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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 detect the characteristic points of QRS complex of ECG by using the joint algorithm of energy transformation and wavelet decomposition, and to provide a new method for the automatic analysis of ECG signals. Methods The energy transformation is based on the local features of the signal, which can effectively highlight the peak or valley of the signal. The wavelet decomposition decomposes the signal multi-resolution, which can highlight the characteristic information of the signal. The combination of the two methods is more conducive to the QRS complex The test. Results 30 samples were used to test the performance of the algorithm. It was proved that the joint algorithm can improve the signal-to-noise ratio and locate the feature points accurately and reliably. The MIT / BIH ECG database testing and verification, the R wave positioning accuracy of up to 99.79%. The use of heart rate trend analysis analysis results, not only can completely correct the false positive and missed, but also to locate abnormal heartbeat. Conclusion This algorithm can accurately and real-time identify the QRS complex of ECG seriously disturbed by noise, so it has a good application prospect in the automatic analysis of ECG signal.