Designing a model for affective digital games to support the social-emotional development of teenagers diagnosed with an autism spectrum disorder

Mitu Khandaker

Extended Abstract

Autism spectrum disorders are a group of developmental neuropsychiatric disorders, comprised of three diagnostic entities - autistic disorder (AD), Asperger's disorder (AS), and Pervasive Developmental Disorder Not Otherwise Specified (including atypical autism) (PDD-NOS) (NHS 2008). The characteristics of autism vary from one person to another, though each sharing the common elements of impairment in social interaction, social communication, and social imagination. Individuals diagnosed with autism may have difficulty making eye contact with others, find it difficult to make friends, may not understand other people's emotions, and have difficulty managing their own emotions. ASDs affect millions of people worldwide, and in the UK alone it is estimated that 1 in 100 children are autistic. As the fastest growing developmental disorder, it is estimated that by 2013, the annual cost of autism in the US will be $200-$400 billion (NAS, 2007; ASA, 2008). Whilst there is currently no "cure" for autism, a number of intervention techniques are currently used to reduce some of the associated challenges, with techniques ranging from behavioural therapy to dietary interventions, to traditional counselling.

There has also been some limited research into the use of non-directive play therapy in treating autistic children (Josefi and Ryan 2004). However, adolescents may feel uncomfortable engaging in traditional play with toys they may be too old for. Moreover, the cost of trained personnel will be increasingly expensive. Thus, this work-in-progress poster proposes that digital games, and furthermore, affective digital games (that is, games which infer emotion as an input) could be an additional intervention technique in helping adolescents with ASD.

Affective computing technologies refer to computationally 'recognising' emotions in a user, often through the use of multimodal affective sensors, including facial expressions, postural shifts, and physiological signals such as heart rate, skin conductivity, and EEG signals. More recently such work has been applied to social-emotional computing applications to support high-functioning individuals with autism spectrum disorders (Lee 2008; Lee 2008; Madsen 2008; Picard and Goodwin 2008). This poster furthers this work by proposing a systemic model for games which use real-time multimodal affective recognition technologies as an input mechanism; this builds upon existing work on the benefit of games for therapeutic use (Griffiths, 2005) although allows additional scope for emotion regulation. The resulting system is a cybernetic feedback loop; a model for games which has also been advocated by Salen and Zimmerman (2005).

There is however a danger in designing games for specific therapeutic value that also exists in traditional play therapy with adolescents: play is not fun unless arising by choice. Furthermore, there is a certain level of stigma associated with 'serious games' and 'edutainment'. Therefore, it is proposed that games designed primarily for entertainment should be modified to leverage affective technologies in order to engage autistic teenagers on a social, emotional and behavioural level.

References:

Josefi, O. and V. Ryan (2004). "Non-Directive Play Therapy for Young Children with Autism: A Case Study." Clinical Child Psychology and Psychiatry 9(4): 533-551.

Lee, C. H., Kim, K., Breazeal, C., and Picard, R.W. (2008). Shybot : Friend-Stranger Interaction for Children Living with Autism. CHI, Florence, Italy.

Lee, C. H., Morris, R., Goodwin, M., and Picard, R.W (2008). Lessons Learned from a Pilot Study Quantifying Face Contact and Skin Conductance in Teens with Asperger Syndrome. CHI 2008. Florence, Italy.

Madsen, M., el Kaliouby, R., Goodwin, M., and Picard, R.W. (2008). Technology for Just-In-Time In-Situ Learning of Facial Affect for Persons Diagnosed with an Autism Spectrum Disorder. 10th ACM Conference on Computers and Accessibility (ASSETS), Halifax, Canada.

NHS (2008). Autistic spectrum disorder. NHS Direct Health Encyclopedia.

Picard, R. W. and M. S. Goodwin (2008). Developing Innnovative Technology for Future Personalized Autism Research and Treatment. Autism Advocate. 50: 32-39.