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  • 2014

  • Bekele, Esubalew; Sarkar, Nilanjan (2014) : Psychophysiological feedback for adaptive human-robot interaction (HRI) In: Fairclough, Stephen H.; Gilleade, Kiel (Hg.): Advances in physiological computing: New York, NY: Springer-Verlag Publishing (Human-computer interaction series; ISSN: 1571-5035 (Print)), S. 141-167

    DOI: https://doi.org/10.1007/978-1-4471-6392-3_7 

    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. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

    Keywords: Bedienung & Handhabung, Feedback, Human Machine Systems, Human robot interaction, human-robot interaction, machine learning, psychophysiological feedback, Psychophysiology, Robotics, social interaction, therapeutic applications, Therapeutic Processes
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