Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/27910
Title: Integration of IoMT Sensors’ Data from Mobile Applications into Cloud Based Personal Health Record
Authors: Beredimas, Nikolaos
Maglaveras, Nicos
Trajkovik, Vladimir
Issue Date: 11-Apr-2022
Publisher: Springer Nature
Journal: ICT Innovations 2021. Digital Transformation: 13th International Conference, ICT Innovations 2021, Virtual Event, September 27–28, 2021, Revised Selected Papers
Abstract: Mobile applications for vital signs measurement are popular in ambient assisted living environments. They typically include various wearables and devices with their applications connected with the production company with some security preferences. When a manufacturer develops and markets a specific sensor, a smartphone application is developed. Many of the sensors and devices are secured and can work only with its host application developed by the manufacturer. However, for these sensors and devices related to a patient’s cloud-based Personal Health Record (PHR), different mobile applications must be created to connect all additional wearables or IoT-based medical sensors or devices to the appropriate cloud-based PHR. All data from these mobile applications needs be collected into the PHR database securely and in time to store medical information for the patient’s health in the PHR. This paper presents the integration of two types of mobile applications–for medical professionals and citizens with the PHR, intended for the Cross4all project. The paper explains how the mobile application is integrated with different sensors and devices and the cloud PHR. We also describe the challenges that have arisen from the pilot project implementation and solutions. The presented concept improves cross-border evidence-based healthcare and integrates the e-prescription and e-referral system intended to solve some cross-border healthcare problems for foreign citizens.
URI: http://hdl.handle.net/20.500.12188/27910
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles

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