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Possibilities and Research Issues for Measuring Human Emotions in Real Life

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Human-Computer Interaction. Theoretical Approaches and Design Methods (HCII 2022)

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Abstract

We would like to provide systems and services that contribute to people’s well-being by capturing emotional responses using bio-signals that can be measured with low burden in daily life. In this paper, the current status and issues related to measurement devices, verification of accuracy, and detection of measurement failures that are necessary to achieve this goal are discussed. Burden-free measurements are categorized as wearable, environmental embedded, and camera-based. Each has its own strengths and weaknesses, and it is best to use them in combination according to the purpose. In addition, three prototypes developed using a small processor with the function to communicate with the cloud via Wi-Fi and commercially available sensors are presented, and future challenges is discussed through these trials. In order to create systems and services that people are willing to use and that make them active and positive, industry-academia collaboration, including experts and users from various fields is desirable.

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References

  1. Ohsuga, M., Shimono, F., Genno, H.: Assessment of phasic work stress using autonomic indices. Int. J. Psychophysiol. 40(3), 211–220 (2001)

    Article  Google Scholar 

  2. Ohsuga, M., Kamakura, Y., Inoue, Y., Noguchi, Y., Shimada, K., Mishiro, M.: Estimation of driver’s arousal state using multi-dimensional physiological indices. In: Harris, D. (ed.) EPCE 2011. LNCS (LNAI), vol. 6781, pp. 176–185. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21741-8_20

    Chapter  Google Scholar 

  3. Joko, S., Ohsuga, M., Tada, Y., Ishikawa, J.: Evaluation of a mental care system for patients recuperating in a sterile room after hematopoietic cell transplantation. In: 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1314–1317 (2019)

    Google Scholar 

  4. Yoshioka, N., Araki, N., Ohsuga, M.: Importance of the features of event-related potentials used for a machine learning-based model applied to single-trial data during oddball task. In: 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 2123–2126 (2021)

    Google Scholar 

  5. Can, Y.S., Arnrich, B., Ersoy, C.: Stress detection in daily life scenarios using smart phones and wearable sensors: a survey. J. Biomed. Inform. 92, 103139 (2019)

    Article  Google Scholar 

  6. Albertetti, F., Simalastar, A., Rizzotti-Kaddouri, A.: Stress detection with deep learning approaches using physiological signals. In: Goleva, R., Garcia, NRd.C., Pires, I.M. (eds.) HealthyIoT 2020. LNICSSITE, vol. 360, pp. 95–111. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-69963-5_7

    Chapter  Google Scholar 

  7. Gao, N., Marschall, M., Burry, J., Watkins, S., Salim, F.D.: Understanding occupants’ behaviour, engagement, emotion, and comfort indoors with heterogeneous sensors and wearables. arXiv preprint arXiv:2105.06637 (2021)

  8. HEXOSKIN: Hexoskin Smart Shirts - Cardiac, Respiratory, Sleep & Activity Metrics. https://www.hexoskin.com/. Accessed 11 Feb 2022

  9. Montes, J., Young, J.C., Tandy, R., Navalta, J.W.: Reliability and validation of the hexoskin wearable bio-collection device during walking conditions. Int. J. Exerc. Sci. 11(7), 806–816 (2018)

    Google Scholar 

  10. Emprica: E4 wristband. https://www.empatica.com/. Accessed 11 Feb 2022

  11. Ohsuga, M., Kamakura, Y., Takeuchi, H., Koba, H.: Low burden measurement of autonomic indices for self-measurement or longtime measurement in the field. In: Black, N.L., Neumann, W.P., Noy, I. (eds.) IEA 2021. LNNS, vol. 222, pp. 652–657. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-74611-7_89

    Chapter  Google Scholar 

  12. Hayashi, K., Ohsuga, M.: A basic study on the utilization of physiological indicators for mental health support. Jpn. J. Ergon. 57, 2G2-1 (2021). (in Japanese)

    Google Scholar 

  13. BITalino: Redefining Biomedical Toolkits. https://bitalino.com/. Accessed 11 Feb 2022

  14. Batista, D., da Silva, H.P., Fred, A., Moreira, C., Reis, M., Ferreira, H.A.: Benchmarking of the BITalino biomedical toolkit against an established gold standard. Healthc. Technol. Lett. 6(2), 32–36 (2019)

    Article  Google Scholar 

  15. Fitbit: FitBit wristband. https://www.fitbit.com/. Accessed 11 Feb 2022

  16. Spirehealth: Remote Patient Monitoring. https://www.spirehealth.com/. Accessed 11 Feb 2022

  17. OURA: Accurate Health Information Accessible to Everyone. https://ouraring.com/. Accessed 11 Feb 2022

  18. Uratani, H., Ohsuga, M.: Relaxation effect of a respiration-leading stuffed toy. Adv. Biomed. Eng. 7, 100–106 (2018)

    Article  Google Scholar 

  19. Urabe, H., Koba, H., Ohsuga, M.: Proposal of sleep promotion device using breathing guidance by cushion robot. In: 2021 Proceeding of Human-Agent Interaction Symposium, P-44 (2021). (in Japanese)

