Evaluation et rééducation des expressions faciales émotionnelles chez l’enfant avec TSA : le projet JEMImE

The autism spectrum disorder (ASD) is characterized by difficulties in socials skills, as emotion recognition and production. Several studies focused on emotional facial expressions (EFE) recognition, but few worked on its production, either in typical children or in children with ASD. Nowadays, information and communication technologies are used to work on social skills in ASD but few studies using these technologies focus on EFE production. After a literature review, we found only 4 games regarding EFE production. Our final goal was to create the serious game JEMImE to work on EFE production with children with ASD using an automatic feedback. We first created a dataset of EFE of typical children and children with ASD to train an EFE recognition algorithm and to study their production skills. Several factors modulate them, such as age, type of emotion or culture. We observed that human judges and the algorithm assess the quality of the EFE of children with ASD as poorer than the EFE of typical children. Also, the EFE recognition algorithm needs more features to classify their EFE. We then integrated the algorithm in JEMImE to give the child a visual feedback in real time to correct his/her productions. A pilot study including 23 children with ASD showed that children are able to adapt their productions thanks to the feedback given by the algorithm and illustrated an overall good subjective experience with JEMImE. The beta version of JEMImE shows promising potential and encourages further development of the game in order to offer longer game exposure to children with ASD and so allow a reliable assessment of the effect of this training on their production of EFE.Le trouble du Spectre de l’Autisme (TSA) est caractérisé par des difficultés concernant les habiletés sociales dont l’utilisation des expressions faciales émotionnelles (EFE). Si de nombreuses études s’intéressent à leur reconnaissance, peu évaluent leur production chez l’enfant typique et avec TSA. Les nouvelles technologies sont plébiscitées pour travailler les habiletés sociales auprès des enfants avec TSA, or, peu d’études concernent leur utilisation pour le travail de la production des EFE. Au début de ce projet, nous retrouvions seulement 4 jeux la travaillant. Notre objectif a été la création du jeu sérieux JEMImE travaillant la production des EFE chez l’enfant avec TSA grâce à un feedback automatisé. Nous avons d’abord constitué une base de données d’EFE d’enfants typiques et avec TSA pour créer un algorithme de reconnaissance des EFE et étudier leurs compétences de production. Plusieurs facteurs les influencent comme l’âge, le type d’émotion, la culture. Les EFE des enfants avec TSA sont jugées de moins bonne qualité par des juges humains et par l’algorithme de reconnaissance des EFE qui a besoin de plus de points repères sur leurs visages pour classer leurs EFE. L’algorithme ensuite intégré dans JEMImE donne un retour visuel en temps réel à l’enfant pour corriger ses productions. Une étude pilote auprès de 23 enfants avec TSA met en avant une bonne adaptation des enfants aux retours de l’algorithme ainsi qu’une bonne expérience dans l’utilisation du jeu. Ces résultats prometteurs ouvrent la voie à un développement plus poussé du jeu pour augmenter le temps de jeu et ainsi évaluer l’effet de cet entraînement sur la production des EFE chez les enfants avec TSA

Assessment and rehabilitation of emotional facial expressions in children with ASD : the JEMImE project

Le trouble du Spectre de l’Autisme (TSA) est caractérisé par des difficultés concernant les habiletés sociales dont l’utilisation des expressions faciales émotionnelles (EFE). Si de nombreuses études s’intéressent à leur reconnaissance, peu évaluent leur production chez l’enfant typique et avec TSA. Les nouvelles technologies sont plébiscitées pour travailler les habiletés sociales auprès des enfants avec TSA, or, peu d’études concernent leur utilisation pour le travail de la production des EFE. Au début de ce projet, nous retrouvions seulement 4 jeux la travaillant. Notre objectif a été la création du jeu sérieux JEMImE travaillant la production des EFE chez l’enfant avec TSA grâce à un feedback automatisé. Nous avons d’abord constitué une base de données d’EFE d’enfants typiques et avec TSA pour créer un algorithme de reconnaissance des EFE et étudier leurs compétences de production. Plusieurs facteurs les influencent comme l’âge, le type d’émotion, la culture. Les EFE des enfants avec TSA sont jugées de moins bonne qualité par des juges humains et par l’algorithme de reconnaissance des EFE qui a besoin de plus de points repères sur leurs visages pour classer leurs EFE. L’algorithme ensuite intégré dans JEMImE donne un retour visuel en temps réel à l’enfant pour corriger ses productions. Une étude pilote auprès de 23 enfants avec TSA met en avant une bonne adaptation des enfants aux retours de l’algorithme ainsi qu’une bonne expérience dans l’utilisation du jeu. Ces résultats prometteurs ouvrent la voie à un développement plus poussé du jeu pour augmenter le temps de jeu et ainsi évaluer l’effet de cet entraînement sur la production des EFE chez les enfants avec TSA.The autism spectrum disorder (ASD) is characterized by difficulties in socials skills, as emotion recognition and production. Several studies focused on emotional facial expressions (EFE) recognition, but few worked on its production, either in typical children or in children with ASD. Nowadays, information and communication technologies are used to work on social skills in ASD but few studies using these technologies focus on EFE production. After a literature review, we found only 4 games regarding EFE production. Our final goal was to create the serious game JEMImE to work on EFE production with children with ASD using an automatic feedback. We first created a dataset of EFE of typical children and children with ASD to train an EFE recognition algorithm and to study their production skills. Several factors modulate them, such as age, type of emotion or culture. We observed that human judges and the algorithm assess the quality of the EFE of children with ASD as poorer than the EFE of typical children. Also, the EFE recognition algorithm needs more features to classify their EFE. We then integrated the algorithm in JEMImE to give the child a visual feedback in real time to correct his/her productions. A pilot study including 23 children with ASD showed that children are able to adapt their productions thanks to the feedback given by the algorithm and illustrated an overall good subjective experience with JEMImE. The beta version of JEMImE shows promising potential and encourages further development of the game in order to offer longer game exposure to children with ASD and so allow a reliable assessment of the effect of this training on their production of EFE

