Facing the challenge of teaching emotions to individuals with low- and high-functioning autism using a new Serious game: a pilot study

Abstract

BackgroundIt is widely accepted that emotion processing difficulties are involved in Autism Spectrum Conditions (ASC). An increasing number of studies have focused on the development of training programs and have shown promising results. However, most of these programs are appropriate for individuals with high-functioning ASC (HFA) but exclude individuals with low-functioning ASC (LFA). We have developed a computer-based game called JeStiMulE based on logical skills to teach emotions to individuals with ASC, independently of their age, intellectual, verbal and academic level.The aim of the present study was to verify the usability of JeStiMulE (which is its adaptability, effectiveness and efficiency) on a heterogeneous ASC group. We hypothesized that after JeStiMulE training, a performance improvement would be found in emotion recognition tasks.MethodsA heterogeneous group of thirty-three children and adolescents with ASC received two one-hour JeStiMulE sessions per week over four weeks. In order to verify the usability of JeStiMulE, game data were collected for each participant. Furthermore, all participants were presented before and after training with five emotion recognition tasks, two including pictures of game avatars (faces and gestures) and three including pictures of real-life characters (faces, gestures and social scenes).ResultsDescriptive data showed suitable adaptability, effectiveness and efficiency of JeStiMulE. Results revealed a significant main effect of Session on avatars (ANOVA: F (1,32) = 98.48, P < .001) and on pictures of real-life characters (ANOVA: F (1,32) = 49.09, P < .001). A significant Session × Task × Emotion interaction was also found for avatars (ANOVA: F (6,192) = 2.84, P = .01). This triple interaction was close to significance for pictures of real-life characters (ANOVA: F (12,384) = 1.73, P = .057). Post-hoc analyses revealed that 30 out of 35 conditions found a significant increase after training.ConclusionsJeStiMulE appears to be a promising tool to teach emotion recognition not only to individuals with HFA but also those with LFA. JeStiMulE is thus based on ASC-specific skills, offering a model of logical processing of social information to compensate for difficulties with intuitive social processing.Trial registrationComité de Protection des Personnes Sud Méditerranée V (CPP): reference number 11.046 (https://cpp-sud-mediterranee-v.fr/).

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

“…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.…”

“…Many pilot studies simply validated a predefined set of hypotheses using their programs [28,38,41,85]. In all studies, the usability of the programs used could also be evaluated [61]. A special case for usability study is testing the acceptability of a new way of delivering content to individuals with ASD, such as [48,153], where a consumer-grade head-mounted virtual reality goggle was experimented.…”

“…The user is also asked to calibrate the tactile feedback of the game controller he/she will be using in the program because the authors anticipated that different users would have different sensitivity preferences. Furthermore, different methods were provided in [61] for a user to indicate the specific emotion they recognized, including a visual non-verbal code where each emotion to be recognized was represented by a particular color/icon (happiness was represented by yellow, angle was represented by red, disgust was represented purple, fear was represented by green, sadness was represented by light blue, surprise was indicated by dark blue, pain was represented by black, neutral was represented by white, and funny face was represented by a trash can), emotional words that told the emotion as it was, and idiomatic expressions, which were short sentences containing a figurative meaning, e.g., an idiomatic expression for fear could be "to get cold feet". In [25], all three motion-based games were designed for customizability.…”

“…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. Unity is also used in [61] for virtual reality production, where both static and animated avatars are used and are capable of making ten different facial motions, including happiness, anger, disgust, fear, sadness, surprise, pain, neutral, and funny face. Unlike other studies, in [61], a game controller (referred to as gamepad in the paper) was used to control the avatars, control the cursors for answering questions, and receive vibration based tactile feedback.…”

“…In [61], a user is asked to customize the avatar and the virtual environment of his/her choice. The user is also asked to calibrate the tactile feedback of the game controller he/she will be using in the program because the authors anticipated that different users would have different sensitivity preferences.…”