LOWNS分类信号检测技术  

The Technique of Detecting Lowns Classification

作　　者：王越[1] 赵捷[1] 赵艳娜[1] 田杰[1] 李群[1] 

机构地区：[1]山东师范大学物理与电子科学学院

出　　处：《现代生物医学进展》2009年第22期4354-4356,共3页Progress in Modern Biomedicine

基　　金：山东省科技攻关项目(2007GG10001018);山东省自然科学基金(Y2007G05)

摘　　要：目的:检测出Lown分级中各种室性心律失常,进一步完善便携式心电仪中心电的诊断分析,增强其功能。方法:本文提出一种在基于小波变换理论上检测出R波的基础上,采用适当的阀值并结合新的模板匹配方法检测出室性早搏,并进而检测出Lown分级中各种室性心律失常。结果: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,能正确检测出各种室性心律失常,错检率较低,实现简单,适合实时处理。结论:此方法正确率高,符合心电分析要求,进行算法优化后可嵌入到心电检测仪中实现应用,为便携式心电仪功能的完善有很大的帮助。Objective：To detect ventricular arrhythmia of Lowns and further improve the function of ECG diagnosis and analysis of portable electrocardiograph （ECG） monitor. Methods： In this paper, a method for detecting the typical ventricular arrhythmia was proposed, which is based on the wavelet transform to detect the R-wave, and to use the appropriate threshold in combination with the new template matching method to detect premature ventricular contractions （PVC）, and thus to detect a variety of typical ventricular arrhythmias of Lowns. Results： We choose some signals from MIT-BIH Arrhythmia Database; the results show that our method can correctly detect all kinds of typical ventricular arrhythmia,The fallout ratio is low. It is simple and easily implemented. So it is suitable for real-time processing. Conclusion： Our method has a higher accuracy, after optimization the algorithm can be embedded in portable electrocardiograph （ECG） monitor. It has a great help for perfect the function of portable electrocardiograph （ECG） monitor.

关 键 词：ECG LOWN分级 室性心律失常 模板 阀值 

分 类 号：R318[医药卫生—生物医学工程] TP391[医药卫生—基础医学]