological; Monitoring, Physiologic; Predictive Value of Tests; Reproducibility of Results; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2009.2032160
  • Filename
    5268215