Temporal Taylor's scaling of facial electromyography and electrodermal activity 
in the course of emotional stimulation

Choloniewski, Jan; Chmiel, Anna; Sienkiewicz, Julian; Holyst, Janusz A.; Kuester, Dennis; Kappas, Arvid

doi:10.1016/j.chaos.2016.04.023

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Temporal Taylor's scaling of facial electromyography and electrodermal activity in the course of emotional stimulation

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Sienkiewicz, Julian
Max Planck Institute for the Physics of Complex Systems, Max Planck Society;

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http://arxiv.org/pdf/1601.01649.pdf
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https://www.sciencedirect.com/science/article/pii/S0960077916301564?via%3Dihub
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Citation

Choloniewski, J., Chmiel, A., Sienkiewicz, J., Holyst, J. A., Kuester, D., & Kappas, A. (2016). Temporal Taylor's scaling of facial electromyography and electrodermal activity in the course of emotional stimulation. Chaos, Solitons and Fractals, 90, 91-100. doi:10.1016/j.chaos.2016.04.023.

Cite as: https://hdl.handle.net/11858/00-001M-0000-002B-19F8-8

Abstract

High frequency psychophysiological data create a challenge for quantitative modeling based on Big Data tools since they reflect the complexity of processes taking place in human body and its responses to external events. Here we present studies of fluctuations in facial electromyography (fEMG) and electrodermal activity (EDA) massive time series and changes of such signals in the course of emotional stimulation. Zygomaticus major (ZYG; "smiling" muscle) activity, corrugator supercilii (COR; "frowning" muscle) activity, and phasic skin conductance (PHSC; sweating) levels of 65 participants were recorded during experiments that involved exposure to emotional stimuli (i.e., IAPS images, reading and writing messages on an artificial online discussion board). Temporal Taylor's fluctuations scaling were found when signals for various participants and during various types of emotional events were compared. Values of scaling exponents were close to one, suggesting an external origin of system dynamics and/or strong interactions between system's basic elements (e.g., muscle fibres). Our statistical analysis shows that the scaling exponents enable identification of high valence and arousal levels in ZYG and COR signals. (C) 2016 Elsevier Ltd. All rights reserved.