Electroencephalography and vision tracking to evaluate influences of gender, personality types and cultural differences on product designers during the final design selection process

With humanoid robots gaining popularity in the service industry, the design of these artificial beings has not been easy. When designing humanoid robots, product designers put additional thoughts into the aesthetic design to avoid the complications that may arise from the “Uncanny Valley”. They stru...

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Bibliographic Details
Main Author: Khoo, Nicholas Hong Li
Other Authors: Chen Chun-Hsien
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/138508
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Institution: Nanyang Technological University
Language: English
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Summary:With humanoid robots gaining popularity in the service industry, the design of these artificial beings has not been easy. When designing humanoid robots, product designers put additional thoughts into the aesthetic design to avoid the complications that may arise from the “Uncanny Valley”. They struggle and spend a significant amount of time choosing between their final designs, which further delays the product launch. In addition, the use of traditional evaluation tools such as surveys may be time-consuming and subjective to biasness among designers. To better aid and hasten the selection process, this report explores the use of Electroencephalography (EEG) and vision tracking devices to evaluate preferences based on the “aesthetic” criteria of robot designs. The data gathered from individuals of different genders, personalities and cultural differences were compared with their top design choices as well as their individual image ratings. Based on the analysis, it was found that individuals, regardless of the three traits mentioned, paid more attention to their top choices during the selection. Correlations were also found between the traits of individuals and the robots’ perceived friendliness, dominance, intelligence and valence. Lastly, emotions gathered from the display of individual images were independent from their choices. However, this could be partly attributed to the presence of noise in emotions data. As a result, it can be concluded that certain characteristics of robots are influenced by an individuals’ gender, personality and cultural differences. This should be a consideration should product designers choose to adopt EEG and vision tracking devices in their product selection process in the future.