Preprint 2022
Pauline Hohl and Youngjun Cho
Department of Computer Science, University College London, London, UK
Eye blinking is a subconscious behaviour that is associated with our affective states. While spontaneous eye blinking and its relationship with anxiety and stress have been actively explored in the literature, it has not yet been considered in a loop of biofeedback. Here, we explore biofeedback meditation mechanisms with eye-blink. In our within-participant experiment (n=19), we assess the impact of eye-blinking biofeedback on self-perceived anxiety and stress levels and on spontaneous eye blink rate (SEBR). This is done by exposing participants to two conditions (with visual biofeedback exercises, and with it) during an anxiety and stress-inducing mock job interview. Our results show no significant effects of the independent variable on self-rated anxiety/stress scores and SEBR; however, we have identified that eye blink-triggered visual biofeedback can be distractive given that it can lead to high perceptual load during the mock interview. Building upon participants’ feedback, we establish design implications and suggest further research directions that can potentially involve other modalities such as tactile or olfactory feedback for eye blink biofeedback. Note that this work builds on our previous projects (see details in [1-9]).
References
[1] Moge, C., Wang, K. and Cho, Y., 2022. Shared user interfaces of physiological data: Systematic review of social biofeedback systems and contexts in HCI. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1-16).
[2] Cho, Y., 2021. Rethinking eye-blink: Assessing task difficulty through physiological representation of spontaneous blinking. In Proceedings of the 2021 CHI conference on human factors in computing systems (pp. 1-12).
[3] Cho, Y., Bianchi-Berthouze, N. and Julier, S.J., 2017. DeepBreath: Deep learning of breathing patterns for automatic stress recognition using low-cost thermal imaging in unconstrained settings. In 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), pp. 456-463.
[4] Cho, Y., Julier, S. J. and Bianchi-Berthouze, N., 2019. Instant Stress: Detection of Perceived Mental Stress Through Smartphone Photoplethysmography and Thermal Imaging. JMIR mental health, 6(4), e10140.
[5] Cho, Y. and Bianchi-Berthouze, N., 2019. Physiological and affective computing through thermal imaging: A survey. arXiv preprint arXiv:1908.10307.
[6] Cho, Y., et al.,2019. Nose heat: Exploring stress-induced nasal thermal variability through mobile thermal imaging. In 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII), pp. 566-572
[7] Cho, Y. and Joung, M., 2017. Display apparatus and method for operating the same. U.S. Patent 9,733,765.
[8] Cho, Y., Youn, J., Joung, M., and Kim, S., 2020. Vehicle display device and vehicle. U.S. Patent 10,534,440.
[9] Cho, Y., Julier, S.J., Marquardt, N. and Bianchi-Berthouze, N., 2017. Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging. Biomedical optics express, 8(10), pp.4480-4503.