Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
| Autor: | Thomas L. Martin, Deba Pratim Saha, R. Benjamin Knapp |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Service (business)
Continuous measurement Computer science 05 social sciences Probabilistic logic Wearable computer Virtual reality Physiological computing Affective Feedback 03 medical and health sciences 0302 clinical medicine Human–computer interaction Intelligent environment 0501 psychology and cognitive sciences Physiological Computing 050107 human factors 030217 neurology & neurosurgery |
| Zdroj: | UbiComp/ISWC Adjunct |
| Popis: | The probabilistic nature of the inferences in a context-aware intelligent environment (CAIE) renders them vulnerable to erroneous decisions resulting in wrong services. Learning to recognize a user’s negative reactions to such wrong services will enable a CAIE to anticipate a service’s appropriateness. We propose a framework for continuous measurement of physiology to infer a user’s negative-emotions arising from receiving wrong services, thereby implementing an implicit-feedback loop in the CAIE system. To induce such negative-emotions, in this paper, we present a virtualreality (VR) based experimental platform while collecting real-time physiological data from ambulatory wearable sensors. Results from the electrodermal activity (EDA) data analysis reveal patterns that correlate with known features of negative-emotions, indicating the possibility to infer service appropriateness from user’s reactions to a service, thereby closing an implicit-feedback loop for the CAIE. The authors would like to thank Institute for Creativity, Arts and Technology at Virginia Tech for supporting this project, especially Reza Tasooji and Zachary Duer for helping us model the 3D environment. |
| Databáze: | OpenAIRE |
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