Visualizing the Electroencephalography Signal Discrepancy When Maintaining Social Distancing

2022. 05. 16

Visualizing the Electroencephalography Signal Discrepancy When Maintaining Social Distancing: EEG-Based Interactive Moiré Patterns

In the context of the COIVD-19 pandemic, everyone is required to maintain social distance in the public. We have lost the way to perceive each other through “distances” in public places. However, “distance” is an essential factor in communication that can’t be ignored, like “facial expressions” and “body movements”. This paper reflects on the current fixed “social distancing” in a particular context. The innovative point of our research is to detect and calculate the differences in brainwave signal data between two people and visualize the differences through programmed 2D moving images. In terms of the research process, first, we explored a new way of interaction, using brainwave signals to express “distances” and Moiré patterns as visual representations. Then we wrote an algorithm to generate the dynamic responses of the Moiré patterns to different stimuli in real-time to represent the concepts of distances and visualize people’s reactions. Finally, we developed an interactive device to imagine “electroencephalography (EEG) signal discrepancy” to perceive the “distances” in social situations. Nowadays, online meetings, classes, etc., are becoming more and more popular, and the distances between people in virtual spaces will be more ambiguous. In light of this, we plan to explore the visualization of electroencephalography (EEG) signal discrepancy in remote communication to enhance people’s perceptions of each other in the future.


Project Member: Jingjing Li1, Ye Yang2, Zhexin Zhang1, Yinan Zhao1, Vargas Meza Xanat1 and Yoichi Ochiai/ 李晶晶1、杨叶2、張哲新1、趙一楠1、Vargas Meza Xanat1、落合陽一1

1 Library and Information Media, University of Tsukuba, Tsukuba, Japan / 1 筑波大学図書館情報メディア系,日本,つくば

2 College of Design and Innovation, Tongji University, Shanghai, China / 同済大学,中国,上海市

Contact / 連絡先

Li Jingjing, Yang Ye, Zhang Zhexin, Yoshida Nozomu, Xanat Vargas Meza and Ochiai Yoichi (2022) Psychological distance and user engagement in online exhibitions: Visualization of moiré patterns based on electroencephalography signals. Front. Psychol. 13:954803. doi: 10.3389/fpsyg.2022.954803,

Jingjing Li, Ye Yang, Zhexin Zhang, Yinan Zhao, Vargas Meza Xanat, Yoichi Ochiai . (2022). Visualizing the Electroencephalography Signal Discrepancy When Maintaining Social Distancing: EEG-Based Interactive Moiré Patterns. In: Soares, M.M., Rosenzweig, E., Marcus, A. (eds) Design, User Experience, and Usability: Design for Emotion, Well-being and Health, Learning, and Culture. HCII 2022. Lecture Notes in Computer Science, vol 13322. Springer, Cham.