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Intelligent Home Monitoring
The main goal of this project is to facilitate high-quality care and explore evidences of new health conditions of the patients which could result in reducing the readmission to hospital after discharge.
It also applies precise evidence-based economic analytics to evaluate the level of success. The health condition of the patient is constantly and precisely monitored to allow for sending timely medical instructions. Also, applying different real-time machine learning algorithms allows for extracting different behavior patterns, performing personalized analysis, and making knowledge-driven medical decisions. The signals from a comprehensive set of sensors will be collected and forwarded to the infrastructure to be analyzed by a variety of big data analytics solutions to extract dynamic behavior patterns. Our intelligent decision system will assist the physician for more knowledge-driven decision making.
We use advanced AR/VR techniques to enhance the user interactions with the system. The provided solutions will be applied on several volunteered residents in our collaborator retirement homes community and the final approved systems will be provided to the larger community. Our team in geriatric medicine ensure a non-intrusive and consent-based approach to the volunteered elderly residents.
Publications
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B. Eapen, N. Archer, K. Sartipi | February 2021 | Journal of JMIR Dermatol 2020
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B. Eapen, K. Sartipi, N. Archer | May 2020 | ArXiv.org
Intelligent Home Monitoring Team
Special thanks to the close collaboration with East Carolina University, Georgia State University & Cypress Glen Retirement Community



Other projects
Clinical Decision System
Medical Informatics
A multi-disciplinary research initiative on Information and System Intelligence research.