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基于腦電主成分分析和k-最近鄰的多動(dòng)癥兒童與正常兒童分類研究

發(fā)布時(shí)間:2018-02-28 21:07

  本文關(guān)鍵詞: 腦電圖 多動(dòng)癥 干擾控制 主成分分析 分類 出處:《生物醫(yī)學(xué)工程學(xué)雜志》2016年02期  論文類型:期刊論文


【摘要】:本文嘗試通過腦電信號(hào)檢測方法輔助多動(dòng)癥兒童進(jìn)行臨床個(gè)體化診斷。首先基于一種經(jīng)典的干擾控制試驗(yàn)任務(wù)Simon-spatial Stroop范例采集14名多動(dòng)癥兒童和16名正常兒童的腦電數(shù)據(jù),并完成濾波、分段、去偽跡等預(yù)處理;然后采用主成分分析(PCA)進(jìn)行電極優(yōu)化選擇,分別選取每種刺激模式下出現(xiàn)率90%以上的優(yōu)化電極作為共有電極,并提取共有電極潛伏期(200~450ms)波幅的均值特征;最后采用基于歐氏距離的k-最近鄰(KNN)和基于徑向基核函數(shù)的支持向量機(jī)(SVM)分類器來分類。實(shí)驗(yàn)發(fā)現(xiàn)同種試驗(yàn)任務(wù)中多動(dòng)癥兒童比正常兒童表現(xiàn)出更低的反應(yīng)正確率和更長的反應(yīng)時(shí)間;多動(dòng)癥兒童與正常兒童的前額葉優(yōu)化電極均出現(xiàn)N2,頂枕葉均有P2出現(xiàn),且多動(dòng)癥兒童的峰值更低;在該實(shí)驗(yàn)中KNN分類準(zhǔn)確率高于SVM分類器,StI刺激模式下KNN分類器的最高分類準(zhǔn)確率為89.29%。以上結(jié)果說明,干擾控制試驗(yàn)中多動(dòng)癥兒童與正常兒童的前額葉及頂枕葉的腦電信號(hào)存在差異,該結(jié)果可為多動(dòng)癥個(gè)體的腦電信號(hào)臨床診斷提供一定科學(xué)依據(jù)。
[Abstract]:This paper attempts to assist children with ADHD with clinical individualized diagnosis by means of EEG signal detection. Firstly, the EEG data of 14 children with ADHD and 16 normal children were collected based on a classical interference control test task, Simon-spatial Stroop. The preprocessing of filtering, segmenting and removing artifacts was completed, and then the electrode was optimized by principal component analysis (PCA), and the optimal electrode with a rate of more than 90% in each stimulus mode was selected as the common electrode, respectively. The mean values of the amplitudes of the shared electrode latencies (200 ~ 450ms) were extracted. Finally, the classification is done by using K- nearest neighbor (KNN) based on Euclidean distance and support vector machine (SVM) classifier based on radial basis function kernel function. It is found that children with ADHD in the same task have lower response than normal children. Rate and longer reaction time; In children with ADHD and normal children, N2 was found in prefrontal lobe, P2 in parietal occipital lobe, and the peak value was lower in ADHD children. In this experiment, the accuracy of KNN classification is higher than that of KNN classifier under SVM stimulus mode, which is 89.29. The EEG signals in prefrontal lobe and parietal occipital lobe of ADHD children and normal children are different in interference control test. The results can provide a scientific basis for the clinical diagnosis of EEG in ADHD individuals.
【作者單位】: 常州大學(xué)信息科學(xué)與工程學(xué)院;常州市生物醫(yī)學(xué)信息技術(shù)重點(diǎn)實(shí)驗(yàn)室;蘇州大學(xué)附屬第三醫(yī)院腦科學(xué)研究中心;
【基金】:國家自然科學(xué)基金資助項(xiàng)目(61201096) 常州市科技資助項(xiàng)目(CE20145055) 江蘇省“青藍(lán)工程”資助項(xiàng)目
【分類號(hào)】:R749.94

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