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- M. Tech. in Automotive Engineering -Postgraduate
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Publication Type : Journal Article
Url : https://journal.esrgroups.org/jes/article/view/7016/4839
Campus : Nagercoil
School : School of Computing
Abstract : From intrusive implanted devices to more approachable exterior and edible technology, wearable sensors have attracted a number of customers. Implantable devices that are extremely expensive and invasive, which restricts their use even though they offer vital life support. Conversely, ingestible sensors with pills present a more cost-effective and minimally intrusive alternative. This work introduces a unique ingestible sensor that can track real-time electrolyte balance and hydration leveling’sin addition to gastrointestinal health parameters including gut motility and pH levels. To analyze the sensor data, we utilised a novel Concatenated Long Short-Term Memory (CLSTM) deep learning algorithm. This allows the users to accurately identify electrolytic imbalanceand dehydrating stagesearly on, as well as the gastrointestinal diseases like Crohn's disease and irritable bowel syndromes. The proposed results givesthat our adaptable edible sensor has beena useful tool for managing gastrointestinal health as well as optimizing hydration because it not only offers thorough health in detectionsbut also makes properactions easier. This strategy is having thepotential to improve overall health management, tailored treatment and early detection in a variety of groups.