Emotional child-robot interaction helps catching quickly child attention and enhancing information perception during learning and verbalization in children with Special Educational Needs (SEN). This will improve the pedagogical rehabilitation for these children and also develop their emotional knowledge and memory in play-like activities mediated by emotion-expressive social robots. The designed by us EEG-based portable Brain-Computer Interface (BCI) measures and features the brain electrical activity in real time in order to analyze the correlated attentional or emotional states of a child. Different BCI outputs can assist special educators in assessment of the emotional and cognitive performance of a child or can be used directly as inputs for robot control. BCI is a new technology for human-robot interaction and it can evolve into technology for self-regulatory training of attention and emotional skills via neurofeedback exposed on a robot. Since the attention or emotional responses of children with SEN make robots to act, these skills are naturally reinforced in the play. Two research protocols based on this idea are presented. They describe the procedures for conducting custom scenarios for robotic intervention with a portable brain-listening headset. The proposed BCI is used to translate the human brain activity, head motion and eye movement during the process of expressing emotions into robot commands. Then, they are wirelessly transmitted to the robot sensors, modules and controllers by a new designed BCI-Robot framework. This study marks a first step towards the way of utilizing the advantages of educational theater in Social Robotics in order to transfer the emotional talent of an actor to an emotion-expressive robot.


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    Title :

    . Social Robots For Reinforcing Attention And Forming Emotional Knowledge Of Children With Special Educational Needs


    Contributors:
    Lekova A (author) / Tanev T (author) / Vassileva-Aleksandrova V (author) / Kostova S. (author) / Dachkinov P. (author)

    Publication date :

    2019-10-25


    Remarks:

    oai:zenodo.org:3518978



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629





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