Design Preferred Aesthetic User Interface with Eye Movement and Electroencephalography Data

Abstract

Traditional user interface (UI) optimization design mainly depends on the designer's manual adjustment, however it is a complex and inefficient process, and always dose not match the end users' preference. In order to solve this problem, this paper presents a new method that combines user's eye movement and electroencephalography (EEG) data to drive interactive genetic algorithm (IGA) and optimize UI design solutions automatically. We apply this method to optimize the UI of music player (panel of the software), and the pilot study proves that the method can evolve towards the user's preference and finally obtain the optimized aesthetic design solution that meets the user's preference.