Abdur Rahman, Md, Rashid, Mamun, Le Kernec, Julien, Philippe, Bruno, Barnes, Stuart, Fioranelli, Francesco, Yang, Shufan, Romain, Olivier, Abbasi, Qammer, Loukas, George ORCID: 0000-0003-3559-5182 and Imran, Muhammad (2019) A secure occupational therapy framework for monitoring cancer patients’ quality of life. Sensors, 19 (23):5258. ISSN 1424-8220 (doi:https://doi.org/10.3390/s19235258)

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Abstract

Once diagnosed with cancer, a patient goes through a series of diagnosis and tests, referred to as after cancer treatment. Due to the nature of the treatment and side effects, maintaining quality of life (QoL) in the home environment is a challenging task. Sometimes, a cancer patient’s situation changes abruptly, as the functionality of certain organs deteriorates, which affects their QoL. One way of knowing the physiological functional status of a cancer patient is to design an occupational therapy. In this paper, we propose a Blockchain and off-chain based framework which will allow multiple medical and ambient intelligent Internet of Things sensors to capture the QoL information from one’s home environment and securely share it with their community of interest. Using our proposed framework, both transactional records and multimedia big data can be shared with an oncologist or palliative care unit for real-time decision support. We have also developed Blockchain-based data analytics, which will allow a clinician to visualize the immutable history of the patient’s data available from an in-home secure monitoring system for a better understanding of a patient’s current or historical states. Finally, we will present our current implementation status, which provides significant encouragement for further development.

Item Type:	Article
Uncontrolled Keywords:	security, internet of things, medical technologies
Subjects:	Q Science > Q Science (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > Internet of Things and Security Research Centre (ISEC) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Last Modified:	04 Mar 2022 13:06
URI:	http://gala.gre.ac.uk/id/eprint/26108

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