从腹部心电图无阈值检测母体心率

M. Algunaidi, M. A. Mohd. Ali
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引用次数: 8

摘要

这项工作涉及腹部心电图(AECG)波形中QRS复合物的无阈值检测。QRS复合物的识别精度对于在线计算母体心率至关重要,并将导致在线检测胎儿心脏。在上个世纪,在这个领域进行了大量的工作,使用了各种方法,从滤波和阈值方法,到小波方法,再到神经网络等,每种方法都有不同的有效性和弱点。虽然它们的性能总体上不错,但是,主要的缺点是,它们依赖于阈值。在该算法中,基于正常最大和最小心率(HR)计算RR运动间隔。这样做的好处是确保每个r峰值都包含在移动间隔的边缘之间。因此,该算法的有效性在于,它与阈值无关,并且在每次检测到峰值后更新RR移动间隔以计算其边缘之间包含的下一个峰值。完整的算法使用MATLAB 7.4实现。使用20个记录数据验证了该方法。检测方法的平均灵敏度为99.05%,平均阳性预测率为99.8%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Threshold-free detection of maternal heart rate from abdominal electrocardiogram
This work is involved the threshold-free detection of QRS complexes in an abdominal electrocardiogram (AECG) waveform. The precision in the identification of QRS complexes is of great importance for on-line maternal heart rate calculation and, will lead to on line fetal heart detection,. During the last century much work has been carried out in this field, using various methods ranging from filtering and threshold methods, through wavelet methods, to neural networks, and others, each of which has different effectiveness and weaknesses. Although their performance is generally good, but, the main weakness is that, they are threshold dependent. In the proposed algorithm a RR moving interval is calculated, based on normal maximum and minimum heart rate (HR). This has the advantage of ensuring that every R-peak is contained between the edges of the moving interval. Thus the effectiveness of this algorithm is that, it is threshold independent, and after every peak detection the RR moving interval is updated to calculate the next peak contained between its edges. The complete algorithm is implemented using MATLAB 7.4. The method is validated using 20 recorded data. The average sensitivity and average positive predictivity of the detection method are 99.05% and 99.8% respectively.
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