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Automated Robotic System For Autism Treatment

机译:自动化处理自动机器人系统

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摘要

This article is about possible implementation of automated robotic system for children's autism treatment. There are many well established approaches to autism treatment, however all of them are done manually by therapists and parents. In order to reduce manual work, we try to partially automate ABA method -, the one which has practically proved to be useful and scientifically well researched, - applied behaviour analysis based treatment. Simply put ABA, among others, includes time-consuming and laborious procedures which can be transferred into computational tasks. That allows us to apply computational algorithms from data mining and computer vision domain. Therefore, we propose that automation and further data intellectual analysis can increase productivity and effectiveness of applied method. In this work we first look at socio-economic and social aspects of issue, analyse frequently used methods and then based on specifics of autism and applied treatment we suggest basic workflow for automation of ABA method and data intellectual analysis. Workflow includes video and audio data acquisition and preprocessing for further emotion and behaviour recognition in correlation to external events. Similarly, suggested system allows monitoring and possible alteration of child's performance throughout the course of treatment. System implementation is heavily dependent on data mining and computer vision technologies, such as neural networks, clustering algorithms, video segmentation, feature extraction etc. Desired performance of overall system and its units is made possible by the function of feedback, on hardware and software level.
机译:本文是关于儿童自闭症治疗的自动机器人系统可能的实现。自闭症治疗有许多成熟的方法,但所有这些方法都是由治疗师和父母手动完成的。为了减少手动工作,我们试图部分自动化ABA方法 - ,实际证明是有用和科学良好的研究,基于应用的行为分析的治疗方法。简单地放置ABA,包括耗时和费力的程序,可以转移到计算任务中。这允许我们从数据挖掘和计算机视觉域应用计算算法。因此,我们建议自动化和进一步的数据智力分析可以提高应用方法的生产力和有效性。在这项工作中,我们首先研究了问题的社会经济和社会方面,分析了经常使用的方法,然后根据自闭症和应用的细节,我们建议ABA方法和数据智力分析的自动化基本工作流程。工作流程包括视频和音频数据采集和预处理,用于进一步的情感和行为识别与外部事件相关。同样,建议的系统允许在整个治疗过程中监测和可能改变孩子的表现。系统实现严重依赖于数据挖掘和计算机视觉技术,例如神经网络,聚类算法,视频分割,特征提取等。通过反馈的功能,在硬件和软件级别的功能,实现了整体系统的所需性能。

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