Smartphone based non-invasive salivary glucose biosensor.

The present work deals with the development of a non-invasive optical glucose biosensor using saliva samples and a smartphone. The sensor was fabricated with a simple methodology by immobilization of Glucose oxidase enzyme along with a pH responsive dye on a filter paper based strip. The strip changes color upon reaction with glucose present in saliva and the color changes were detected using a smartphone camera through RGB profiling. This standalone biosensor showed good sensitivity and low interference while operating within 20 s response time. We used various means for improvements such as the use of slope method instead of differential response; use of a responsive pH indicator and made numerous tweaks in the smartphone app. Calibration with spiked saliva samples with slopes for (R + G + B) pixels revealed an exponentially increasing calibration curve with a linear detection range of 50-540 mg/dL, sensitivity of 0.0012 pixels sec/mg dL and LOD of 24.6 mg/dL. The biosensor was clinically validated on both healthy and diabetic subjects divided into several categories based on sex, age, diabetic status etc. and correlation between blood and salivary glucose has been established for better standardization of the sensor. Correlation of 0.44 was obtained between blood and salivary glucose in healthy individuals whereas it was 0.64 and 0.94 in case of prediabetic and diabetic patients respectively. The developed biosensor has the potential to be used for mass diagnosis of diabetes especially in such areas where people remain prohibited from routine analysis due to high healthcare cost. Apart from that, a smartphone would be the only device the user needs for this measurement, along with a disposable low cost test strip.