Multivariate calibration of NIR spectroscopic sensors for continuous glucose monitoring

Mohammad Goodarzi, Sandeep Sharma, Herman Ramon, Wouter Saeys

Research output: Contribution to journalReview articlepeer-review

96 Scopus citations


Diabetes, a disorder in the control of blood-glucose levels, is one of the most serious metabolic diseases worldwide. Among the investigated technologies for continuous glucose monitoring (CGM), near-infrared spectroscopy (NIR) has received the most attention. There have been many attempts to develop NIR-based CGM systems with promising in-vitro results, but they lacked robustness for in-vivo use. We critically review the application of chemometrics for CGM and the research needed. Pre-processing and multivariate-calibration techniques, which allow exploiting expert knowledge on the potential interferences, are possible solutions. The combination and first overtone bands in the ranges 2050-2300nm and 1500-1800nm, respectively, are the most informative regions. We therefore recommended selecting the most informative variables and exploiting the available expert knowledge on known interferences in pre-processing or multivariate calibration to develop an NIR-based CGM sensor for in-vivo use.

Original languageEnglish (US)
Pages (from-to)147-158
Number of pages12
JournalTrAC - Trends in Analytical Chemistry
StatePublished - Apr 1 2015


  • Blood-glucose measurement
  • Chemometrics
  • Continuous glucose monitoring
  • Diabetes
  • In-vivo use
  • Multivariate calibration
  • NIR spectroscopy
  • Pre-processing strategy
  • Sensor
  • Variable selection

ASJC Scopus subject areas

  • Analytical Chemistry
  • Spectroscopy


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