Detecting flow in games using facial expressions

Andrew Burns, James Tulip

Research output: Book chapter/Published conference paperConference paper

3 Citations (Scopus)

Abstract

Many games use dynamic difficulty adjustment (DDA) to promote the achievement of flow and consequent positive affective states. However, performance based DDA assume a specific ludic attitude: that of the hard-core gamer. An alternative approach is to apply affective computing techniques to monitor players adjust difficulty to achieve the desired affective state directly. Such an emotion-controlled dynamic difficulty adjustment (EC-DDA) system might be more flexible and achieve better outcomes for a wider variety of players. Current approaches to monitoring affective state such as ECGs or EEGs can be very intrusive. However, monitoring affective state using facial expressions is non-intrusive, and can be done with minimal, generally existing hardware. This paper presents a simple arcade styled game incorporating a webcam and COTS facial expression analytical software. It presents the results of a set of experiments investigating the issues involved in collecting and analyzing facial expressions to determine player affect. Results demonstrate the feasibility of using facial expressions as a mechanism for determining player affect, but also illustrate some of the difficulties inherent in the EC- DDA approach. Specifically, the affects observed are not consistent with a standard interpretation of flow as characterized by high arousal and positive affect. Instead, even in a state of flow, the affect expressed may be flat. In other instances, affect may be highly variable, expressing a range of transitory basic emotions. Preliminary findings support the notion of flow as a complex cognitive state resulting from a cycle of transitions between simple affective states such as frustration and joy.
Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE Conference on Computational Intelligence and Games (CIG)
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages45-52
Number of pages8
ISBN (Electronic)9781538632338
DOIs
Publication statusPublished - 26 Oct 2017
Event2017 IEEE International Conference on Computational Intelligence and Games: CIG 2017 - New York University, New York, United States
Duration: 22 Aug 201725 Aug 2017
http://www.cig2017.com/ (Conference website)

Conference

Conference2017 IEEE International Conference on Computational Intelligence and Games
CountryUnited States
CityNew York
Period22/08/1725/08/17
Internet address

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