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    From wellness to medical diagnostic apps: the Parkinson's Disease case

    Kueppers, Stefan and Daskalopoulos, I. and Jha, A. and Fragopanagos, N.F. and Kassavetis, P. and Nomikou, E. and Saifee, T. and Rothwell, J.C. and Bhatia, K. and Luchini, M.U. and Iannone, M. and Moussouri, T. and Roussos, George (2016) From wellness to medical diagnostic apps: the Parkinson's Disease case. In: Giokas, K. and Bokor, L. and Hopfgartner, F. (eds.) eHealth 360°: International Summit on eHealth, Budapest, Hungary, June 14-16, 2016, Revised Selected Papers. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 181. New York, U.S.: Springer, pp. 384-389. ISBN 9783319496542.

    updrs_v0.3.pdf - Author's Accepted Manuscript

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    This paper presents the design and development of the CloudUPDRS app and supporting system developed as a Class I medical device to assess the severity of motor symptoms for Parkinson’s Disease. We report on lessons learnt towards meeting fidelity and regulatory requirements; effective procedures employed to structure user context and ensure data quality; a robust service provision architecture; a dependable analytics toolkit; and provisions to meet mobility and social needs of people with Parkinson’s.


    Item Type: Book Section
    Additional Information: Series ISSN: 1867-8211. The final publication is available at Springer via the link above.
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Depositing User: George Roussos
    Date Deposited: 16 Feb 2017 15:18
    Last Modified: 09 Aug 2023 12:39


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