提出一种基于希尔伯特变换和自适应双阈值的R波检测算法。首先对预处理后的信号进行幅度归一化和希尔伯特包络分析;然后采用自适应双阈值法检测R波;最后,根据增强后的信号定位检测到R波的位置。使用4个具有不同频率和信噪比的数据库(MIT...提出一种基于希尔伯特变换和自适应双阈值的R波检测算法。首先对预处理后的信号进行幅度归一化和希尔伯特包络分析;然后采用自适应双阈值法检测R波;最后,根据增强后的信号定位检测到R波的位置。使用4个具有不同频率和信噪比的数据库(MIT-BIH心率失常数据库、QT数据库、NST噪声数据库、European ST-T数据库)和临床采集心电数据对所提算法进行性能评估,结果表明,各种不规律和含有严重噪声干扰的心电信号中R波的位置依然能被所提算法准确检测出。在MIT-BIH心律失常数据库中,总体数据检测的敏感性、阳性检测度和准确率分别达到了99.36%、99.77%和99.13%,每条记录平均消耗时间比传统的Pan and Tompkins算法大大缩短。实验结果表明该算法具有良好的鲁棒性和实时性。展开更多
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
Electrocardiogram（ECG） can be used as a valid way for diagnosing heart disease.To fulfill ECG processing in wearable devices by reducing computation complexity and hardware cost,two kinds of adaptive filters are des...Electrocardiogram（ECG） can be used as a valid way for diagnosing heart disease.To fulfill ECG processing in wearable devices by reducing computation complexity and hardware cost,two kinds of adaptive filters are designed to perform QRS complex detection and motion artifacts removal,respectively.The proposed design achieves a sensitivity of 99.49% and a positive predictivity of 99.72%,tested under the MIT-BIH ECG database.The proposed design is synthesized under the SMIC 65-nm CMOS technology and verified by post-synthesis simulation.Experimental results show that the power consumption and area cost of this design are of 160 μW and 1.09×10^5 μm^2,respectively.展开更多
文摘提出一种基于希尔伯特变换和自适应双阈值的R波检测算法。首先对预处理后的信号进行幅度归一化和希尔伯特包络分析;然后采用自适应双阈值法检测R波;最后,根据增强后的信号定位检测到R波的位置。使用4个具有不同频率和信噪比的数据库(MIT-BIH心率失常数据库、QT数据库、NST噪声数据库、European ST-T数据库)和临床采集心电数据对所提算法进行性能评估,结果表明,各种不规律和含有严重噪声干扰的心电信号中R波的位置依然能被所提算法准确检测出。在MIT-BIH心律失常数据库中,总体数据检测的敏感性、阳性检测度和准确率分别达到了99.36%、99.77%和99.13%,每条记录平均消耗时间比传统的Pan and Tompkins算法大大缩短。实验结果表明该算法具有良好的鲁棒性和实时性。
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.61574040,61234002,61525401)
文摘Electrocardiogram（ECG） can be used as a valid way for diagnosing heart disease.To fulfill ECG processing in wearable devices by reducing computation complexity and hardware cost,two kinds of adaptive filters are designed to perform QRS complex detection and motion artifacts removal,respectively.The proposed design achieves a sensitivity of 99.49% and a positive predictivity of 99.72%,tested under the MIT-BIH ECG database.The proposed design is synthesized under the SMIC 65-nm CMOS technology and verified by post-synthesis simulation.Experimental results show that the power consumption and area cost of this design are of 160 μW and 1.09×10^5 μm^2,respectively.
