Model-driven prototyping support for pervasive healthcare applications

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review

1 Citation (Scopus)

Abstract

Pervasive healthcare applications aim at improving habitability by assisting individuals in living autonomously. To achieve this goal, data on an individual's behavior and his or her environment (often collected with wireless sensors) is interpreted by machine learning algorithms; their decision finally leads to the initiation of appropriate actions, e.g., turning on the light. Developers of pervasive healthcare applications therefore face complexity stemming, amongst others, from different types of environmental and vital parameters, heterogeneous sensor platforms, unreliable network connections, as well as from different programming languages. Moreover, developing such applications often includes extensive prototyping work to collect large amounts of training data to optimize the machine learning algorithms. In this chapter the authors present a model-driven prototyping approach for the development of pervasive healthcare applications to leverage the complexity incurred in developing prototypes and applications. They support the approach with a development environment that simplifies application development with graphical editors, code generators, and pre-defined components.

Original languageEnglish
Title of host publicationPervasive and Smart Technologies for Healthcare
Subtitle of host publicationUbiquitous Methodologies and Tools
PublisherIGI Global
Pages251-281
Number of pages31
ISBN (Print)9781615207657
DOIs
Publication statusPublished - 2010

Keywords

  • wireless sensor networks
  • pervasive healthcare systems
  • model-driven development

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