Galvanic skin response as a measure of engagement during play in virtual reality

Roni Barak Ventura, Maurizio Porfiri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Competition is a common design strategy used to enhance user engagement and participation. However, it remains unclear how winning or losing might influence player's engagement. In a recent study, we used behavioral metrics to quantify player engagement during competitive gameplay in virtual reality. To control for players' status of winning or losing, we programmed a virtual opponent to either under-perform, over-perform, or tie with them. We conducted a series of experiments and found that players' engagement was higher when they were losing, compared to when they played alone. Nevertheless, players' engagement did not change during competition with an under-performing or equally-performing opponent. By applying the information-theoretic notion of transfer entropy, we unveiled a causal relationships between relative performance and engagement, whereby players monitored the scores and adapted their behavior accordingly. However, behavioral metrics are not detached from volition and may be influenced by confounding factors. This limitation is addressed by the use of physiological metrics, which offer largely unbiased measurements of cognitive and emotional processes. In the present study, we sought to strengthen our prior findings by measuring engagement with a physiological correlate. We conducted experiments in the same experimental setting and we measured players' galvanic skin response during competition. We discovered that players' skin conductance was higher when they were outperformed by their opponent, indicating that they were experiencing less flow. The results inform the design of technology-mediated applications toward sustaining user engagement and participation.

Original languageEnglish (US)
Title of host publicationAdaptive/Intelligent Sys. Control; Driver Assistance/Autonomous Tech.; Control Design Methods; Nonlinear Control; Robotics; Assistive/Rehabilitation Devices; Biomedical/Neural Systems; Building Energy Systems; Connected Vehicle Systems; Control/Estimation of Energy Systems; Control Apps.; Smart Buildings/Microgrids; Education; Human-Robot Systems; Soft Mechatronics/Robotic Components/Systems; Energy/Power Systems; Energy Storage; Estimation/Identification; Vehicle Efficiency/Emissions
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791884270
DOIs
StatePublished - 2020
Externally publishedYes
EventASME 2020 Dynamic Systems and Control Conference, DSCC 2020 - Virtual, Online
Duration: Oct 5 2020Oct 7 2020

Publication series

NameASME 2020 Dynamic Systems and Control Conference, DSCC 2020
Volume1

Conference

ConferenceASME 2020 Dynamic Systems and Control Conference, DSCC 2020
CityVirtual, Online
Period10/5/2010/7/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Aerospace Engineering
  • Automotive Engineering
  • Biomedical Engineering
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

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