Wearable Biosensors for Continuous Glucose Monitoring Using Flexible Electronics and IoT Integration

Wearable Biosensors for Continuous Glucose Monitoring Using Flexible Electronics and IoT Integration | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Wearable Biosensors for Continuous Glucose Monitoring Using Flexible Electronics and IoT Integration Tejaswi Rupakula, Kishore Kunal, Murugadoss R, Rupesh Gupta, Sowjanya Ramisetty, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9221803/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 15 You are reading this latest preprint version Abstract Continuous glucose monitoring (CGM) plays a vital role in managing diabetes, a chronic condition affecting millions globally. Traditional glucose monitoring methods often require invasive procedures, resulting in discomfort and poor patient compliance. To address this limitation, this study explores the development of a wearable biosensor system using flexible electronics integrated with IoT technology for non-invasive, real-time glucose monitoring. The primary aim is to design a smart, cost-effective, and accurate biosensor for early detection and continuous tracking of glucose levels. Clinical data were collected from 150 patients with Type 1 and Type 2 diabetes across three diabetic care centers over a six-month period. Saliva,blood, sweat, and urine samples were used as non-invasive biofluids to extract glucose concentration data. The wearable biosensor, embedded with flexible electrochemical sensors and microfluidic channels, continuously monitored glucose levels. IoT modules enabled secure wireless data transmission to cloud-based platforms for remote healthcare access. Measurement tools included a flexible graphene-based electrode coupled with an enzymatic glucose oxidase (GOx) sensor for accurate biochemical detection. Data were validated against standard glucometer readings using paired t-tests and Bland-Altman plots. Performance metrics such as Mean Absolute Relative Difference (MARD), sensitivity, specificity, and RMSE were evaluated to assess reliability. This research confirms the feasibility of integrating flexible biosensors with IoT for real-time diabetic monitoring, promoting proactive care, enhanced user comfort, and scalability in digital health systems. Continuous Glucose Monitoring Wearable Biosensors Flexible Electronics IoT Integration Diabetes Management Non-Invasive Sensing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 17 May, 2026 Reviews received at journal 10 May, 2026 Reviews received at journal 09 May, 2026 Reviews received at journal 08 May, 2026 Reviews received at journal 06 May, 2026 Reviews received at journal 01 May, 2026 Reviewers agreed at journal 30 Apr, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers agreed at journal 29 Apr, 2026 Reviewers invited by journal 29 Apr, 2026 Editor assigned by journal 27 Mar, 2026 Submission checks completed at journal 26 Mar, 2026 First submitted to journal 25 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9221803","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635657137,"identity":"ee79fdb7-283d-42a0-9bb1-fc4f2ba8779e","order_by":0,"name":"Tejaswi Rupakula","email":"","orcid":"","institution":"Engineering Odessa College","correspondingAuthor":false,"prefix":"","firstName":"Tejaswi","middleName":"","lastName":"Rupakula","suffix":""},{"id":635657140,"identity":"e78e68d8-e833-479e-9dcf-3ff0f33f85b8","order_by":1,"name":"Kishore Kunal","email":"","orcid":"","institution":"Loyola Institute of Business 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Traditional glucose monitoring methods often require invasive procedures, resulting in discomfort and poor patient compliance. To address this limitation, this study explores the development of a wearable biosensor system using flexible electronics integrated with IoT technology for non-invasive, real-time glucose monitoring. The primary aim is to design a smart, cost-effective, and accurate biosensor for early detection and continuous tracking of glucose levels. Clinical data were collected from 150 patients with Type 1 and Type 2 diabetes across three diabetic care centers over a six-month period. Saliva,blood, sweat, and urine samples were used as non-invasive biofluids to extract glucose concentration data. The wearable biosensor, embedded with flexible electrochemical sensors and microfluidic channels, continuously monitored glucose levels. IoT modules enabled secure wireless data transmission to cloud-based platforms for remote healthcare access. 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