Evaluation of User Interface, User Experience, and Usability in Software Through Electroencephalography (EEG) Signal Detection: A Mapping Review

As the digital landscape continues to evolve through the widespread use of software, understanding how users interact with software becomes increasingly important. This article presents the findings of a literature review that explores the use of Electroencephalography (EEG) signals to assess user interfaces, user experience, and/or software usability. We used the mapping review method in this research with the main stages including: 1) Establishing research questions; 2) Source selection; 3) Identifying keywords; 4) Carrying out a screening process; and 5) Extracting and synthesizing data. As a result, we determined 16 relevant papers as primary sources. We highlight the distribution of papers from various databases and their suitability for the period January 2013 to May 2023. In addition, we find that traditional EEG devices, standard five frequency bands, 32 electrodes, signal classification techniques such as Linear Discriminant Analysis (LDA), Frequency Fourier Transform (FFT), and Power Spectrum Density (PSD), gaming software as research subjects, and user experience evaluation questionnaires are most widely used in research practice. The results of this literature review provide comprehensive insight into the latest developments in the use of EEG signals to evaluate software in terms of the field of Human-Computer Interaction, to reduce the factors of subjectivity, bias, efficiency, and accuracy of evaluation results. These insights can serve as a basis for further research and the development of more effective methods and tools for improving software quality.