小波族对健康与ADHD儿童脑电信号分类的比较研究。

IF 1.6 4区 医学 Q3 CLINICAL NEUROLOGY
Clinical EEG and Neuroscience Pub Date : 2024-01-01 Epub Date: 2023-08-22 DOI:10.1177/15500594231192817
Shahrzad Ayoubipour, Nasrin Sho'ouri
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引用次数: 0

摘要

根据以往的研究,注意缺陷多动障碍(ADHD)患者的眼球运动与正常人存在差异,因此两组的眼电信号存在差异。因此,本研究旨在检查30名ADHD儿童和30名健康儿童在执行注意相关任务时记录的脑电图信号。为此,利用不同的小波函数对两组eeg信号进行分解。然后,计算近似和细节小波系数的均值、能量和标准差(SD)等特征。采用Davies-Bouldin (DB)指数对特征空间质量进行评价。最后,利用一维特征向量和支持向量机(SVM)对两组进行分类。选取细节系数的SD (db4)作为区分两组的最有效特征。统计分析发现,ADHD组脑电图信号细节系数的能量值和SD值明显低于健康组(P < 0.05)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comparative Investigation of Wavelet Families for Classification of EOG Signals Related to Healthy and ADHD Children.

Based on previous research, there are differences between eye movements of people with attention-deficit hyperactivity disorder (ADHD) and of healthy people, as a result, the existence of differences regarding the electrooculogram (EOG) signals of the 2 groups exists. Thus, this study aimed to examine the recorded EOG signals of 30 ADHD children and 30 healthy children while performing an attention-related task. For this purpose, the EOG signals of these 2 groups were decomposed utilizing various wavelet functions. Afterward, features, including mean, energy, and standard deviation (SD) of approximation and detail wavelet coefficients were calculated. The Davies-Bouldin (DB) index was used for the evaluation of the feature space quality. Finally, the 2 groups were classified using one-dimensional feature vector and support vector machine (SVM). The SD of detail coefficients (db4) was selected as the most effective feature for separating the 2 groups. Statistical analysis revealed that the values of energy and SD of EOG signals' detail coefficients were significantly lower in the ADHD group in comparison with the healthy group (P<.001). These results showed that the speed of the ADHD group's eye movements was slower due to the fact that the high-frequency band activity of EOG signals in the healthy group was higher. In addition, the EOG signals were classified with a detection accuracy of 83.42 ± 3.8%. The results of this study can be applied in designing an EOG biofeedback protocol to treat or mitigate the symptoms of ADHD patients.

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来源期刊
Clinical EEG and Neuroscience
Clinical EEG and Neuroscience 医学-临床神经学
CiteScore
5.20
自引率
5.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Clinical EEG and Neuroscience conveys clinically relevant research and development in electroencephalography and neuroscience. Original articles on any aspect of clinical neurophysiology or related work in allied fields are invited for publication.
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