Application of Electroencephalogram Physiological Experiment in Interface Design Teaching: A Case Study of Visual Cognitive Errors

Author/s: Xiaojiao Chen, Yafeng Niu, Fanqing Ding, Chengqi Xue

DOI: 10.12738/estp.2018.5.129 

Year: 2018 Vol: 18 Number: 5

Abstract

Technology changes accelerated the speed of subject interaction more and more frequency in now days. Take advantage of electroencephalogram (EEG) physiological experiments to analysis the user interface (UI) of software, bring the assessment criteria of quantitative analysis to the design discipline, these methods were accepted by more and more researcher in a university or institute. As a researcher in a university, we show EEG in this paper our experiences and results in teaching students whose major in interface design with five stages, our focus is one of EEG solutions, which offers several UI possibilities. Take EEG physiological experiments to analysis the visualization cognitive errors (VCE) could help designers understand the cognition process of digital interface visual information (DIVI) by different users and improve the overall efficiency of digital interface design. Based on the composition of DIVI, VCE of DIVI were analyzed from color and layout difference. According to the experimental factors of the error trap, this paper designed two EEG physiological experiments to study the behavioral responses and EEG responses of the brain to DIVI. In order to improve the versatility of experimental conclusions in digital interface design, the EEG physiological experiments in this paper was designed under the Oddball experimental paradigm. And the experimental materials include the digital interface of PC terminal and mobile terminal. The statistical analysis results of the experimental data show that the behavioral data and brainwave data of the EEG experiment can be used as the basis for judging the cognitive errors of the digital interface visual information. However, EEG components and EEG topographic maps related to VCE of DIVI may vary significantly due to differences in experimental materials. The experiment also indicates that there are many branches in the EEG experiments to analysis the VCE of DIVI. It is helpful to improve the reliability of digital interface design by perfecting the EEG physiological experiments of these branches. We give an example of the practical problems and adequate sequences for teaching EEG approaches based on our study and experiences.

Keywords
Electroencephalograph (EEG), Visualization Cognitive Error (VCE), Digital Interface, Physiological Experiment

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