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.

中文翻译：

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用于评估新兴移动 EEG 技术的用户体验的跨模态匹配

脑状态监测的新兴技术提供了在实验室外进行测量的可能性。然而，缺乏用户体验研究。在本文中，我们展示并测试了一种使用所谓的跨模态匹配 (CMM) 来确定用户体验随时间发展的方法。我们对 24 名受试者进行了实验，并评估了七种移动脑电图 (EEG) 设备。使用 CMM 方法，我们记录了 EEG 设备的耳机压力和受试者的情绪。我们能够确定耳机压力和情绪之间的相关性并观察时间趋势。随着时间的推移，受试者认为最重的、基于针脚的设备不太舒服。基于凝胶的 EEG 帽是最舒适的设备，就其长期特性而言。用于新 EEG 技术用户体验评估的 CMM 方法直接、快速且易于执行。这一事实为用户体验和人为因素领域的未来研究创造了新的机会。