Abstract
Modern lifestyle, swift adoption of fast-food diet and various environmental changes causing chronic life-threatening diseases stimulates a real necessity of advancements in built-in Internet technology for remote healthcare. Proposed work discourses an IoT paradigm comprising of Wireless Health Sensors (WHS) that allows us to observe essentially continuous monitorable and/or should be monitored biometric parameters like pulse rate, pulmonary functional quality, blood pressure, body temperature, electro cardio activity, etc., which in turn helps us for self-evaluation and control future severity by predictive analysis via smart healthcare systems in a long run diagnostic procedure by a medical practitioner. The work addresses the development of an Arduino-based all-in-one cost-effective, miniaturized Wireless Intelligent Embedded Healthcare Device (WIEHD) that can provide home-based health services to the patient. The sensors are connected to Arduino to track the status which is interfaced to a display as well as Wi-Fi connection in order to transmit collected data and receive user requests. The parameters can be monitored from a smartphone application. This system is based on a cloud platform and keeps track of the device data on daily basis. This data is shared with doctors through a website where the doctor can analyze the condition of the patient and provide further details online and intimate patient about future severity well in time.
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Ethical approval and informed consent All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors, and informed consent was obtained from all individual participants included in the study.
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Aski, V.J., Sonawane, S.S., Soni, U. (2019). IoT Enabled Ubiquitous Healthcare Data Acquisition and Monitoring System for Personal and Medical Usage Powered by Cloud Application: An Architectural Overview. In: Kalita, J., Balas, V., Borah, S., Pradhan, R. (eds) Recent Developments in Machine Learning and Data Analytics. Advances in Intelligent Systems and Computing, vol 740. Springer, Singapore. https://doi.org/10.1007/978-981-13-1280-9_1
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