NDLI: On line - Affective state reporting device: A tool for evaluating affective state inference systems

Content Provider	IEEE Xplore Digital Library
Author	Zoghbi, S. Kulić, D. Croft, E. Van der Loos, M.
Copyright Year	2009
Description	Author affiliation: Dept. of Mechano-Inf., Univ. of Tokyo, Tokyo, Japan (Kulić, D.) \|\| Dept. of Mech. Eng., Univ. of British Columbia, Vancouver, BC, Canada (Zoghbi, S.; Croft, E.; Van der Loos, M.)
Abstract	The monitoring of human affective state is a key part of developing responsive and naturally behaving human-robot interaction systems. However, evaluation and calibration of physiologically monitored affective state data is typically done using offline questionnaires and user reports. In this paper we investigate the use of an online-device for collecting real-time user reports of affective state during interaction with a robot. These reports are compared to both previous survey reports taken after the interaction, and the affective states estimated by an inference system. The aim is to evaluate and characterize the physiological signal-based inference system and determine which factors significantly influence its performance. This analysis will be used in future work, to fine tune the affective estimations by identifying what kind of variations in physiological signals precede or accompany the variations in reported affective states.
Sponsorship	IEEE Robotics Autom. Soc.
Starting Page	311
Ending Page	312
File Size	433289
Page Count	2
File Format	PDF
ISBN	9781605584041
ISSN	21672148
e-ISBN	9781605584041
DOI	10.1145/1514095.1514191
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Association for Computing Machinery, Inc. (ACM)
Subject Keyword	Human's Responses to Robots - Affective responses Physiological signal monitoring Humans Estimation Human-robot interaction Educational institutions Biomedical monitoring Mechanical engineering Affective state estimation Robots Monitoring
Content Type	Text
Resource Type	Article

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