University of Twente Student Theses
Development of an AI Model Capable of Distinguishing the Reason for an Attention-Seeking Touch
Josan, A. (2024) Development of an AI Model Capable of Distinguishing the Reason for an Attention-Seeking Touch.
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| Abstract: | Existing studies in mediated social touch have primarily focused on the effects of touch on users, often neglecting the need for systems to understand user-initiated touches. This research addressed this gap by developing a machine learning model to determine the intention behind attention-seeking touches, specifically differentiating between comforting and warning gestures. Utilizing insights from prior studies, the proposed model enhanced the understanding of social touch in human-machine interactions. The methodology included a literature review and an experiment with human participants. Participants performed attention-seeking touches on a mannequin arm equipped with a Touch Sensitive Patch (TSP). Data on touch location, intensity, and duration were collected and anonymized. A Random Forest Classifier was primarily used to train the model, with an additional classifier explored. This research demonstrated the potential of machine learning to interpret reason-dependent attention-seeking touch signals, advancing the understanding of social touch. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Awards: | Best paper award |
| Link to this item: | https://purl.utwente.nl/essays/100880 |
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