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System for Detecting Student Attention Pertaining and Alerting

机译:检测学生注意力和警报的系统

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Concentration is the ability to focus the mind on a specific context at a time. This is important to do any activities efficiently such as learning and driving. Especially, for students, it is tough to be stay focused because of the distractions. A single moment of drifting in mind may cause a significant impact on student's performance. Therefore finding that moment and alert the student to regain attention, would help him to improve the ability to be concentrated while learning. Several types of researches have been conducted to find out the connection between concentration and human related parameters such as heart rate variability, brain waves, and facial expressions while learning. We propose a methodology to combine these three parameters, expected to overcome the limitations of one parameter by another. The extracted features from each collected data from the relevant sensors are fed into the classification models. As per the initial experiments, the primary relationships were derived with separate machine learning models for each parameter.
机译:浓度是一次将心灵集中在特定上下文中的能力。这对于有效地进行任何活动,例如学习和驾驶是很重要的。特别是,对于学生而言,由于分心,它很难被关注。一刻漂移的漂流可能会对学生的表现产生重大影响。因此,发现那一刻并提醒学生重新引起关注,有助于他提高学习的能力。已经进行了几种研究以找出浓度和人类相关参数之间的联系,例如心率变异性,脑波和面部表情在学习时。我们提出了一种方法来结合这三个参数,预计将克服另一个参数的局限性。来自相关传感器的每个收集数据的提取特征被馈送到分类模型中。根据初始实验,主要关系是针对每个参数的单独机器学习模型推导出主要关系。

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