【摘要】：動(dòng)脈硬化無(wú)創(chuàng)檢測(cè)對(duì)于預(yù)防心血管事件具有重要意義。然而,基于心電信號(hào)或脈搏波信號(hào)的單一特征源的無(wú)創(chuàng)動(dòng)脈硬化檢測(cè)無(wú)法全面反映心血管動(dòng)脈硬化事件。為了提高動(dòng)脈硬化無(wú)創(chuàng)檢測(cè)識(shí)別精度,提出了基于心電信號(hào)、脈搏波信號(hào)的多源數(shù)據(jù)無(wú)創(chuàng)動(dòng)脈硬化識(shí)別方法,構(gòu)建了具有變異特性的蟻群聚類算法,對(duì)提取的40組臨床心電、脈搏波信號(hào)的特征值向量進(jìn)行監(jiān)督分類。通過(guò)對(duì)系統(tǒng)測(cè)試結(jié)果與專家分類結(jié)果對(duì)比分析,表明該方法提高了單一特征源的動(dòng)脈硬化識(shí)別率,是一種有效的動(dòng)脈硬化無(wú)創(chuàng)識(shí)別方法。
[Abstract]:Noninvasive detection of arteriosclerosis is of great significance in preventing cardiovascular events. However, noninvasive arteriosclerosis detection based on single characteristic source of ECG signal or pulse wave signal can not fully reflect cardiovascular arteriosclerosis events. In order to improve the accuracy of noninvasive detection and recognition of arteriosclerosis, a multi-source data noninvasive arteriosclerosis recognition method based on ECG and pulse wave signals was proposed, and an ant colony clustering algorithm with variation characteristics was constructed. 40 groups of clinical ECG were extracted. The eigenvalue vectors of pulse wave signal are supervised and classified. By comparing the system test results with the expert classification results, it is shown that the method improves the recognition rate of arteriosclerosis of a single characteristic source and is an effective noninvasive method for the identification of arteriosclerosis.
【作者單位】： 內(nèi)蒙古師范大學(xué)物理與電子信息學(xué)院;內(nèi)蒙古農(nóng)業(yè)大學(xué)機(jī)電工程學(xué)院;內(nèi)蒙古大學(xué)電子信息工程學(xué)院;
【基金】：內(nèi)蒙古自然科學(xué)基金(No.2013MS0924) 國(guó)家自然科學(xué)基金(No.61461042) 內(nèi)蒙古師范大學(xué)科研基金(No.2012ZRYB001)
【分類號(hào)】：R54;TP18

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