Abstract
Anxiety is one of the most significant health issues. Generally, there are four levels of anxiety: mild anxiety, moderate anxiety, severe anxiety, and panic level anxiety. While mild anxiety may not significantly impact a person’s daily life, severe anxiety can be debilitating and affect their ability to carry out normal activities. People with moderate, severe anxiety and panic level anxiety cannot be relieved through common relaxation methods. However, psychology-based therapeutic intervention such as Virtual Reality therapy has been shown to be effective in alleviating anxiety. To develop an efficient VR therapy system for anxiety relief, it is necessary to measure and understand a person’s anxiety state using a wearable device, which can be easily equipped without the need to be interrupted during the therapy session. The aim of this study is to investigate the methods to accurately measure periodic anxiety and to find the reliable physiological indexes that can be used in anxiety research. We conduct a flicker task experiment by constantly flickering two images with subtle differences to induce anxiety. The results showed that LF/HF ratio, RMSSD, and SDNN can effectively be used to detect anxiety levels.
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References
World Health Organization: Covid-19 pandemic triggers 25% increase in prevalence of anxiety and depression worldwide (2022). https://www.who.int/news/item/02-03-2022-covid-19-pandemic-triggers-25-increase-in-prevalence-of-anxiety-and-depression-worldwide
World Health Organization: Adolescent mental health (2021). https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health
Spielberger, C.D.: State-trait anxiety inventory for adults (1983)
Tsai, C.-F., Hsu, Y.-W., Huang, Y.-T., Hsu, W.-L., Chung, M.-H.: The effect of augmented reality and virtual reality on inducing anxiety for exposure therapy: a comparison using heart rate variability. J. Healthc. Eng. 2018, 7 (2018)
Forte, G., Favieri, F., Tambelli, R., Casagrande, M.: Anxiety and attentional processes: the role of resting heart rate variability. Brain Sci. 11(4), 480 (2021)
Mauss, I.B., Robinson, M.D.: Measures of emotion: a review. Cogn. Emot. 23(2), 209–237 (2009)
Kawakami, Y., Hasegawa, S., Furukawa, R., Homma, R.: Preliminary study on color therapy effect evaluation by the emotion estimation method with biological signals. In: Di Bucchianico, G., Sethi, T., Lee, Y. (eds.) Advances in Industrial Design: Proceedings of the AHFE 2020 Virtual Conferences on Design for Inclusion, Affective and Pleasurable Design, Interdisciplinary Practice in Industrial Design, Kansei Engineering, and Human Factors for Apparel and Textile Engineering, 16–20 July 2020, USA, pp. 71–79. Springer (2020)
Appelhans, B.M., Luecken, L.J.: Heart rate variability as an index of regulated emotional responding. Rev. Gen. Psychol. 10(3), 229–240 (2006)
Lang, P.J., Bradley, M.M., Cuthbert, B.N.: International affective picture system (IAPS): technical manual and affective ratings. NIMH Cent. Study Emot. Attention 1, 39–58 (1997)
Peirce, J., Gray, A.A., Simpson, A., MacAskill, M.R.: PsychoPy: psychophysics software in Python. In: Bilgin, A.A., Kurbanoglu, S., Tonta, Y. (eds.) Proceedings of the 9th International Conference on Computer Science and Information Management, pp. 123–134. Springer (2019)
Union Tool. https://www.uniontool-mybeat.com/
Acknowledgement
We extend our sincere gratitude to all the participants who dedicated their valuable time and effort to this study. Additionally, we express our appreciation to Zhouhaotian Yang for his valuable technical guidance and unwavering support for the image processing involved in this experiment.
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He, H., Feng, C., Sripian, P., Laohakangvalvit, T., Sugaya, M. (2023). Preliminary Experiment for Measuring the Anxiety Level Using Heart Rate Variability. In: Chen, J.Y.C., Fragomeni, G. (eds) Virtual, Augmented and Mixed Reality. HCII 2023. Lecture Notes in Computer Science, vol 14027. Springer, Cham. https://doi.org/10.1007/978-3-031-35634-6_33
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DOI: https://doi.org/10.1007/978-3-031-35634-6_33
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