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Advances in Physiological ComputingPsychophysiological Feedback for Adaptive Human–Robot Interaction (HRI)

Advances in Physiological Computing: Psychophysiological Feedback for Adaptive Human–Robot... [Recent advances in robotics and sensing have given rise to a diverse set of robots and their applications. In recent years robots have increasingly applied in the service industry, search and rescue operations and therapeutic applications. The introduction of robots to interact with humans resulted in a dedicated field called human–robot interaction (HRI). Social HRI is of particular importance as it is the main focus of this chapter. This chapter presents an affect-inspired approach for social HRI. Physiological processing together with machine learning was employed to model affective states for an adaptive social HRI and its application in social interaction in the context of autism therapy was investigated.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Advances in Physiological ComputingPsychophysiological Feedback for Adaptive Human–Robot Interaction (HRI)

Part of the Human–Computer Interaction Series Book Series
Editors: Fairclough, Stephen H.; Gilleade, Kiel

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Publisher
Springer London
Copyright
© Springer-Verlag London 2014
ISBN
978-1-4471-6391-6
Pages
141 –167
DOI
10.1007/978-1-4471-6392-3_7
Publisher site
See Chapter on Publisher Site

Abstract

[Recent advances in robotics and sensing have given rise to a diverse set of robots and their applications. In recent years robots have increasingly applied in the service industry, search and rescue operations and therapeutic applications. The introduction of robots to interact with humans resulted in a dedicated field called human–robot interaction (HRI). Social HRI is of particular importance as it is the main focus of this chapter. This chapter presents an affect-inspired approach for social HRI. Physiological processing together with machine learning was employed to model affective states for an adaptive social HRI and its application in social interaction in the context of autism therapy was investigated.]

Published: Mar 27, 2014

Keywords: Autism Spectrum Disorder; Affective State; Emotion Recognition; Galvanic Skin Response; Pulse Transit Time

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