Abstract
This paper presents a fuzzy logic model for Real-time Stress Detection (RSD) that allows continuous and in-depth evaluation of user’s stress in a straightforward and systematic way by using physiological data. The RSD model takes as input signals’ values (galvanic skin response, heart rate) and then generates the corresponding level for user’s stress (low, mid-low, mid-high and high). To this end, skin conductance and heart rate signals were used to determine the stress levels classes. Results showed that the proposed tool-based stress detection mechanism can support a systematic evaluation of user’s stress in real time. Given that stress is highly subjective and may largely depend both on context and user characteristics, such results are rather encouraging for such a challenging problem. From a UX evaluators’ perspective, a preliminary study, involving three HCI experts, investigated the usefulness of the proposed RSD mechanism and revealed that it can substantially decrease time and effort required to make sense of user testing data. Furthermore, practitioners reported that using RSD they could conduct a more in-depth analysis compared to their current practices.
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Liapis, A., Katsanos, C., Karousos, N., Sotiropoulos, D., Xenos, M., Orphanoudakis, T. (2020). Stress Heatmaps: A Fuzzy-Based Approach that Uses Physiological Signals. In: Marcus, A., Rosenzweig, E. (eds) Design, User Experience, and Usability. Case Studies in Public and Personal Interactive Systems. HCII 2020. Lecture Notes in Computer Science(), vol 12202. Springer, Cham. https://doi.org/10.1007/978-3-030-49757-6_19
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