Evaluation du langage de l'enfant de 18 à 36 mois : Adaptation d'Antoine et Caroline

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Evaluation du langage de l'enfant de 18 à 36 mois : Adaptation d'Antoine et Caroline

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Serious games to teach social interactions and emotions to individuals with autism spectrum disorders (ASD)

International audienceThe use of information communication technologies (ICTs) in therapy offers new perspectives for treating many domains in individuals with autism spectrum disorders (ASD) because they can be used in many different ways and settings and they are attractive to the patients. We reviewed the available literature on serious games that are used to teach social interactions to individuals with ASD. After screening the Medline, Science Direct and ACM Digital Library databases, we found a total of 31 serious games: 16 that targeted emotion recognition or production and 15 that targeted social skills. There was a significant correlation between the number of reports per year and the year of publication. Serious games appeared promising because they can support training on many different skills and they favour interactions in diverse contexts and situations, some of which may resemble real life. However, the currently available serious games exhibit some limitations: (i) most of them are developed for High-Functioning individuals; (ii) their clinical validation has rarely met the evidence-based medicine standards; (iii) the game design is not usually described; and, (iv) in many cases, the clinical validation and playability/game design are not compatible

ICT and autism care

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Automatic Analysis of Typical and Atypical Encoding of Spontaneous Emotion in the Voice of Children

International audienceChildren with Autism Spectrum Disorders (ASD) present significant difficulties to understand and express emotions. Systems have thus been proposed to provide objective measurements of acoustic features used by children suffering from ASD to encode emotion in speech. However, only a few studies have exploited such systems to compare different groups of children in their ability to express emotions, and even less have focused on the analysis of spontaneous emotion. In this contribution, we provide insights by extensive evaluations carried out on a new database of spontaneous speech inducing three emotion categories of valence (positive, neutral, and negative). We evaluate the potential of using an automatic recognition system to differentiate groups of children, i.e., pervasive developmental disorders, pervasive developmental disorders not-otherwise specified, specific language impairments, and typically developing, in their abilities to express spontaneous emotion in a common unconstrained task. Results show that all groups of children can be differentiated directly (diagnosis recognition) and indirectly (emotion recognition) by the proposed system

Children Facial Expression Production: Influence of Age, Gender, Emotion Subtype, Elicitation Condition and Culture

The production of facial expressions (FEs) is an important skill that allows children to share and adapt emotions with their relatives and peers during social interactions. These skills are impaired in children with Autism Spectrum Disorder. However, the way in which typical children develop and master their production of FEs has still not been clearly assessed. This study aimed to explore factors that could influence the production of FEs in childhood such as age, gender, emotion subtype (sadness, anger, joy, and neutral), elicitation task (on request, imitation), area of recruitment (French Riviera and Parisian) and emotion multimodality. A total of one hundred fifty-seven children aged 6–11 years were enrolled in Nice and Paris, France. We asked them to produce FEs in two different tasks: imitation with an avatar model and production on request without a model. Results from a multivariate analysis revealed that: (1) children performed better with age. (2) Positive emotions were easier to produce than negative emotions. (3) Children produced better FE on request (as opposed to imitation); and (4) Riviera children performed better than Parisian children suggesting regional influences on emotion production. We conclude that facial emotion production is a complex developmental process influenced by several factors that needs to be acknowledged in future research

JEMImE: A Serious Game to Teach Children with ASD How to Adequately Produce Facial Expressions

International audienc