【摘要】：動脈硬化無創(chuàng)檢測對于預防心血管事件具有重要意義。然而,基于心電信號或脈搏波信號的單一特征源的無創(chuàng)動脈硬化檢測無法全面反映心血管動脈硬化事件。為了提高動脈硬化無創(chuàng)檢測識別精度,提出了基于心電信號、脈搏波信號的多源數(shù)據(jù)無創(chuàng)動脈硬化識別方法,構(gòu)建了具有變異特性的蟻群聚類算法,對提取的40組臨床心電、脈搏波信號的特征值向量進行監(jiān)督分類。通過對系統(tǒng)測試結(jié)果與專家分類結(jié)果對比分析,表明該方法提高了單一特征源的動脈硬化識別率,是一種有效的動脈硬化無創(chuàng)識別方法。
[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)蒙古師范大學物理與電子信息學院;內(nèi)蒙古農(nóng)業(yè)大學機電工程學院;內(nèi)蒙古大學電子信息工程學院;
【基金】：內(nèi)蒙古自然科學基金(No.2013MS0924) 國家自然科學基金(No.61461042) 內(nèi)蒙古師范大學科研基金(No.2012ZRYB001)
【分類號】：R54;TP18

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