摘要
动脉硬化无创检测对于预防心血管事件具有重要意义。然而,基于心电信号或脉搏波信号的单一特征源的无创动脉硬化检测无法全面反映心血管动脉硬化事件。为了提高动脉硬化无创检测识别精度,提出了基于心电信号、脉搏波信号的多源数据无创动脉硬化识别方法,构建了具有变异特性的蚁群聚类算法,对提取的40组临床心电、脉搏波信号的特征值向量进行监督分类。通过对系统测试结果与专家分类结果对比分析,表明该方法提高了单一特征源的动脉硬化识别率,是一种有效的动脉硬化无创识别方法。
Non-invasive detection of arteriosclerosis for the prevention of cardiovascular events is important.In order toimprove the accuracy of arteriosclerosis recognition,this paper puts forward multi-source signal(ECG and pulse wave)recognition model to detect arteriosclerosis based on ant colony clustering algorithm with mutation features.The performanceof method is tested by40sets actual samples data.The compared results between simulation and professionalclustering show that the proposed method can improve the atherosclerosis recognition rate;therefore the proposed modelis an effective atherosclerosis non-invasive detection model.
作者
张丽娜
周润景
武佩
刘美玲
张珏
ZHANG Lina;ZHOU Runjing;WU Pei;LIU Meiling;ZHANG Jue(College of Physics and Electronic Information Science, Inner Mongolia Normal University, Hohhot 010022, China;College of Electronics and Information Engineering, Inner Mongolia University, Hohhot 010021, China;College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)
出处
《计算机工程与应用》
CSCD
北大核心
2017年第7期235-241,共7页
Computer Engineering and Applications
基金
内蒙古自然科学基金(No.2013MS0924)
国家自然科学基金(No.61461042)
内蒙古师范大学科研基金(No.2012ZRYB001)
关键词
心电信号
脉搏波信号
动脉硬化
蚁群算法
无创检测
ECG signal
pulse wave signal
arteriosclerosis
ant colony algorithm
non-invasive detection
