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In vivo continuous glucose monitoring using a chip based near infrared sensor

: Mohammadi, Lhoucine Ben; Sigloch, Susanne; Frese, Ines; Welzel, Knut; Göddel, Michael; Klotzbücher, Thomas


Popp, J. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Biophotonics: Photonic Solutions for Better Health Care IV. Proceedings : April 14, 2014, Brussels, Belgium
Bellingham, WA: SPIE, 2014 (Proceedings of SPIE 9129)
ISBN: 978-1-6284-1077-8
Paper 912929, 9 pp.
Conference "Biophotonics - Photonic Solutions for Better Health Care" <4, 2014, Brussels>
Conference Paper
Fraunhofer ICT-IMM ()
glucose; near infrared; sensors; blood; LED lighting

Diabetes is a serious health condition considered to be one of the major healthcare epidemics of modern era. An effective treatment of this disease can be only achieved by reliable continuous information on blood glucose levels. In this work we present a minimally invasive, chip-based near infrared (NIR) sensor, combined with microdialysis, for continuous glucose monitoring (CGM). The sensor principle is based on difference absorption spectroscopy in the 1st overtone band of the near infrared spectrum. The device features a multi-emitter LED and InGaAs-Photodiodes, which are located on a single electronic board (non-disposable part), connected to a personal computer via Bluetooth. The disposable part consists of a chip containing the fluidic connections for microdialysis, two fluidic channels acting as optical transmission cells and total internally reflecting mirrors for in- and out-coupling of the LED light to the chip and to the detectors. The sensor is combined with an intraveneous microdialysis to separate the glucose from the cells and proteins in the blood and operates without any chemical consumption. In vitro measurements showed a linear relationship between glucose concentration and the integrated difference signal with a coefficient of determination of 99 % in the relevant physiological concentration range from 0 to 400 mg/dl. In vivo measurements on 10 patients showed that the NIR-CGM sensor data reflects the blood reference values adequately, if a proper calibration and signal drift compensation is applied. The MARE (mean absolute relative error) value taken over all patient data is 13.8 %. The best achieved MARE value is at 4.8 %, whereas the worst is 25.8 %, with a standard deviation of 5.5 %. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.