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      VALE-Emotions: Teaching mobile application for individuals with Autism Spectrum Disorders Translated title: VALE-Emotions: Aplicación móvil de enseñanza para individuos con Desordenes del Espectro Autista

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          Abstract

          Abstract: In this paper, the development of an interactive mobile application to strengthen the learning of emotion recognition in children with Autism Spectrum Disorders (ASD) is presented. This App is part of an authoring Virtual Advanced Learning Environment (VALE) devoted to support teaching and learning activities. VALE-Emotions App is based on the six basic emotions studied by (Paul Ekman, 1992), but it is not only limited to the recognition of such emotions in their highest intensity levels. In fact, the app allows for determining the effective recognition of these emotions at different intensity levels. Such intensity levels are generated by an authoring Dynamic Facial Expressions (DFE) coding using virtual avatars. Each learning activity is carried out through training and tests applications, giving to the users the opportunity of freely developing, learning, and strengthen social skills in an entertaining way. The results of the experimentation of the VALE-Emotions on subjects with ASD are also reported. In general, the participants showed efficient response at the stimulus during the developed activities obtaining a high and fast recognition of certain emotions.

          Translated abstract

          Resumen: En este artículo, se presenta el desarrollo de una aplicación móvil interactiva para fortalecer el aprendizaje de reconocimiento de emociones en niños con Desordenes del Espectro Autista (ASD, en inglés). Esta App forma parte de un Avanzado Ambiente Virtual de Aprendizaje (VALE, en inglés), propuesto por los autores para soportar actividades de enseñanza y aprendizaje. La App VALE-Emotions está fundamentada en las seis emociones básicas estudiadas por (Paul Ekman, 1992), pero no está limitada solo al reconocimiento de tales emociones en sus máximos niveles de intensidad. De hecho, la App permite determinar el reconocimiento efectivo de estas emociones a diferentes niveles de intensidad. Tales niveles de intensidad son generados por una codificación propuesta por los autores mediante un DFE (Expresiones Faciales Dinámicas, en español) usando avatars virtuales. Cada actividad de aprendizaje es realizada a través de aplicaciones de entrenamiento y evaluación, dando la oportunidad a los usuarios de desarrollar, aprender y fortalecer libremente habilidades sociales de una manera entretenida. Además, se reportan los resultados de experimentación usando VALE-Emotions en individuos con ASD. En general, los participantes mostraron una eficiente respuesta a los estímulos durante las actividades desarrolladas obteniendo un alto y rápido reconocimiento de ciertas emociones.

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          Measuring facial expressions by computer image analysis.

          Facial expressions provide an important behavioral measure for the study of emotion, cognitive processes, and social interaction. The Facial Action Coding System (Ekman & Friesen, 1978) is an objective method for quantifying facial movement in terms of component actions. We applied computer image analysis to the problem of automatically detecting facial actions in sequences of images. Three approaches were compared: holistic spatial analysis, explicit measurement of features such as wrinkles, and estimation of motion flow fields. The three methods were combined in a hybrid system that classified six upper facial actions with 91% accuracy. The hybrid system outperformed human nonexperts on this task and performed as well as highly trained experts. An automated system would make facial expression measurement more widely accessible as a research tool in behavioral science and investigations of the neural substrates of emotion.
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            The use and understanding of virtual environments by adolescents with autistic spectrum disorders.

            The potential of virtual environments for teaching people with autism has been positively promoted in recent years. The present study aimed to systematically investigate this potential with 12 participants with autistic spectrum disorders (ASDs), each individually matched with comparison participants according to either verbal IQ or performance IQ, as well as gender and chronological age. Participants practised using a desktop 'training' virtual environment, before completing a number of tasks in a virtual café. We examined time spent completing tasks, errors made, basic understanding of the representational quality of virtual environments and the social appropriateness of performance. The use of the environments by the participants with ASDs was on a par with their PIQ-matched counterparts, and the majority of the group seemed to have a basic understanding of the virtual environment as a representation of reality. However, some participants in the ASD group were significantly more likely to be judged as bumping into, or walking between, other people in the virtual scene, compared to their paired matches. This tendency could not be explained by executive dysfunction or a general motor difficulty. This might be a sign that understanding personal space is impaired in autism. Virtual environments might offer a useful tool for social skills training, and this would be a valuable topic for future research.
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              Verbal bias in recognition of facial emotions in children with Asperger syndrome.

              Thirteen children and adolescents with diagnoses of Asperger syndrome (AS) were matched with 13 nonautistic control children on chronological age and verbal IQ. They were tested on their ability to recognize simple facial emotions, as well as facial emotions paired with matching, mismatching, or irrelevant verbal labels. There were no differences between the groups at recognizing simple emotions but the Asperger group performed significantly worse than the control group at recognizing emotions when faces were paired with mismatching words (but not with matching or irrelevant words). The results suggest that there are qualitative differences from nonclinical populations in how children with AS process facial expressions. When presented with a more demanding affective processing task, individuals with AS showed a bias towards visual-verbal over visual-affective information (i.e., words over faces). Thus, children with AS may be utilizing compensatory strategies, such as verbal mediation, to process facial expressions of emotion.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                enfoqueute
                Enfoque UTE
                Enfoque UTE
                Universidad Tecnológica Equinoccial (Quito, Pichincha, Ecuador )
                1390-9363
                1390-6542
                February 2017
                : 8
                : suppl 1
                : 358-373
                Affiliations
                [1] Riobamba Chimborazo orgnameEscuela Superior Politécnica de Chimborazo Ecuador diana.olmedoespoch.edu.ec, jorge.hernandezespoch.edu.ec, davila@ 123456espoch.edu.ec
                [2] Rende orgnameUniversità della Calabria Italia eleonora.bilottaunical.it, piepa@ 123456unical.it
                Article
                S1390-65422017000100358
                10.29019/enfoqueute.v8n1.145
                4545b120-f3d6-4e5e-aca4-963fd34b9dec

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 09 January 2017
                : 24 February 2017
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 27, Pages: 16
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                Expresiones Faciales Dinámicas,Aplicaciones Móviles;,Emotions Recognition,Autism,Dynamic Facial Expressions,Mobile Application;,Reconocimiento de Emociones,Autismo

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