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Measuring Flow Using Psychophysiological Data in a Multiplayer Gaming Context MARIE-CHRISTINE BASTARACHE-ROBERGE, PIERRE-MAJORIQUE LÉGER, FRANÇOIS COURTEMANCHE, SYLVAIN SÉNÉCAL AND MARC FREDETTE Gmunden Retreat on NeuroIS 2015 June 3rd 2015, Gmunden, Austria

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Measuring Flow Using Psychophysiological Data in a Multiplayer Gaming Context

MARIE-CHRISTINE BASTARACHE-ROBERGE, PIERRE-MAJORIQUE LÉGER, FRANÇOIS COURTEMANCHE, SYLVAIN SÉNÉCAL AND MARC FREDETTE

Gmunden Retreat on NeuroIS 2015

June 3rd 2015, Gmunden, Austria

© Copyright Tech3Lab 2015

Tech3Lab 2015 :

Objective:INVESTIGATE, IN A GAMING CONTEXT, HOW A PLAYER’S AND HIS TEAMMATE’S PERSONALITY AND NEUROPHYSIOLOGICAL REACTIONS CAN CONTRIBUTE IN EXPLAI-NING A PLAYER’S FLOW ASSESSMENT.

Flow in group

Integrative definiton of flow experience(PEIFER, 2012)

Optimal challenge

Physiological activation

Positive valence

FLOW = DiFF icuLty anD cOmpet ency+

psychOphys iOLOgicaL stat e OF t he Learner

Predicting the flow state

16%

18%

© Copyright Tech3Lab 2015

Léger, Pierre-Majorique, et al. “Neurophysiological correlates of cognitive absorption in an enactive training context.” Computers in Human Behavior 34 (2014): 273-283.

Methodology

Flow in group

players games88 120

Electrodermal activity

© Copyright Tech3Lab 2015

Cardiac activity and respiration

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Automatic Facial Analysis

FLOW OF pLayer (a)= DiFF icuLty + cOmpet ency+

pLayer (a)+pLayer (B)

Predicting flow in multiplayer context

66%

Léger et al (unpublished)

Automatic facial analysis and behavioural predictionFACIAL EMOTION CAN PREDICT UP TO 30 SEC BEFORE THE INTENTION TO CHANGE THE DIFFICULTY OF A GAME.

Thank you!