Prediabetes often develops without symptoms, meaning a person can be\nat high risk of developing diabetes mellitus without realising it. This\nproblem prompted four students at Universitas Gadjah Mada (UGM) to\ndevelop a screening device that offers a different approach: detecting\nprediabetes risk through saliva without drawing blood.<\/p>\n
The innovation, named Glicovia, combines electrochemical sensors,\nartificial intelligence (AI), and the Internet of Things (IoT) to read a\nnumber of indicators in saliva related to prediabetes risk.<\/p>\n
The development team consists of Alya Ramadhani as chair, Naefi\nLuthfia Zahra and Emmily Martha Renaunia from the UGM Faculty of\nDentistry, and Hendra Kurnia Maliqi from the UGM Faculty of Engineering.\nThey developed Glicovia under the supervision of Dr.\u00a0drg. Indra\nBramanti, M.Sc., Sp.KGA(K).<\/p>\n
Alya said the idea stemmed from diabetes remaining a health challenge\nin Indonesia. According to data underpinning the team\u2019s development,\naround 20.4 million Indonesians aged 20\u201379 were living with diabetes in\n2024. At the same time, an estimated 29.8 million people were in a\nprediabetic state or had impaired glucose tolerance.<\/p>\n
\u201cPrediabetes is a phase when blood glucose levels are above normal\nbut do not yet meet the criteria for diabetes. This condition generally\ncauses no symptoms, so sufferers are often unaware of it,\u201d Alya said in\na statement on 26 July.<\/p>\n
Yet this phase represents one of the opportunities to intervene\nbefore a person develops type 2 diabetes mellitus. Lifestyle changes and\nearly treatment can help reduce that risk.<\/p>\n
The problem is that health check-ups for some people are still\nsynonymous with blood sampling procedures. Glicovia seeks to shift that\napproach by using saliva as the test material.<\/p>\n
The process begins when the user places saliva on a sensor on the\ndevice. The electrochemical sensor then measures a number of indicators,\nincluding glucose, salivary fructosamine, and acidity or pH levels.<\/p>\n
The measurement data is then processed using an artificial\nintelligence model based on a Support Vector Machine (SVM) to produce an\nassessment of prediabetes risk level.<\/p>\n
The results can then be transmitted to an application or digital\nplatform through IoT integration. With this mechanism, users not only\nreceive test results but can also store and monitor their examination\nhistory digitally.<\/p>\n
\u201cWe want to present a screening method that is not only accurate but\nalso more comfortable. By using saliva as a test sample and integrating\nartificial intelligence and IoT, we hope early detection of prediabetes\ncan be carried out more widely so that the risk of developing diabetes\ncan be reduced from the outset,\u201d Alya said.<\/p>\n
Nevertheless, Glicovia is not yet at the stage of being ready for use\nas a public diagnostic device. Its development has only reached around\n70 percent.<\/p>\n
The team has completed the system design, sensor development, IoT\nintegration, and AI model development. The next stage is validation\nusing real saliva samples to test the accuracy and reliability of the\nresults obtained by the device.<\/p>\n
The validation stage is important because the ability to detect\ncertain indicators in saliva does not automatically make a device a\ndiagnostic tool. The system needs to undergo testing to determine how\nconsistent the measurement results are and how well the model identifies\nrisk.<\/p>\n
In addition to comfort, the UGM students have also incorporated the\nconcept of green diagnostics into Glicovia\u2019s development. Using saliva\nas a sample has the potential to reduce a number of consumables used in\nblood-based examination procedures.<\/p>\n
Meanwhile, IoT integration is designed so that examination data can\nbe stored digitally, enabling continuous health monitoring.<\/p>\n
Glicovia was developed through funding from the 2026 Student\nCreativity Programme for Creative Works (PKM-KC), supported by the\nDirectorate General of Higher Education, Research, and Technology\nthrough the Directorate of Learning and Student Affairs.<\/p>\n
The team aims to continue developing the device through to the\nNational Student Scientific Week (PIMNAS). However, their long-term\ntarget is not merely a student competition, but to present a more\npractical screening method that can be used to expand access to diabetes\nrisk detection, particularly in the stage before the disease\ndevelops.<\/p>\n
If the validation process shows adequate results, the saliva-based\napproach could potentially become an alternative for more comfortable\nhealth screening. In this way, efforts to detect diabetes risk would not\ndepend solely on examinations conducted once a person has developed\nsymptoms or requires further testing.<\/p>", "url": "https:\/\/jawawa.id\/newsitem\/no-need-for-finger-pricks-ugm-students-develop-prediabetes-detection-device-from-saliva-1788717015", "image": "" }, "sponsor": "Okusi Associates", "sponsor_url": "https:\/\/okusiassociates.com" }