https://orcid.org/0000-0002-0010-8279
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ABSTRACT
UX (User experience) can influence important user behaviors, including user preference, purchasing decisions, and customer loyalty. The ability to assess UX during the product trial has practical significance for design and improvement of products. In this article, two smartphones with different UX were selected through a focus group. In the EEG (electroencephalography) experiment, we explored the brain signal of users when using two smartphones to complete three tasks. The brain signal of each participant was recorded through Curry Neuroimaging Suite software (Version 7.0, Compumedics Limited, Abbotsford, Australia) when they were using the smartphones. Then results from behavioral, subjective and neural responses were analyzed. The behavioral results showed that participants completed the three tasks faster by using a smartphone with a higher score of UX. The subjective results showed a significant difference between the two smartphones. The patterns of cortical activity were obtained in the five principal frequency bands, Delta (1–4 Hz), Theta (4–8 Hz), Alpha (8–13 Hz), Beta (13–30 Hz) and Gamma (30–45 Hz). The results indicated that a smartphone with higher scores of UX could evoke stronger relative power of Alpha (fronto-central, parietal and partieto-occipital regions), Delta (frontal region) and Gamma rhythms (C3 site), but weaker relative power of Beta (left central region) and Theta rhythms (frontal and parieto-occipital regions). Also, the correlation analysis showed that there was no significant relationship between EEG and behavioral results. User’s subjective experience had a significant positive correlation with the relative power of Gamma band, but a negative correlation with Beta and Theta bands (approximately significant with p = .078 and p = .071). There were also significant correlations between EEG results and sub-items of UX. Our findings suggest that the difference in EEG may be taken as an evaluating indicator of user perception when using products without interruption.
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Yi Ding
Yi Ding is an associate professor from the Department of Industrial Engineering at Anhui Polytechnic University, Wuhu, China. Now he is working as a visiting scholar of school of industrial engineering in Purdue University. His interest and expertise are mental workload, user experience and neuroergonomics in human factors. E-mail: [email protected]
Yaqin Cao
Yaqin Cao is an associate professor from the Department of Industrial Engineering at Anhui Polytechnic University, Wuhu, China. Now she is working as a visiting scholar of school of industrial engineering in Purdue University. Her research interests include emotional design, user experience design, and human computer interaction. E-mail: [email protected]
Qingxing Qu
Qingxing Qu is a Ph.D. candidate, in the Department of Industrial Engineering, School of Business Administration, Northeastern University, Shenyang, China. His research interests include human factors, kansei engineering, user experience design, human-computer interaction, human-robot interaction and smart home system design. E-mail: [email protected] /[email protected]
Vincent G. Duffy
Vincent G. Duffy is an associate professor from the School of Industrial Engineering at Purdue University. He was the chair for conferences on Digital Human Modeling (Part of HCI International) since 2007. His research interest includes digital human modeling, safety engineering, work methods and measurement and ergonomics. E-mail: [email protected]