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New adaptive thresholding-based ECG R-peak detection technique

机译:基于新的自适应阈值的ECG R峰值检测技术

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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复合物(R-峰值)是本质的特征,因为它们提供了心脏病诊断的信息。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,并且计算昂贵。然而,在普遍存在的医疗保健(U-Healthcare)中,能源消耗是一个问题;因此,必须最小化检测时间。在本文中,我们提出了一种新的智能检测算法,可最大限度地减少检测时间,同时保持良好的检测性能。实验结果,在检测到30分钟的记录中检测R峰值,表明所提出的算法已经实现了99.63℃的SE(敏感性)和A + P(阳性预测性)为99.50 %优于来自的众所周知的算法文学。

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