Analysis of EOG Signals Related to ADHD and Healthy Children Using Wavelet Transform

2020 27th National and 5th International Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 2020-11-26 DOI:10.1109/ICBME51989.2020.9319413

Shahrzad Ayoubipour, Hami Hekmati, Nasrin Sho’ouri

{"title":"Analysis of EOG Signals Related to ADHD and Healthy Children Using Wavelet Transform","authors":"Shahrzad Ayoubipour, Hami Hekmati, Nasrin Sho’ouri","doi":"10.1109/ICBME51989.2020.9319413","DOIUrl":null,"url":null,"abstract":"Previous research has shown that eye movements are affected by attention and can be used for the examination of attention-related disorders. In the present study, the eye movements of ADHD individuals and healthy individuals were analyzed. For this purpose, EOG signals of 30 healthy children and 30 children with ADHD were decomposed using wavelet transform (WT) while performing an attention-related task. Then the approximation and detail wavelet coefficients features such as energy and standard deviation were calculated, and the differences between the two groups were detected using statistical tests. The results showed that the energy and standard deviation of the EOG signals’ detail coefficients in ADHD children were significantly lower (p<0.001). Therefore, possibly the high-frequency band activity of EOG signals was higher in healthy children in comparison with ADHD children. The results of this study are likely to be practical in designing an EOG biofeedback protocol for treating or reducing the symptoms of ADHD disorder.","PeriodicalId":120969,"journal":{"name":"2020 27th National and 5th International Iranian Conference on Biomedical Engineering (ICBME)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 27th National and 5th International Iranian Conference on Biomedical Engineering (ICBME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBME51989.2020.9319413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 5

Abstract

Previous research has shown that eye movements are affected by attention and can be used for the examination of attention-related disorders. In the present study, the eye movements of ADHD individuals and healthy individuals were analyzed. For this purpose, EOG signals of 30 healthy children and 30 children with ADHD were decomposed using wavelet transform (WT) while performing an attention-related task. Then the approximation and detail wavelet coefficients features such as energy and standard deviation were calculated, and the differences between the two groups were detected using statistical tests. The results showed that the energy and standard deviation of the EOG signals’ detail coefficients in ADHD children were significantly lower (p<0.001). Therefore, possibly the high-frequency band activity of EOG signals was higher in healthy children in comparison with ADHD children. The results of this study are likely to be practical in designing an EOG biofeedback protocol for treating or reducing the symptoms of ADHD disorder.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于小波变换的ADHD与健康儿童脑电信号分析

先前的研究表明，眼球运动受到注意力的影响，可以用于检查与注意力相关的疾病。本研究对ADHD个体和健康个体的眼球运动进行了分析。为此，对30名健康儿童和30名ADHD儿童在执行注意相关任务时的眼电信号进行小波变换(WT)分解。然后计算小波系数的近似特征和细节特征，如能量和标准差，并通过统计检验检测两组之间的差异。结果表明，ADHD儿童的脑电图信号细节系数的能量和标准差均显著降低(p<0.001)。因此，健康儿童的脑电图信号高频波段活度可能高于ADHD儿童。这项研究的结果可能是实用的设计脑电图生物反馈方案治疗或减少ADHD障碍的症状。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

2020 27th National and 5th International Iranian Conference on Biomedical Engineering (ICBME)

自引率

0.00%

发文量