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Special Sessions

Special sessions are very small and specialized events to be held during the conference as a set of oral and poster presentations that are highly specialized in some particular theme or consisting of the works of some particular international project. The goal of special sessions (minimum 4 papers; maximum 9) is to provide a focused discussion on innovative topics. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on digital support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), DBLP, EI (Elsevier Engineering Village Index), Scopus, Semantic Scholar and Google Scholar.


OASIS 2014Special Session on recognition Of Affect Signals from physiologIcal data for Social robots
Chair(s): Ginevra Castellano, Iolanda Leite and Ana Paiva

Special Session on recognition Of Affect Signals from physiologIcal data for Social robots - OASIS 2014


Ginevra Castellano
University of Birmingham
United Kingdom
Iolanda Leite
INESC-id, Instituto Superior Técnico
Ana Paiva
INESC-id, Instituto Superior Técnico

With the recent advances in biosensor technology, small, wireless and inexpensive sensors are becoming increasingly more popular, as users can wear these sensors while performing a large set of activities without becoming intrusive. Examples of such devices include Affectiva’s Q Sensor1 and edaPlux2, which measure arousal through skin conductance, a form of electrodermal activity linked to states of excitement, attention, anxiety or cognitive load. Socially and affect-aware robots, that can capture some of these states from the user, are considered to be more effective in engaging users for longer periods of time. For these reasons, research on physiological signals has been attracting the attention of researchers in the Human-Robot Interaction (HRI) community.

1 http://www.affectiva.com/q-sensor/
2 http://www.plux.info/EDA