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New adaptive thresholding-based ECG R-peak detection technique

机译:基于自适应阈值的新型心电图R峰检测技术

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The QRS complexes (R-peaks) in the electrocardiogram (ECG) signals are essential features as they provide information for the diagnosis of heart diseases. Because detection accuracy is a major concern in clinical practices, most of the detection methods are complex and computationally expensive. However, in ubiquitous healthcare (u-healthcare), the energy consumption is a question; thus, detection time has to be minimized. In this paper, we propose a new intelligent detection algorithm, which minimizes detection time while maintaining a good level of detection performance. Experimental results, in detecting the R-peaks in 30 minutes long records, showed that the proposed algorithm has achieved an Se (sensitivity) of 99.63% and a +P (positive predictivity) of 99.50% outperforming the well-known algorithms from literature.
机译:心电图(ECG)信号中的QRS络合物(R-peaks)是必不可少的功能,因为它们为心脏病的诊断提供了信息。由于检测准确性是临床实践中的主要问题,因此大多数检测方法都很复杂且计算量很大。但是,在无处不在的医疗保健(u-healthcare)中,能耗是一个问题。因此,检测时间必须最小化。在本文中,我们提出了一种新的智能检测算法,该算法可在保持良好检测性能水平的同时最大程度地缩短检测时间。在30分钟长的记录中检测R峰的实验结果表明,该算法的Se(灵敏度)为99.63%,+ P(正预测性)为99.50%,优于文献中的著名算法。

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