QRS detection is very important in cardiovascular disease diagnosis and ECG (electrocardiogram) monitor, because it is the precondition of the calculation of correlative parameters and diagnosis. This paper presents a...QRS detection is very important in cardiovascular disease diagnosis and ECG (electrocardiogram) monitor, because it is the precondition of the calculation of correlative parameters and diagnosis. This paper presents a non-parametric derivative-based method for R wave detection in ECG signal. This method firstly uses a digital filter to cut out noises from ECG signals, utilizes local polynomial fitting that is a non-parametric derivative-based method to estimate the derivative values, and then selects appropriate thresholds by the difference, and the algorithm adaptively adjusts the size of thresholds periodically according to the different needs. Afterwards, the position of R wave is detected by the estimation of the first-order derivative values with nonparametric local polynomial statistical model. In addition, in order to improve the accuracy of detection, the method of redundant detection and missing detection are applied in this paper. The clinical experimental data are used to evaluate the effectiveness of the algorithm. Experimental results show that the method in the process of the detection of R wave is much smoother, compared with differential threshold algorithm and it can detect the R wave in the ECG signals accurately.展开更多
R-wave detection is the main approach for heart rate variability analysis and clinical application based on R-R interval. The maximum first derivative plus the maximum value of the double search algorithm is applied o...R-wave detection is the main approach for heart rate variability analysis and clinical application based on R-R interval. The maximum first derivative plus the maximum value of the double search algorithm is applied on electrocardiogram(ECG) of MIH-BIT Arrhythmia Database to extract R wave. Through the study of algorithm's characteristics and R-wave detection method, data segmentation method is modified to improve the detection accuracy. After segmentation modification, average accuracy rate of 6 sets of short ECG data increase from 82.51% to 93.70%, and the average accuracy rate of 11 groups long-range data is 96.61%. Test results prove that the algorithm and segmentation method can accurately locate R wave and have good effectiveness and versatility, but may exist some undetected problems due to algorithm implementation.展开更多
We collected 343 groups of abdominal electrocardiogram （ECG） data from 78 pregnant women and deleted the chan- nels unable for experts to determine R-wave peaks from them; then, based on these filtered data, the sta...We collected 343 groups of abdominal electrocardiogram （ECG） data from 78 pregnant women and deleted the chan- nels unable for experts to determine R-wave peaks from them; then, based on these filtered data, the statistics of position difference of corresponding R-wave peaks for different maternal ECG components from different points were studied. The resultant statistics showed the regularity that the position difference of corresponding maternal R-wave peaks between dif- ferent abdominal points does not exceed the range of 30 ms. The regularity was also proved using the fECG data from MIT-BIH PhysioBank. Additionally, the paper applied the obtained regularity, the range of position differences of the corresponding maternal R-wave peaks, to accomplish the automatic detection of maternal R-wave peaks in the recorded all initial 343 groups of abdominal signals, including the ones with the largest fetal ECG components, and all 55 groups of ECG data from MIT-BIH PhysioBank, achieving the successful separation of the maternal ECGs.展开更多
介绍了一种将小波变换应用于ECG信号检测R波的算法。该算法主要是在离散小波变换和多分辨率分析原理的基础上,利用db1小波特有的时频域特性,运用M a llat快速算法对心电信号进行了3层小波分解,分别在2、3层小波分解的高频系数中选择一...介绍了一种将小波变换应用于ECG信号检测R波的算法。该算法主要是在离散小波变换和多分辨率分析原理的基础上,利用db1小波特有的时频域特性,运用M a llat快速算法对心电信号进行了3层小波分解,分别在2、3层小波分解的高频系数中选择一定的阈值作为R波的判定条件,实现R波检测。通过对M IT/B IH(M assachusetts Institu te of T echno logy/Boston's B eth Israe lHosp ita l)心电数据库的R波检测,结果表明,该检测算法即使在噪声干扰和病态的情况下,也很容易实现对R波的准确检测和精确定位,具有相当高的定位精度,R波正确检测率高达到99.8%。展开更多
文摘QRS detection is very important in cardiovascular disease diagnosis and ECG (electrocardiogram) monitor, because it is the precondition of the calculation of correlative parameters and diagnosis. This paper presents a non-parametric derivative-based method for R wave detection in ECG signal. This method firstly uses a digital filter to cut out noises from ECG signals, utilizes local polynomial fitting that is a non-parametric derivative-based method to estimate the derivative values, and then selects appropriate thresholds by the difference, and the algorithm adaptively adjusts the size of thresholds periodically according to the different needs. Afterwards, the position of R wave is detected by the estimation of the first-order derivative values with nonparametric local polynomial statistical model. In addition, in order to improve the accuracy of detection, the method of redundant detection and missing detection are applied in this paper. The clinical experimental data are used to evaluate the effectiveness of the algorithm. Experimental results show that the method in the process of the detection of R wave is much smoother, compared with differential threshold algorithm and it can detect the R wave in the ECG signals accurately.
基金supported by the National Natural Science Foundation of China(Nos.61271082,61201029,81201161)
文摘R-wave detection is the main approach for heart rate variability analysis and clinical application based on R-R interval. The maximum first derivative plus the maximum value of the double search algorithm is applied on electrocardiogram(ECG) of MIH-BIT Arrhythmia Database to extract R wave. Through the study of algorithm's characteristics and R-wave detection method, data segmentation method is modified to improve the detection accuracy. After segmentation modification, average accuracy rate of 6 sets of short ECG data increase from 82.51% to 93.70%, and the average accuracy rate of 11 groups long-range data is 96.61%. Test results prove that the algorithm and segmentation method can accurately locate R wave and have good effectiveness and versatility, but may exist some undetected problems due to algorithm implementation.
基金Project supported by the National Natural Science Foundation of China （Grant No. 61271079） and the Jiangsu Supporting Plan Project, China （Grant No. BE2010720）.
文摘We collected 343 groups of abdominal electrocardiogram （ECG） data from 78 pregnant women and deleted the chan- nels unable for experts to determine R-wave peaks from them; then, based on these filtered data, the statistics of position difference of corresponding R-wave peaks for different maternal ECG components from different points were studied. The resultant statistics showed the regularity that the position difference of corresponding maternal R-wave peaks between dif- ferent abdominal points does not exceed the range of 30 ms. The regularity was also proved using the fECG data from MIT-BIH PhysioBank. Additionally, the paper applied the obtained regularity, the range of position differences of the corresponding maternal R-wave peaks, to accomplish the automatic detection of maternal R-wave peaks in the recorded all initial 343 groups of abdominal signals, including the ones with the largest fetal ECG components, and all 55 groups of ECG data from MIT-BIH PhysioBank, achieving the successful separation of the maternal ECGs.
文摘介绍了一种将小波变换应用于ECG信号检测R波的算法。该算法主要是在离散小波变换和多分辨率分析原理的基础上,利用db1小波特有的时频域特性,运用M a llat快速算法对心电信号进行了3层小波分解,分别在2、3层小波分解的高频系数中选择一定的阈值作为R波的判定条件,实现R波检测。通过对M IT/B IH(M assachusetts Institu te of T echno logy/Boston's B eth Israe lHosp ita l)心电数据库的R波检测,结果表明,该检测算法即使在噪声干扰和病态的情况下,也很容易实现对R波的准确检测和精确定位,具有相当高的定位精度,R波正确检测率高达到99.8%。
