Centre for Biomedical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India; Department of Biomedical Engineering, All India Institute of Medical Sciences, New Delhi, 110029, India.
Centre for Biomedical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India; Department of Biomedical Engineering, All India Institute of Medical Sciences, New Delhi, 110029, India.
Anal Chim Acta. 2017 Dec 15;996:54-63. doi: 10.1016/j.aca.2017.10.003. Epub 2017 Oct 17.
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.
本工作开发了一种使用唾液样本和智能手机的非侵入式光学葡萄糖生物传感器。该传感器采用简单的方法制备，将葡萄糖氧化酶和 pH 响应染料固定在滤纸基带上。当与唾液中的葡萄糖反应时，传感器条带会发生颜色变化，并且颜色变化可以通过智能手机摄像头通过 RGB 分析进行检测。该独立式生物传感器在 20 秒的响应时间内具有良好的灵敏度和低干扰性。我们使用了各种改进方法，例如使用斜率法代替差分响应；使用响应 pH 指示剂，并对智能手机应用程序进行了多次调整。使用带有斜率的加标唾液样本进行校准（R+G+B）像素显示出指数增长的校准曲线，线性检测范围为 50-540mg/dL，灵敏度为 0.0012 像素 sec/mg dL，LOD 为 24.6mg/dL。该生物传感器在健康和糖尿病患者中进行了临床验证，根据性别、年龄、糖尿病状态等进行了分类，并建立了血液和唾液葡萄糖之间的相关性，以更好地标准化传感器。在健康个体中，血液和唾液葡萄糖之间的相关性为 0.44，而在糖尿病前期和糖尿病患者中，相关性分别为 0.64 和 0.94。开发的生物传感器有可能用于大规模诊断糖尿病，特别是在由于医疗费用高而禁止人们进行常规分析的地区。除此之外，用户只需一部智能手机和一个一次性低成本测试条即可进行此测量。
