Chemometric approach for improving VCSEL-based glucose predictions

IEEE Transactions on Biomedical Engineering

Volumn 57, Issue 3, 2010, Pages 578-585

  Fard, Sahba Talebi ^a   Chrostowski, Lukas ^a   Kwok, Ezra ^a   Amann, Markus Christian ^b  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b WALTER SCHOTTKY INSTITUT   (Germany)

Author keywords

Chemometrics for glucose prediction; Optical glucose monitoring; Real time glucose monitoring

Indexed keywords

AQUEOUS SOLUTIONS; AVERAGE PREDICTION ERROR; BLOOD GLUCOSE; BUFFERED SOLUTIONS; CHEMOMETRIC APPROACH; CHEMOMETRICS; DATA PREPROCESSING; DIABETES PATIENTS; GLUCOSE MONITORING; MULTIVARIATE TECHNIQUES; OPTICAL METHODS; PARTIAL LEAST SQUARES; PHYSIOLOGICAL RANGE; REAL-TIME GLUCOSE MONITORING; VERTICAL-CAVITY SURFACE EMITTING LASER; WHITE LIGHT;

ABSORPTION; BLOOD; FORECASTING; LIGHT; LIGHT ABSORPTION; LIGHT SOURCES; SURFACE EMITTING LASERS; TRANSCEIVERS;

GLUCOSE;

BUFFER; GLUCOSE;

ABSORPTION SPECTROSCOPY; ACCURACY; AQUEOUS SOLUTION; ARTICLE; BLOOD; CHEMOMETRIC ANALYSIS; DIABETIC PATIENT; GLUCOSE BLOOD LEVEL; HUMAN; INFORMATION PROCESSING; LASER; PHYSIOLOGY; PREDICTION; SIGNAL NOISE RATIO; SPECTRAL SENSITIVITY; VERTICAL CAVITY SURFACE EMITTING LASER; WHITE LIGHT;

BLOOD GLUCOSE; HUMANS; LASERS; MAGNETIC RESONANCE SPECTROSCOPY; MODELS, BIOLOGICAL; MONITORING, PHYSIOLOGIC; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 77649137108     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2009.2032160     Document Type: Article

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