| 1. |
- Güneysu Özgür, Arzu, et al.
(författare)
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Lessons Learned from in the Wild Child-Robot Interaction in Multiple Ecosystems of Care and Education
- 2023
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Ingår i: HAI 2023 - Proceedings of the 11th Conference on Human-Agent Interaction. - : Association for Computing Machinery (ACM). ; , s. 142-151
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Konferensbidrag (refereegranskat)abstract
- We present here some lessons learned from observations and applications of child-robot interaction research in diverse ecosystems such as schools, therapy centers, and hospitals, where the interaction was facilitated in real-world circumstances rather than lab settings. Specifically, we use observational results from our reflections on multiple child-robot interaction practices in the wild conducted over a 9-year research period. Using these exploratory studies, we outline some general design considerations and adaptation guidelines for improving the design and implementation of robotic systems in healthcare and education that might lead to more practical, feasible, and ethically sustainable results.
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| 2. |
- Mohamed, Youssef, 1998-, et al.
(författare)
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Multi-modal Affect Detection Using Thermal and Optical Imaging in a Gamified Robotic Exercise
- 2023
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Ingår i: International Journal of Social Robotics. - : Springer Nature. - 1875-4791 .- 1875-4805.
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Tidskriftsartikel (refereegranskat)abstract
- Affect recognition, or the ability to detect and interpret emotional states, has the potential to be a valuable tool in the field of healthcare. In particular, it can be useful in gamified therapy, which involves using gaming techniques to motivate and keep the engagement of patients in therapeutic activities. This study aims to examine the accuracy of machine learning models using thermal imaging and action unit data for affect classification in a gamified robot therapy scenario. A self-report survey and three machine learning models were used to assess emotions including frustration, boredom, and enjoyment in participants during different phases of the game. The results showed that the multimodal approach with the combination of thermal imaging and action units with LSTM model had the highest accuracy of 77% for emotion classification over a 7-s sliding window, while thermal imaging had the lowest standard deviation among participants. The results suggest that thermal imaging and action units can be effective in detecting affective states and might have the potential to be used in healthcare applications, such as gamified therapy, as a promising non-intrusive method for recognizing internal states.
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| 3. |
- Tozadore, Daniel C., et al.
(författare)
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Robots for Learning 7 (R4L) : A Look from Stakeholders' Perspective
- 2023
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Ingår i: HRI 2023. - New York, NY, USA : Association for Computing Machinery (ACM). ; , s. 935-937
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Konferensbidrag (refereegranskat)abstract
- This year's conference theme "HRI for all" not just raises the importance of reflecting on how to promote inclusion for every type of user but also calls for careful consideration of the different layers of people potentially impacted by such systems. In educational setups, for instance, the users to be considered first and foremost are the learners. However, teachers, school directors, therapists and parents also form a more secondary layer of users in this ecosystem. The 7th edition of R4L focuses on the issues that HRI experiments in educational environments may cause to stakeholders and how we could improve on bringing the stakeholders' point of view into the loop. This goal is expected to be achieved in a very practical and dynamic way by the means of: (i) lightening talks from the participants; (ii) two discussion panels with special guests: One with active researchers from academia and industry about their experience and point of view regarding the inclusion of stakeholders; another panel with teachers, school directors, and parents that are/were involved in HRI experiments and will share their viewpoint; (iii) semi-structured group discussions and hands-on activities with participants and panellists to evaluate and propose guidelines for good practices regarding how to promote the inclusion of stakeholders, especially teachers, in educational HRI activities. By acquiring the viewpoint from the experimenters and stakeholders and analysing them in the same workshop, we expect to identify current gaps, propose practical solutions to bridge these gaps, and capitalise on existing synergies with the collective intelligence of the two communities.
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| 4. |
- Tozadore, Daniel C., et al.
(författare)
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Teacher's Perception on Social Robots to Promote the Integration of Children with Migration Background
- 2023
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Ingår i: HAI '23: Proceedings of the 11th International Conference on Human-Agent Interaction. - : Association for Computing Machinery (ACM).
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Konferensbidrag (refereegranskat)abstract
- This paper describes the first steps of an ongoing participatory design with teachers from Switzerland to co-create Human-Robot Interaction setups for integrating children with migration history. The herein presented phase had two main goals: (i) initially mapping the current issues and the teachers’ strategy when integrating these children, and (ii) understanding teachers’ perceptions regarding social robots for this goal. Results show that teachers we interviewed are already using technology to communicate with immigrant children, not necessarily for inclusion or promote socialisation with their peers, but simply to understand them. Findings also point to a well-defined application of social robots in inclusion activities, even when never seeing or using them, which contradicts previous results in the literature and which gives potential ways to unfold the next steps of the participatory design.
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