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

Abstract

In the context of the COIVD-19 pandemic, everyone must maintain social distances in public. Our ability to perceive each other through “distances” in public places has been compromised. However, “distance” is an essential factor in communication that cannot be ignored, like “facial expressions” and “body movements”. This paper reflects on the current fixed “social distancing” in the context of the current viral pandemic. The innovative point of our research is to detect and calculate the differences of 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.

J. Li and Y. Yang—The first two authors contributed equally to this work.