Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96935
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Title: Attention distribution and decision-making in the process of robot’s appearance design and selection
Authors: Khoo, NHL
Li, F 
Chen, CH
Liu, Y
Trapsilawati, F
Sourina, O
Issue Date: 2022
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022, v. 13314, p. 535-544
Abstract: Humanoid robots gaining popularity in the service industry all over the world. When designing humanoid robots, product designers put additional thought into the aesthetic design to avoid the complications that arise from the “uncanny valley”. It has long been found that genders, personalities, and cultural upbringings may affect individual ratings on the appearance of humanoid robots. To better aid and hasten the appearance design and selection process, this report explores the use of Electroencephalography (EEG) and vision tracking devices to evaluate preferences based on “aesthetic” criteria of robot designs. Based on the analysis, it was found that individuals, regardless of the three traits, paid more attention to their top choices during the selection. In rating the robots’ appearance, it was also found that Eastern students rated a significantly higher score of “intelligence” than Western students. However, both eastern and western students have a similar choice of their favorite robots.
Keywords: Electroencephalography
Eye-tracking
Robots appearance design
Preference
Publisher: Springer
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-031-06053-3_36
Description: 14th International Conference, CCD 2022, held as part of the 24th HCI International Conference, HCII 2022, Virtual Event, June 26 – July 1, 2022
Rights: © 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-06053-3_36. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms.
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