基于EMD方法和加窗的QRS波群检测算法  

QRS Complex Detection Using Empirical Mode Decomposition and Windowing Technique

作　　者：张开玉[1] 王立[2] 王玉静[1] 宋立新[1] 

机构地区：[1]哈尔滨理工大学电气与电子工程学院,哈尔滨150080 [2]黑龙江省医院,哈尔滨150040

出　　处：《生物医学工程学杂志》2012年第3期411-414,423,共5页Journal of Biomedical Engineering

基　　金：黑龙江省自然科学基金资助项目(F200912)

摘　　要：提出了一种基于经验模态分解(EMD)方法和自适应加窗技术的QRS波群检测算法,该算法主要是利用Hilbert-Huang变换提出适合QRS波群检测的EMD方法,利用该算法对sddb数据库中第30号信号和mitdb数据库中第208号信号进行处理,得到R波的检测结果;同时,利用自适应加窗技术对Q点和S点的检测技术进行分析。通过对MIT/BIT心率异常数据库的部分数据进行R波检测,结果表明,本文提出的算法具有很好的检测效果,其R波的平均正确检测率达到了99.62%,QRS波群的平均敏感性为98.91%,相应的平均特异性为99.35%。A QRS complex detection algorithm based on empirical mode decomposition （EMD） and adaptive windo- wing technique is proposed in this paper. In this algorithm we mainly used Hilbert-Huang transform to propose EMD method suitable for QRS complex detection, with which the 30th signal in sddb database and the 208th signal in mit- db database could be processed, and then obtained R wave detection results. At the same time, Q and S points＇ dect- ection technique was analyzed With adaptive windowing technique. The detection results, through proceeding R wave detection on part data of MIT/BIT arrhythmia database, showed that the proposed algorithm in this paper had a very good detection effect, and that its average correct detection rate of R wave reached 99.62%, its average sensitivity of QRS complex was 98.91%, and the corresponding average specificity was 99.35%.

关 键 词：经验模态分解 加窗技术 Hilbert—Huang变换 QRS波群检测 

分 类 号：R318.0[医药卫生—生物医学工程] TN911.6[医药卫生—基础医学]