摘要
目的使用能量变换与小波分解的联合算法检测心电信号QRS波群的特征点,为心电信号的自动分析提供新的手段。方法能量变换是基于信号的局部特征的,可以有效地突出信号的峰点或谷点;小波分解对信号做多分辨率分解,可以突出信号的特征信息;两种方法的结合更利于QRS波群的检测。结果使用30例样本检测算法性能,证明联合算法能够提高信噪比,对特征点的定位准确可靠。经MIT/BIH心电数据库的检测验证,其R波定位的正确率高达99.79%。使用心率趋势图分析计算结果,不仅可以完全纠正误检和漏检,而且能够定位异常的心搏。结论本算法能够准确、实时地识别被噪声严重干扰的心电信号的QRS波群,因而在心电信号的自动分析中有很好的应用前景。
Objective To find a new method for ECG auto-analysis of through the combination of energy transform and wavelet decomposition for detecting the characteristic point of QRS complex. Methods The energy transform was based on the signal shape and clarified its peaks or valleys. The wavelet transform did multi-resolution analysis on the signal and clarified the ECG characteristics. The combined way could detect the QRS complex easier. Results Based on 30 samples, test proved that the new combined approach improved the signal-to-noise ratio, accuracy and reliability. By using the MIT/BIH arrhythmia database, the QRS detected rate rose to 99.79%. The using of heart rate trendline could not only correct false and missed QRS location, but also easily detect ectopic heart beats. Conclusion The new combined approach can be used to localize the QRS complex accurately and promptly in the ECG signal with serious noise, and brings a prosperous application in the auto analysis of ECG.
出处
《航天医学与医学工程》
CAS
CSCD
北大核心
2009年第3期187-191,共5页
Space Medicine & Medical Engineering
基金
中国载人航天工程项目资助
关键词
心电图
QRS波群
小波分解
能量变换
electrocardiogram （ECG）
QRS complex
wavelet decomposition
energy transform
