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      A Secure Occupational Therapy Framework for Monitoring Cancer Patients’ Quality of Life †

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          Abstract

          Once diagnosed with cancer, a patient goes through a series of diagnosis and tests, which are 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.

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          Blockchain Meets IoT: An Architecture for Scalable Access Management in IoT

          Oscar Novo (2018)
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            FairAccess: a new Blockchain-based access control framework for the Internet of Things

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              Employment pathways in a large cohort of adult cancer survivors.

              Employment and work-related disability were investigated in a cohort of adult cancer survivors who were working when they were diagnosed from 1997 to 1999 with a variety of cancers. Employment from the time of diagnosis through the early years of survivorship was studied, self-reported effects of cancer survival on disability and employment were quantified, and risk factors associated with cancer-related disability and withdrawal from employment were identified. One thousand four hundred thirty-three cancer survivors were interviewed by telephone from 1 year to nearly 5 years after diagnosis. They were asked retrospectively about employment from the time of diagnosis to follow-up and about work-related disability at follow-up. They also were asked whether disabilities or reasons for quitting work were cancer-related. Return to work and quitting work were projected over time in a life-table analysis. Risk factors were identified from logit analyses. One of five survivors reported cancer-related disabilities at follow-up. Half of those with disabilities were working. A projected 13% of all survivors had quit working for cancer-related reasons within 4 years of diagnosis. More than half of survivors quit working after the first year, when three-quarters of those who stopped for treatment returned to work. Survivors of central nervous system, head and neck, and Stage IV blood and lymph malignancies had the highest adjusted risk of disability or quitting work. Cancer survival sometimes has long-term effects on employment and the ability to work. Employment outcomes can be improved with innovations in treatment and with clinical and supportive services aimed at better management of symptoms, rehabilitation, and accommodation of disabilities.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                29 November 2019
                December 2019
                : 19
                : 23
                : 5258
                Affiliations
                [1 ]Department of Cyber Security and Forensic Computing, College of Computer and Cyber Sciences (C3S), University of Prince Mugrin, Madinah 41499, Saudi Arabia
                [2 ]Consumer and Organisational Digital Analytics (CODA) Research Centre, King’s Business School, King’s College, London WC2B 4BG, UK; mamun.rashid@ 123456kcl.ac.uk (M.M.R.); stuart.barnes@ 123456kcl.ac.uk (S.J.B.)
                [3 ]James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK; Julien.LeKernec@ 123456glasgow.ac.uk (J.L.K.); Francesco.Fioranelli@ 123456glasgow.ac.uk (F.F.); Shufan.Yang@ 123456glasgow.ac.uk (S.Y.); Qammer.Abbasi@ 123456glasgow.ac.uk (Q.H.A.); Muhammad.Imran@ 123456glasgow.ac.uk (M.I.)
                [4 ]Laboratoire ETIS, Université Paris Seine, Université Cergy-Pontoise, ENSEA, CNRS, UMR8051, 95000 Paris, France; olivier.romain@ 123456u-cergy.fr
                [5 ]School of Information and Communication, University of Electronic, Science, and Technology of China, Chengdu 610000, China
                [6 ]Pneumology Department, René Dubos Hospital, 95300 Pontoise, France; bruno.philippe@ 123456ght-novo.fr
                [7 ]Computing and Mathematical Sciences, University of Greenwich, London SE1 09LS, UK; G.Loukas@ 123456greenwich.ac.uk
                Author notes
                [* ]Correspondence: m.arahman@ 123456upm.edu.sa ; Tel.: +966-5-610-617-30
                [†]

                This paper is an extended version of our paper published in Rahman, M.A.; Rashid, M.; Barnes, S.; Hossain, M.S.; Hassanain, E.; Guizani, M. An IoT and Blockchain-Based Multi-Sensory In-Home Quality of Life Framework for Cancer Patients. In Proceedings of the 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), Tangier, Morocco, 24–28 June 2019.

                Author information
                https://orcid.org/0000-0002-4105-0368
                https://orcid.org/0000-0003-2124-6803
                https://orcid.org/0000-0003-0531-2903
                https://orcid.org/0000-0002-2172-1865
                https://orcid.org/0000-0002-7097-9969
                Article
                sensors-19-05258
                10.3390/s19235258
                6928807
                31795384
                205a787d-a47c-4ae2-9c3d-019b11d730c3
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 26 September 2019
                : 22 November 2019
                Categories
                Article

                Biomedical engineering
                cyber-physical occupational therapy system,distributed medical big data,health iot sensors,therapeutic kinematic data,quality of life

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