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A cooperative decision support system for children’s neurodevelopment monitoring
Department of Telematic and Electronic Engineering, Technical University of Madrid, Carretera de Valencia KM7, Madrid, Spain.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Department of Telematic and Electronic Engineering, Technical University of Madrid, Carretera de Valencia KM7, Madrid, Spain.
Department of Telematic and Electronic Engineering, Technical University of Madrid, Carretera de Valencia KM7, Madrid, Spain.
Legamar School, Madrid, Spain.
2016 (English)In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2016, Vol. 169, p. 461-466Conference paper, Published paper (Refereed)
Abstract [en]

Decision Support Systems can enhance e-Health monitoring and IoT scenarios on the early detection of neurodevelopmental disorders in children. Thus, Ambient Intelligence could support innovative application domains like motor or cognitive impairments’ detection at the home environment. The paper describes the design of an innovative cooperative system (Galatea) that supports the refinement process of a Knowledge Base expressed as an OWL ontology. The ontology supports decision-making process and is the core of: (1) a Web-Based Smart System aimed to enhance the screening of language disorders at medical centers and schools by fostering the identification of a developmental disorders before 4 years old of age; (2) a set of child smart care services that use Ambient Intelligent paradigm for early attention of motor impairments in children who are often not diagnosed or treated by health care entities.

Place, publisher, year, edition, pages
2016. Vol. 169, p. 461-466
Keywords [en]
Disabilities, E-health, Healthcare services, Smart systems, Artificial intelligence, Decision making, Decision support systems, Diagnosis, Health care, Knowledge based systems, Ambient intelligence, Co-operative systems, Decision making process, Developmental disorders, E health, Smart System, Internet of things
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-34535DOI: 10.1007/978-3-319-47063-4_49ISI: 000398616500049Scopus ID: 2-s2.0-85000470504ISBN: 9783319470627 (print)OAI: oai:DiVA.org:mdh-34535DiVA, id: diva2:1059180
Conference
27 October 2015 through 29 October 2015
Available from: 2016-12-22 Created: 2016-12-22 Last updated: 2017-05-19Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf