Modified sequential floating selection for blood glucose monitoring using near infrared spectral data

C. F. So, Yugu Zeng, Kup Sze Choi, J. W.Y. Chung, T. K.S. Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

To enable non-invasive blood glucose monitoring using near infrared spectroscopy, a modified sequential floating selection method is proposed to remove uninformative data from the spectrum. A linear discriminant function is then used for classification based on selected features. Experiments show that this approach is able to give promising prediction results by classifying near infrared spectroscopic data of blood glucose with good accuracy.
Original languageEnglish
Pages (from-to)284-288
Number of pages5
JournalJournal of Applied Spectroscopy
Volume80
Issue number2
DOIs
Publication statusPublished - 1 May 2013

Keywords

  • Linear discriminant function
  • Near infrared
  • Sequential floating selection
  • Spectroscopic data

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Spectroscopy

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