基于云模型的窦性心率震荡形态表示  

Shock Shape Representation of Sinus Heart Rate Based on Cloud Model

作　　者：尹文枫 赵捷[1] 陈甜甜[1] 张军建[1] 张春游 李大鹏[1] 安佰京[1] 

机构地区：[1]山东师范大学物理与电子科学学院,济南250014

出　　处：《生物医学工程学杂志》2014年第2期279-282,共4页Journal of Biomedical Engineering

基　　金：山东省科技攻关项目资助(2007GG10001018);山东省自然科学基金资助项目(ZR2010HM020);济南市自主创新项目资助(201102005)

摘　　要：本文旨在分析单次室性早搏后窦性心率RR间期的变化趋势,与震荡起始(TO)和震荡斜率(TS)参数对照。在采集窦性心律震荡的样本后,采用一种分段线性化的方法来提取其线性特征,进而通过云模型用自然语言来表示震荡形态;在采集样本的过程中,本文采用指数平滑法预测QRS波出现位置来辅助QRS波的检测,利用新的轮廓限围方法判断窦性心律。利用Matlab仿真工具,选择MIT-BIH心率失常数据库中信号进行验证,能正确检测出单次室性早搏后窦性心率的变化趋势。该算法能实现窦性心律震荡(HRT)的实时检测,并且实现简单,是一种有效的辅助检测方法。The present paper is to analyze the trend of sinus heart rate RR interphase sequence after a single ventricu- lar premature beat and to compare it with the two parameters, turbulence onset （TO） and turbulence slope （TS）. Based on the acquisition of sinus rhythm concussion sample, we in this paper use a piecewise linearization method to extract its linear characteristics, following which we describe shock form with natural language through cloud model. In the process of acquisition, we use the exponential smoothing method to forecast the position where QRS wave may appear to assist QRS wave detection, and use template to judge whether current cardiac is sinus rhythm. And we choose some signals from MIT-BIH Arrhythmia Database to detect whether the algorithm is effective in Matlab. The results show that our method can correctly detect the changing trend of sinus heart rate. The proposed method can a- chieve real-time detection of sinus rhythm shocks, which is simple and easily implemented, so that it is effective as a supplementary method.

关 键 词：窦性心率震荡 分段线性化 指数平滑法 云模型 

分 类 号：R54[医药卫生—心血管疾病]