دورية أكاديمية

Non-invasive platform to estimate fasting blood glucose levels from salivary electrochemical parameters

التفاصيل البيبلوغرافية
العنوان: Non-invasive platform to estimate fasting blood glucose levels from salivary electrochemical parameters
المؤلفون: Sarul Malik, Harsh Parikh, Neil Shah, Sneh Anand, Shalini Gupta
المصدر: Healthcare Technology Letters (2019)
بيانات النشر: Wiley, 2019.
سنة النشر: 2019
المجموعة: LCC:Medical technology
مصطلحات موضوعية: electrochemical sensors, graphical user interfaces, blood, diseases, sugar, calcium, patient diagnosis, potassium, sodium, pH measurement, medical computing, electrochemical properties, FBGL determination process, painless FBGL estimation, noninvasive platform, fasting blood glucose levels, salivary electrochemical parameters, metabolic disorder, proxy biofluid, portable sensors, ionic concentrations, diabetes, K^+, Na^+, Ca^2+, Medical technology, R855-855.5
الوصف: Diabetes is a metabolic disorder that affects more than 400 million people worldwide. Most existing approaches for measuring fasting blood glucose levels (FBGLs) are invasive. This work presents a proof-of-concept study in which saliva is used as a proxy biofluid to estimate FBGL. Saliva collected from 175 volunteers was analysed using portable, handheld sensors to measure its electrochemical properties such as conductivity, redox potential, pH and K^+, Na^+ and Ca^2+ ionic concentrations. These data, along with the person's gender and age, were trained and tested after casewise annotation with their true FBGL values using a set of mathematical algorithms. An accuracy of 87.4 ± 1.7% and a mean relative deviation of 14.1% (R^2 = 0.76) was achieved using a mathematical algorithm. All parameters except the gender were found to play a key role in the FBGL determination process. Finally, the individual electrochemical sensors were integrated into a single platform and interfaced with the authors’ algorithm through a simple graphical user interface. The system was revalidated on 60 new saliva samples and gave an accuracy of 81.67 ± 2.53% (R^2 = 0.71). This study paves the way for rapid, efficient and painless FBGL estimation from saliva.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2053-3713
العلاقة: https://digital-library.theiet.org/content/journals/10.1049/htl.2018.5081Test; https://doaj.org/toc/2053-3713Test
DOI: 10.1049/htl.2018.5081
الوصول الحر: https://doaj.org/article/9344c7c7baa84e2180a0e472fa083b4eTest
رقم الانضمام: edsdoj.9344c7c7baa84e2180a0e472fa083b4e
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20533713
DOI:10.1049/htl.2018.5081