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Cloud-Based Remote Processing and Data-Mining Platform for Automatic Risk Assessment in Hypertensive Patients

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Ambient Assisted Living and Daily Activities (IWAAL 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8868))

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Abstract

The aim of this paper is to describe the design and the preliminary validation of a platform developed to collect and automatically analyze biomedical signals for risk assessment of cardiovascular events in hypertensive patients. This m-health platform, based on cloud computing, was designed to be flexible, extensible, and transparent, and to provide proactive remote monitoring via data-mining functionalities. Clinical trials were designed to test the system. The data of a retrospective study were adopted to train and test the platform. The developed system was able to predict a future vascular event within the next 12 months with an accuracy rate of 67%. In an ongoing prospective trial, almost all the recruited patients accepted favorably the system with a limited rate of inadherences causing of data losses (<20%). The developed platform supported clinical decision by processing tele-monitored data and providing quick and accurate risk assessment of cardiovascular events.

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Author information

Authors and Affiliations

  1. Multidisciplinary Department of Medical, Surgical and Dental Sciences, Second University of Naples, Naples, Italy

    Paolo Melillo

  2. SHARE Project, Italian Ministry of Education, Research and University, Rome, Italy

    Paolo Melillo, Paolo Scala, Filippo Crispino & Leandro Pecchia

  3. School of Engineering, University of Warwick, Coventry, UK

    Leandro Pecchia

Authors
  1. Paolo Melillo
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  2. Paolo Scala
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  3. Filippo Crispino
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  4. Leandro Pecchia
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Editor information

Editors and Affiliations

  1. School of Engineering, University of Warwick, CV4 7AL, Coventry, UK

    Leandro Pecchia

  2. School of Computer Science and Informatics, De Montfort University, The Gateway, LE1 9BH, Leicester, UK

    Liming Luke Chen

  3. Institute, School of Computing and Mathematics, University of Ulster, Computer Science Research, Jordanstown Campus, Shore Road, BT37 0QB, Newtownabbey, UK

    Chris Nugent

  4. Escuela Superior de Informática, Castilla La Mancha University, Paseo de la Universidad 4, 13071, Ciudad, Real, Spain

    José Bravo

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Melillo, P., Scala, P., Crispino, F., Pecchia, L. (2014). Cloud-Based Remote Processing and Data-Mining Platform for Automatic Risk Assessment in Hypertensive Patients. In: Pecchia, L., Chen, L.L., Nugent, C., Bravo, J. (eds) Ambient Assisted Living and Daily Activities. IWAAL 2014. Lecture Notes in Computer Science, vol 8868. Springer, Cham. https://doi.org/10.1007/978-3-319-13105-4_24

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  • DOI: https://doi.org/10.1007/978-3-319-13105-4_24

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13104-7

  • Online ISBN: 978-3-319-13105-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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