中文摘要：

心电信号特征波的准确检测是心电信号自动分析和诊断的关键,其中QRS波群的R波识别更是计算心率,区分心率失常及心率变异性分析的前提和基础。本文在提升小波算法的基础上,对传统的差分阈值算法进行了改进,通过对R波第一检测点及时间窗宽度的精细优化,使得本文改进后的差分阈值算法具有更好的实时性及更强的R波识别率。使用MIT-BIH标准心律失常数据库的心电信号数据作为样本数据进行实验,实验表明本文改进后的差分阈值算法能够准确检测R波的特征值,R波识别率高且明显优于传统的差分阈值算法。

英文摘要：

The accurate detection of ECG signal is the key to analysis and diagnosis. The R wave identification in QRS wave group is the precondition and basis for the calculation of heart rate, distinction the arrhythmias and the heart rate variability. Based on the lifting wavelet algorithm, the traditional differential threshold algorithm has improved. By optimizing the first detection and the time window width of the R wave, the improved algorithm has better real-time performance and stronger R wave identification rate. According to the MIT-BIH standard arrhythmia database of ECG data as samples, experiments show that the improved differ- ential threshold algorithm can accurately detect the characteristic value of the R wave, and R wave identifi- cation rate is significantly better than the traditional difference threshold algorithm.