Concentration Level Detection Using EEG Signal on Reading Practice Application
Concentration Level Detection Using EEG Signal on Reading Practice Application
复制标题
利用脑电信号检测浓度水平在阅读练习中的应用
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Pradareza S.T. Muhammad
中科院分区：
文献类型：
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作者：
I. Zaeni;U. Pujianto;A. R. Taufani;Mahfud Jiono;Pradareza S.T. Muhammad
学习专注是一个有趣的研究课题。一个人在学习时的注意力集中程度，例如他/她在阅读时的注意力集中程度，可以用脑电图仪来测量。放松状态下的α波较高，而注意状态下的β波较高。在这项研究中，阅读实践的应用程序已经开发。该应用程序可用于控制文本阅读器的页面转换，同时也记录用户的脑电图（EEG）。在本研究中，受试者被要求阅读3段，并回答4个问题的多项选择测试的每一段。当受试者阅读文本时，记录他/她的EEG信号。然后将受试者在每个段落上获得的分数与他/她阅读该特定段落时记录的平均EEG频带功率进行比较。通过使用α和β波，估计受试者在他/她阅读阅读材料之后的分数。利用人工神经网络建立了预测模型。该估计模型使用四个输入，即低阿尔法功率、高阿尔法功率、低贝塔功率和高贝塔功率。结果表明，该方法的准确率为73.81%，属于合理范围。
Learning concentration is an interesting topic to study. The concentration while a person study such as when he/she reading can be measured using electroencephalograph. Alpha wave is higher in the relaxation state while Beta wave is higher in the attention state. In this study, an application for reading practice has been developed. The application can be used to control page transition of text reader and also recording the electroencephalograph (EEG) of the user at the same time. In this study, the subject is asked read 3 paragraph and answer 4 question multiple choice test for each paragraph. While the subject reading the text, his/her EEG signal is recorded. The score that earned by the subject on each paragraph is then compared to the average EEG band power recorded while he/she read that particular paragraph. By using the alpha and beta wave, the score of the subject after he/she read the reading material is estimated. The Artificial Neural Network is used to develop the estimation model. There are four inputs that is used on this estimation model, namely low alpha power, high alpha power, low beta power, and high beta power. The result shows that the accuracy is 73.81% which can be categorized as reasonable.
DOI：
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发表时间：
2009
期刊：
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影响因子：
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作者：
S. Tong;N. Thakor
通讯作者：
S. Tong;N. Thakor