Assessing the Utility of a Virtual Environment for Enhancing Facial Affect Recognition in Adolescents with Autism

Abstract

Teenagers with autism spectrum disorder (ASD) and age-matched controls participated in a dynamic facial affect recognition task within a virtual reality (VR) environment. Participants identified the emotion of a facial expression displayed at varied levels of intensity by a computer generated avatar. The system assessed performance (i.e., accuracy, confidence ratings, response latency, and stimulus discrimination) as well as how participants used their gaze to process facial information using an eye tracker. Participants in both groups were similarly accurate at basic facial affect recognition at varied levels of intensity. Despite similar performance characteristics, ASD participants endorsed lower confidence in their responses and substantial variation in gaze patterns in absence of perceptual discrimination deficits. These results add support to the hypothesis that deficits in emotion and face recognition for individuals with ASD are related to fundamental differences in information processing. We discuss implications of this finding in a VR environment with regards to potential future applications and paradigms targeting not just enhanced performance, but enhanced social information processing within intelligent systems capable of adaptation to individual processing differences.

Technology-Facilitated Diagnosis and Treatment of Individuals with Autism Spectrum Disorder: An Engineering Perspective

“…Different from the Vizard Virtual Reality Toolkit and Game Studio A6, other modeling and animation tools are needed for dynamic facial expression design and animation. In [60], the Maya tool from autodesk was used to animate the characters taken from Mixamo (http://www.mixamo.com). In this study, seven universal facial expressions were used, including "joy, surprise, contempt, sadness, fear, disgust, and angle" (page 1644) [60].…”

“…In [60], the Maya tool from autodesk was used to animate the characters taken from Mixamo (http://www.mixamo.com). In this study, seven universal facial expressions were used, including "joy, surprise, contempt, sadness, fear, disgust, and angle" (page 1644) [60]. For each emotional expression, four emotion intensity levels were animated (low, medium, high, and extreme), which correspond to four different difficulty levels in facial expression recognition where the lower intention level the more difficult to recognize.…”

“…To collect direct input from a participant, a conventional approach is to use a menu-driven interface or to display all possible options on the screen where a participant would choose the right answer from several response options using the mouse pointer [40,41,[59][60][61]. It is also common to require a participant to type a key as the answer, for example, "A" for the anger emotion, and "H" for the happy emotion.…”

“…It is interesting to note that not only the correctness of the selection or input is important, but in some research, the response time, i.e., the time it takes for a participant to make the selection/input since the prompt of the question is also recorded because this delay can be scientifically significant. For example, in [60], the response time was recorded to validate their hypothesis that it takes longer time for a child with ASD to recognize a facial affect than that for a typical developing child.…”

Introduction to Technologies in the Daily Lives of Individuals with Autism

“…In contrast to other recent virtual reality work examining therapeutic or educational aspects of virtual reality (e.g. Bekele et al 2014;Smith et al 2015), Kim et al (2015) examine how technological platforms may provide additional insights regarding phenotypic variation at the group or individual level. This last area, that of the exceptional monitoring and dense data collection capabilities of many technological platforms, is especially topical as it can often be overshadowed by a singular focus on therapeutic outcomes.…”