本文關(guān)鍵詞： 腦電圖 多動癥 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檢測方法輔助多動癥兒童進行臨床個體化診斷。首先基于一種經(jīng)典的干擾控制試驗任務(wù)Simon-spatial Stroop范例采集14名多動癥兒童和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(SVM)分類器來分類。實驗發(fā)現(xiàn)同種試驗任務(wù)中多動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)時間;多動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),且多動癥兒童的峰值更低;在該實驗中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,干擾控制試驗中多動癥兒童與正常兒童的前額葉及頂枕葉的腦電信號存在差異,該結(jié)果可為多動癥個體的腦電信號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)重點實驗室;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)基金資助項目(61201096) 常州市科技資助項目(CE20145055) 江蘇省“青藍工程”資助項目
【分類號】：R749.94

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