Document details

User friendly knowledge acquisition system for medical devices actuation

Author(s): Costa, Nuno Miguel Cerqueira da

Date: 2012

Persistent ID:

Origin: Repositório Institucional da UNL

Subject(s): Human computer interaction; Knowledge acquisition system; Ontology; Schema language; JSON; Electrostimulation


Internet provides a new environment to develop a variety of applications. Hence, large amounts of data, increasing every day, are stored and transferred through the internet. These data are normally weakly structured making information disperse, uncorrelated, non-transparent and difficult to access and share. Semantic Web, proposed by theWorldWideWeb Consortium (W3C), addresses this problem by promoting semantic structured data, like ontologies, enabling machines to perform more work involved in finding, combining, and acting upon information on theWeb. Pursuing this vision, a Knowledge Acquisition System (KAS) was created, written in JavaScript using JavaScript Object Notation (JSON) as the data structure and JSON Schema to define that structure. It grants new ways to acquire and store knowledge semantically structured and human readable. Plus, structuring data with a Schema generates a software robust and error – free. A novel Human Computer Interaction (HCI) framework was constructed employing this KAS, allowing the end user to configure and control medical devices. To demonstrate the potential of this tool, we present the configuration and control of an electrostimulator. Nowadays, most of the software for Electrostimulation is made with specific purposes, and in some cases they have complicated user interfaces and large, bulky designs that deter usability and acceptability. The HCI concedes the opportunity to configure and control an electrostimulator that surpasses the specific use of several electrostimulator software. In the configuration the user is able to compile different types of electrical impulses (modes) in a temporal session, automating the control, making it simple and user-friendly.

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Document Type Master thesis
Language English
Advisor(s) Gamboa, Hugo
Contributor(s) Costa, Nuno Miguel Cerqueira da
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