@inproceedings{d0873396e4ea49e19df73eba2e4c0fc8,
title = "Developing an Integrated Dashboard to Analyze Multimodal Data for User Experience Evaluation",
abstract = "The evaluation of user experience (UX) is a multifaceted process that encompasses a range of methods such as surveys, emotion recognition, and attention recognition. The effectiveness of UX evaluation depends on the integration of dependable and unbiased techniques derived from diverse user-generated data sources. In this context, we introduce a Multimodal INteractive Dashboard (MIND), a web-based platform tailored to furnish a reliable and user-centric avenue for UX evaluation. MIND incorporates three core functionalities: facial emotion recognition, EEG-based attention recognition, and image generation informed by estimated user's poses and affective states. By seamlessly engaging users, MIND facilitates a quantitative assessment of their experiences. The proposed MIND offers multimodal data analytics and visualization to enable insights of time spans of the UX with individual users, helping improve the overall user experience.",
keywords = "EEG, User experience, attention, dashboard, facial emotion recognition, image generation, pose estimation",
author = "Hyejeong Jo and Junhyeok Lee and Park, {Hye Won} and Minjae Kim and Yeonwoo Kim and Lee, {Won Hee}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023 ; Conference date: 23-10-2023 Through 25-10-2023",
year = "2023",
doi = "10.1109/ICCE-Asia59966.2023.10326366",
language = "English",
series = "2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023",
address = "United States",
}