Abstract
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.
Keywords
- Social cues
- Facial signals
- Robot-assisted training
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Acknowledgement
This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 721619 for the SOCRATES project.
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Akalin, N., Kiselev, A., Kristoffersson, A., Loutfi, A. (2018). The Relevance of Social Cues in Assistive Training with a Social Robot. In: Ge, S., et al. Social Robotics. ICSR 2018. Lecture Notes in Computer Science(), vol 11357. Springer, Cham. https://doi.org/10.1007/978-3-030-05204-1_45
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DOI: https://doi.org/10.1007/978-3-030-05204-1_45
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