    Google Scholar 

  20. Ohsuga, M.: Development of chairs for nonintrusive measurement of heart rate and respiration and its application. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds.) IEA 2018. AISC, vol. 827, pp. 392–404. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-96059-3_44

    Chapter  Google Scholar 

  21. Ohsuga, M., Sugiyama, S.: Obtaining heart rate information from a driver using capacity coupled electrodes (5th report). In: Proceeding of 2016 JSAE Annual Congress (Spring), pp.1539–1542 (2016). (in Japanese)

    Google Scholar 

  22. Ohsuga, M., Sugiyama, S.: Obtaining heart rate information from a driver using capacity coupled electrodes (6th report). In: Proceeding of 2016 JSAE Annual Congress (Autumn), pp.1075–1078 (2016). (in Japanese)

    Google Scholar 

  23. QuooBoo: A Tailed Cushion That Heals Your Heart. https://qoobo.info/index-en/. Accessed 11 Feb 2022

  24. Kamakura, Y., Takeuchi, H., Ohsuga, M.: Contactless and low-burden measurement of physiological signals and comparison of obtained indices. In: Black, N.L., Patrick Neumann, W., Noy, I. (eds.) IEA 2021. LNNS, vol. 222, pp. 615–619. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-74611-7_83

    Chapter  Google Scholar 

  25. GitHub - CMU-Perceptual-Computing-Lab/openpose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation. https://github.com/CMU-Perceptual-Computing-Lab/openpose. Accessed 11 Feb 2022

  26. Report of the project of New Media Development Association supported by Japan Keirin Autorace foundation (JKA) and its promotion funds from KEIRIN RACE (2020). (in Japanese)

    Google Scholar 

  27. Takeuchi, H., Ohsuga, M., Kamakura, Y.: A study on region of interest in remote PPG and an attempt to eliminate false positive results using SVM classification. In: 2021 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), pp.1–5 (2021)

    Google Scholar 

  28. Lang, M.: Beyond Fitbit: a critical appraisal of optical heart rate monitoring wearables and apps, their current limitations and legal implications. Alb. LJ Sci. Tech. 28, 39–72 (2017)

    Google Scholar 

  29. ThingSpeak: IoT Analytics - ThingSpeak Internet of Things. https://thingspeak.com/, Accessed 11 Feb 2022

  30. ATC INNOVATION WEEK (in Japanese). https://www.atc-co.com/innovation-week/. Accessed 11 Feb 2022

  31. Nomiya, N., Hayashi, K., Koba, H., Takeuchi, H.: Development of a support system for caregivers that presents emotional changes in children with autism spectrum disorder. In: 2021 Conference of Japan Ergonomics Society KANSAI Branch, p. B-2-2 (2021). (in Japanese)

    Google Scholar 

  32. Taj-Eldin, M., Ryan, C., O’Flynn, B., Galvin, P.: A review of wearable solutions for physiological and emotional monitoring for use by people with autism spectrum disorder and their caregivers. Sensors 18(12), 4271–4299 (2018)

    Article  Google Scholar 

  33. Ohsuga, M., Shimono, F., Akashi, C.: Development of an apparatus for monitoring degree of mental tension. Trans. Soc. Instrum. Control Eng. 28(8), 910–915 (1992). (in Japanese)

    Article  Google Scholar 

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Acknowledgment

The author thanks her co-researcher Dr. Yoshiyuki Kamakura (Department of Information Science, Osaka Institute of Technology) for frequent discussions and collaboration. She also thanks to the students in “wellness” laboratory, especially graduate students; Mr. Hiroki.Takeuchi (Sect. 3.2), Mr. Kaito Hayashi (Sect. 3.1), and undergraduate student; Mrs. Ayaka Yamauchi (Sect. 4.1), Mrs. Narumi Nomiya (Sect. 4.2), and Mrs. Emi Yamanari (Sect. 4.3) for their contributions to the specific research. The author is also grateful to the participants who participated in the experiments and to the many people who provided useful comments on the research. A part of work cited in Sect. 2.3 was conducted by New Media Development Association supported by Japan Keirin Auto race foundation (JKA) and its promotion funds from KEIRIN RACE.

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  1. Osaka Institute of Technology, Osaka, 530-8568, Japan

    Mieko Ohsuga

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  1. Mieko Ohsuga
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Correspondence to Mieko Ohsuga .

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  1. The Open University of Japan, Chiba, Japan

    Masaaki Kurosu

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Ohsuga, M. (2022). Possibilities and Research Issues for Measuring Human Emotions in Real Life. In: Kurosu, M. (eds) Human-Computer Interaction. Theoretical Approaches and Design Methods. HCII 2022. Lecture Notes in Computer Science, vol 13302. Springer, Cham. https://doi.org/10.1007/978-3-031-05311-5_34

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  • DOI: https://doi.org/10.1007/978-3-031-05311-5_34

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