Microfluidic biosensors for intelligent metabolite monitoring

Nitin Radhakrishnan; Jongwon Park; Chang-Soo Kim

doi:10.1117/12.737092

5 October 2007 Microfluidic biosensors for intelligent metabolite monitoring

Nitin Radhakrishnan, Jongwon Park, Chang-Soo Kim

Proceedings Volume 6759, Smart Biomedical and Physiological Sensor Technology V; 67590U (2007) https://doi.org/10.1117/12.737092
Event: Optics East, 2007, Boston, MA, United States

Abstract

We present an intelligent microfluidic system with oxidase enzyme coupled biosensors. Baseline (zero-value) drift and sensitivity degradation are two common problems related with biosensors. In order to overcome these problems there is a great need for integrating an on-demand, in situ self-diagnosis and self-calibration unit along with the sensor. Utilizing the microfluidic technology, we explore the feasibility of implementing this function without any externally coupled bulky apparatus. A microsystem including a microfluidic channel and calibration electrodes are prepared by microfabrication techniques. A novel method of using hydrogen and oxygen bubbles generated by electrolysis of water is used to saturate the solution with these gases in the microfluidic channel where the biosensor is placed. The hydrogen bubble provides oxygen-depleted microenvironment to conduct a zero-value calibration procedure for the sensor. The oxygen bubble provides high sensitivity and constant oxygen background environment to allow stable enzyme reactions that is not limited or perturbed by the fluctuation of background oxygen in sample solutions. Commercial oxygen sensors and pH sensors are used to confirm whether saturation or depletion of oxygen has occurred with minimum local pH change near the sensor during the electrolytic bubble generation. The glucose data obtained from the experiments assure that our proposed method is promising to overcome the above mentioned two problems.

Citation Download Citation

Nitin Radhakrishnan, Jongwon Park, and Chang-Soo Kim "Microfluidic biosensors for intelligent metabolite monitoring", Proc. SPIE 6759, Smart Biomedical and Physiological Sensor Technology V, 67590U (5 October 2007); https://doi.org/10.1117/12.737092

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