Cross-Modality Matching for Evaluating User Experience of Emerging Mobile EEG Technology

Emerging technology for brain-state monitoring offers the possibility to conduct measurements outside the laboratory. However, user-experience research is lacking. In this article, we present and test an approach for determining the development of user experience in the course of time using the so-called cross-modality matching (CMM). We conducted experiments with 24 subjects and evaluated seven mobile electroencephalography (EEG) devices. Using the CMM method, we registered the headset pressure of the EEG devices and subject’s mood. We are able to identify a correlation between headset pressure and mood and to observe time trends. Subjects rated the heaviest, pin-based device as less comfortable in the course of time. The gel-based EEG cap is the most comfortable device regarding its long-time properties. The CMM approach for user-experience evaluation of new EEG technologies is direct, rapid, and easy to perform. This fact creates new opportunities for future studies in the field of user experience and human factors.

The complete article is published in the Journal "IEEE Transactions on Human-Machine Systems", Volume 50, Issue 4, pp. 298-305.

Bibliographic information

Title:  Cross-Modality Matching for Evaluating User Experience of Emerging Mobile EEG Technology. 

Written by:  T. Radüntz, B. Meffert

in: IEEE Transactions on Human-Machine Systems, Volume 50, Issue 4, 2020.  pages: 298-305, Project number: F 2402, PDF file, DOI: 10.1109/THMS.2020.2989380

Download file "Cross-Modality Matching for Evaluating User Experience of Emerging Mobile EEG Technology" (PDF, 2 MB, Not barrier-free file)

Further Information

Research Project

Project numberF 2402 StatusCompleted Project Experimental studies on the development of continuous neuronal mental workload registration for field use

To the Project

Research completed