From Wellness to Medical Diagnostic Apps: The Parkinson’s Disease Case

Stefan Kueppers; Ioannis Daskalopoulos; Ashwani Jha; Nikos Fragopanagos; Panagiotis Kassavetis; Effrosyni Nomikou; Tabish Saifee; John Rothwell; Kailash Bhatia; Marco Luchini; Marco Iannone; Theano Moussouri; George Roussos

eHealth 360°. International Summit on eHealth, Budapest, Hungary, June 14-16, 2016, Revised Selected Papers

Research Article

From Wellness to Medical Diagnostic Apps: The Parkinson’s Disease Case

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@INPROCEEDINGS{10.1007/978-3-319-49655-9_46,
    author={Stefan Kueppers and Ioannis Daskalopoulos and Ashwani Jha and Nikos Fragopanagos and Panagiotis Kassavetis and Effrosyni Nomikou and Tabish Saifee and John Rothwell and Kailash Bhatia and Marco Luchini and Marco Iannone and Theano Moussouri and George Roussos},
    title={From Wellness to Medical Diagnostic Apps: The Parkinson’s Disease Case},
    proceedings={eHealth 360°. International Summit on eHealth, Budapest, Hungary, June 14-16, 2016, Revised Selected Papers},
    proceedings_a={EHEALTH360},
    year={2017},
    month={1},
    keywords={},
    doi={10.1007/978-3-319-49655-9_46}
}

Stefan Kueppers
Ioannis Daskalopoulos
Ashwani Jha
Nikos Fragopanagos
Panagiotis Kassavetis
Effrosyni Nomikou
Tabish Saifee
John Rothwell
Kailash Bhatia
Marco Luchini
Marco Iannone
Theano Moussouri
George Roussos
Year: 2017
From Wellness to Medical Diagnostic Apps: The Parkinson’s Disease Case
EHEALTH360
Springer
DOI: 10.1007/978-3-319-49655-9_46

Stefan Kueppers^,*, Ioannis Daskalopoulos¹, Ashwani Jha², Nikos Fragopanagos³, Panagiotis Kassavetis, Effrosyni Nomikou⁴, Tabish Saifee², John Rothwell², Kailash Bhatia², Marco Luchini⁵, Marco Iannone³, Theano Moussouri, George Roussos¹

1: Birkbeck College, University of London
2: University College London
3: re:technica Ltd.
4: Audience Focus Ltd.
5: Benchmark Performance Ltd.

*Contact email: stefan@dcs.bbk.ac.uk

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.

Published: 2017-01-05
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-319-49655-9_46