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Addressing dysgraphia with a mobile, web-based software with interactive feedback

机译:使用带有交互式反馈的基于Web的移动软件解决打字困难

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Learning disabilities affect an increasing number of students. Among these disabilities, dysgraphia has a nonindifferent role since it undermines the writing communication abilities of the students, with side effects on their self-esteem and a great risk of reduced school performance and more difficult relationships with classmates. It is the opinion of many people that the right way to prevent students from losing the writing gesture and allow for the acquisition of the correct writing automatism is through supporting exercises and activities. With these aims in mind we have designed and developed a client-server web-based software system, usable through modern devices such as tablets and smartphones using cutting edge Javascript libraries and framework and sophisticated algorithms for multiple hand gesture recognition, namely the Dynamic Time Warping algorithm that has been modified to recognize composite gesture. The software tool offers the users the possibility to execute sets of different exercises types, organized in levels, from simple connect the dots to complete writing a word, and the writing is compared with a reference trace done by an expert. The software tool offers immediate feedback on the basis of objective parameters, as well as a comprehensive collection of data stored both in JSON and INKML format, useful for identifying, studying and rehabilitating dysgraphic handwriting.
机译:学习障碍影响着越来越多的学生。在这些残障人士中,书写障碍症的作用很重要,因为它会损害学生的写作交流能力,对他们的自尊产生副作用,并有降低学校成绩和与同学建立更艰难关系的巨大风险。许多人认为,防止学生失去写作姿态并获得正确的写作自动性的正确方法是通过支持练习和活动。考虑到这些目标,我们设计和开发了基于Web的客户端-服务器网络软件系统,可通过现代设备(如平板电脑和智能手机)使用最先进的Javascript库和框架以及用于多手势识别的复杂算法(即动态时间规整)来使用已被修改以识别合成手势的算法。该软件工具为用户提供了执行级别不同的练习集的可能性,从简单的连接点到完成单词的编写,都将其按级别组织起来,然后将笔迹与专家的参考迹线进行比较。该软件工具可根据客观参数以及以JSON和INKML格式存储的数据的全面收集提供即时反馈,这对于识别,研究和修复笔迹手写很有用。

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