Temporal Taylor’s scaling of facial electromyography and electrodermal activity in the course of emotional stimulation
Jan Chołoniewski , Anna Chmiel , Julian Sienkiewicz , Janusz Hołyst , Dennis Küster , Arvid Kappas
AbstractHigh 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.
|Journal series||Chaos Solitons & Fractals, ISSN 0960-0779|
|Publication size in sheets||0.5|
|Keywords in Polish||brak|
|Keywords in English||Taylor’s power law; Temporal fluctuations scaling; Facial electromyography; Electrodermal activity; IAPS; Emotions|
|Abstract in Polish||brak|
|Project||Collective Emotions in Cyberspace . Project leader: Hołyst Janusz,
, Phone: 22 234 7133, start date 01-02-2009, end date 31-07-2013, FP7 Grant Agreement 231323, Completed
|Score|| = 30.0, 17-09-2020, ArticleFromJournal|
= 30.0, 17-09-2020, ArticleFromJournal
|Publication indicators||= 3; = 2; = 7.0; : 2016 = 0.856; : 2016 = 1.455 (2) - 2016=1.604 (5)|
|Citation count*||7 (2020-09-01)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.