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The Relevance of Social Cues in Assistive Training with a Social Robot
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0001-6168-0706
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-0305-3728
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-4368-4751
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-3122-693X
2018 (English)In: 10th International Conference on Social Robotics, ICSR 2018, Proceedings / [ed] Ge, S.S., Cabibihan, J.-J., Salichs, M.A., Broadbent, E., He, H., Wagner, A., Castro-González, Á., Springer, 2018, p. 462-471Conference paper, Published paper (Refereed)
Abstract [en]

This paper examines whether social cues, such as facial expressions, can be used to adapt and tailor a robot-assisted training in order to maximize performance and comfort. Specifically, this paper serves as a basis in determining whether key facial signals, including emotions and facial actions, are common among participants during a physical and cognitive training scenario. In the experiment, participants performed basic arm exercises with a social robot as a guide. We extracted facial features from video recordings of participants and applied a recursive feature elimination algorithm to select a subset of discriminating facial features. These features are correlated with the performance of the user and the level of difficulty of the exercises. The long-term aim of this work, building upon the work presented here, is to develop an algorithm that can eventually be used in robot-assisted training to allow a robot to tailor a training program based on the physical capabilities as well as the social cues of the users.

Place, publisher, year, edition, pages
Springer, 2018. p. 462-471
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11357
Keywords [en]
Social cues, Facial signals, Robot-assisted training
National Category
Computer Systems Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-70817DOI: 10.1007/978-3-030-05204-1_45ISI: 000775457300045Scopus ID: 2-s2.0-85058342671ISBN: 978-3-030-05203-4 (print)ISBN: 978-3-030-05204-1 (electronic)OAI: oai:DiVA.org:oru-70817DiVA, id: diva2:1272355
Conference
10th International Conference on Social Robotics (ICSR 2018), Qingdao, China, November 28-30, 2018
Projects
SOCRATES
Funder
EU, Horizon 2020, 721619Available from: 2018-12-19 Created: 2018-12-19 Last updated: 2024-01-16Bibliographically approved

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Akalin, NezihaKiselev, AndreyKristoffersson, AnnicaLoutfi, Amy

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Citation style
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