Sotiriadis, Stelios and Thermolia, C. and Bei, E. and Stravoskoufos, K. and Petrakis, E. (2015) Designing a patient monitoring system using Cloud and Semantic web technologies. International Journal of Medical and Health Sciences 9 (5), pp. 1117-1124. ISSN 2277-4505.
![[img]](https://eprints.bbk.ac.uk/style/images/fileicons/text.png) |
Text
Designing-a-Patient-Monitoring-System-Using-Cloud-and-Semantic-Web-Technologies.pdf - Published Version of Record Restricted to Repository staff only Download (1MB) | Request a copy |
Abstract
Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called affective disorders, which is characterized by great mood swings. We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s non- response to treatment. We propose an architecture as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support
Metadata
| Item Type: | Article |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Research Centres and Institutes: | Birkbeck Knowledge Lab |
| Depositing User: | Stelios Sotiriadis |
| Date Deposited: | 08 Jun 2018 13:45 |
| Last Modified: | 09 Aug 2023 12:43 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/21910 |
Statistics
Additional statistics are available via IRStats2.
Archive Staff Only (login required)
