Abstract
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.
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Acknowledgments
Project CloudUPDRS: Big Data Analytics for Parkinson’s Disease patient stratification is supported by Innovate UK (Project Number 102160). The project partners would also like to thank Parkinson’s UK for providing access to their online forums and assisting with the recruitment of survey participants.
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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Kueppers, S. et al. (2017). From Wellness to Medical Diagnostic Apps: The Parkinson’s Disease Case. In: Giokas, K., Bokor, L., Hopfgartner, F. (eds) eHealth 360°. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 181. Springer, Cham. https://doi.org/10.1007/978-3-319-49655-9_46
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DOI: https://doi.org/10.1007/978-3-319-49655-9_46
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