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HCI Int 2018 Posters Ext Abstr (2018). 2018 Jul;851:349-355. doi: 10.1007/978-3-319-92279-9_47. Epub 2018 Jun 7.

VEO-Engine: Interfacing and Reasoning with an Emotion Ontology for Device Visual Expression.

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University of Texas Health Science Center, Houston, TX 77030, USA.
Johns Hopkins University, Baltimore, MD 21218, USA.
Lousiana Tech University, Ruston, LA 71272, USA.


In order for machines to understand or express emotion to users, the specific emotions must be formally defined and the software coded to how those emotions are to be expressed. This is particularly important if devices or computer-based tools are utilized in clinical settings, which may be stressful for patients and where emotions can dominate their decision making. We have reported our development and feasibility results of an ontology, Visualized Emotion Ontology (VEO), that links abstract visualizations that express specific emotions. Here, we used VEO with the VEO-Engine, a software API package that interfaces with the VEO. The VEO-Engine was developed in Java using Apache Jena and OWL-API. The software package was tested on a Raspberry Pi machine with a small touchscreen display that linked each visualization to an emotion. The VEO-Engine stores input parameters of emotional situations and valences to reason and interpret users' emotions using the ontology-based reasoner. With this software, devices can interfaced wirelessly, so smart devices with visual displays can interact with the ontology. By means of the VEO-Engine, we show the portability and usability of the VEO in human-computer interaction.


Emotions; Ontology; Semantic web; mHealth Affective computing

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