Abstract
We are looking for a relationship between electrodermal activity and the amplitude of fluctuations in the size of the pupils, depending on the magnitude of the stress (stress state) experienced. Studies have been carried out on the psychophysiological reactions of a person (emotions) arising in response to external stress factors (stimuli). For this, a device was used to register changes in pupil size and galvanic skin response. It turned out that the change in the values of galvanic skin response and pupil size correlates (p = 0.9) in the presence of emotions (all other things being equal). The result of measuring galvanic skin reaction (GSR) shows that the level of attention during the test to some stimuli was higher than to others. This means that the first stimuli may be more significant for the subject than the second. The results obtained make it possible to link the galvanic skin response and the pupil response in response to the stimulus material. Our research also shows that the pupil diameter signal has a good discriminating ability to detect changes in the psychological state of a person. The results can be useful for the development of Computer Vision and Artificial Intelligence.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Matsumoto, Y., Ogasawara, T., Zelinsky, A.: Behavior recognition based on head pose and gaze direction measurement. In: Conference: Intelligent Robots and Systems (IROS 2000), Takamatsu, Japan, vol. 3, pp. 2127–2132 (2000). https://doi.org/10.1109/IROS.2000.895285.
Batchuluun, G., et al.: Fuzzy system based human behavior recognition by combining behavior prediction and recognition. Expert Syst. Appl. 81, 108–133 (2017). https://doi.org/10.1016/j.eswa.2017.03.052
Gunes, H., Piccardi, M.: Bi-modal emotion recognition from expressive face and body gestures. J. Netw. Comput. Appl. 30(4), 1334–1345 (2007). https://doi.org/10.1016/j.jnca.2006.09.007
Baltrusaitis, T., Zadeh, A., Lim, Y.C., Morency, L.: OpenFace 2.0: facial behavior analysis toolkit. In: 13th IEEE International Conference on Automatic Face & Gesture Recognition, Xi’an, China, pp. 59–66. IEEE (2018). https://doi.org/10.1109/FG.2018.00019
Laksana, E., Baltrušaitis, T., Morency, L., Pestian, J.P.: Investigating facial behavior indicators of suicidal ideation. In: 12th IEEE International Conference on Automatic Face & Gesture Recognition, Washington, DC, USA, pp. 770–777. IEEE (2017). https://doi.org/10.1109/FG.2017.96
Melnikova, O.T., Khoroshilov, D.A.: Modern criterion systems for the validity of qualitative research in psychology. Natl. Psychol. J. 2(14), 36–48 (2014). https://doi.org/10.11621/npj.2014.0205
Montagu, J.D., Coles, E.M.: Mechanism and measurement of the galvanic skin response. Psychol. Bull. 65(5), 261–279 (1966). https://doi.org/10.1037/h0023204
Pedrotti, M., et al.: Automatic stress classification with pupil diameter analysis. Int. J. Hum. Comput. Interact. 30(3), 220–236 (2014). https://doi.org/10.1080/10447318.2013.848320
Tsagarelli Yu, A.: Systemic Diagnostics of a Person and the Development of Mental Functions. Knowledge, Kazan (2009)
Kostin, A.N., Golikov, Y.Y.: Conceptual foundations of the joint analysis of EOG and GSR for the study of mental regulation of activity and functional states. In: Experimental Psychology in Russia: Traditions and Perspectives, pp. 515–519 (2010)
Boronenko M.P., Isaeva O.L., Zelensky V.I..: Method for increasing the accuracy of tracking the center of attention of the gaze. In: 2021 International Symposium on Electrical, Electronics and Information Engineering (ISEEIE 2021), Seoul, Republic of Korea, New York, NY, USA, p. 6. ACM (2021). https://doi.org/10.1145/3459104.3459172
IMOTIONS Homepage. https://imotions.com/blog/capturing-life-as-it-happens-an-online-field-study-in-politics/. Accessed 26 June 2021
Sautin M.G., Gamayunov P.P.: Driver fatigue recognition system. In: Actual Issues of the Organization of Road Transport and Traffic Safety: A Collection of Materials of the International Scientific and Practical Conference, vol.355, pp.147–151 (2018)
Acknowledgment
The study was carried out with the financial support of the Russian Foundation for Basic Research in the framework of the research project 18-47-860018 p_a.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Boronenko, M., Isaeva, O., Boronenko, Y., Zelensky, V., Gulyaev, P. (2021). Recognition of Changes in the Psychoemotional State of a Person by the Video Image of the Pupils. In: Wojtkiewicz, K., Treur, J., Pimenidis, E., Maleszka, M. (eds) Advances in Computational Collective Intelligence. ICCCI 2021. Communications in Computer and Information Science, vol 1463. Springer, Cham. https://doi.org/10.1007/978-3-030-88113-9_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-88113-9_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-88112-2
Online ISBN: 978-3-030-88113-9
eBook Packages: Computer ScienceComputer Science (R0)