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首页> 外文期刊>IEEE Transactions on Biomedical Engineering >Detection of the Third Heart Sound Based on Nonlinear Signal Decomposition and Time–Frequency Localization
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Detection of the Third Heart Sound Based on Nonlinear Signal Decomposition and Time–Frequency Localization

机译:基于非线性信号分解和时频定位的第三心音检测

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This study presents a precise way to detect the third ($S_{3}$ ) heart sound, which is recognized as an important indication of heart failure, based on nonlinear single decomposition and time–frequency localization. The detection of the $S_{3}$ is obscured due to its significantly low energy and frequency. Even more, the detected $S_{3}$ may be misunderstood as an abnormal second heart sound with a fixed split, which was not addressed in the literature. To detect such $S_{3}$, the Hilbert vibration decomposition method is applied to decompose the heart sound into a certain number of subcomponents while intactly preserving the phase information. Thus, the time information of all of the decomposed components are unchanged, which further expedites the identification and localization of any module/section of a signal properly. Next, the proposed localization step is applied to the decomposed subcomponents by using smoothed pseudo Wigner–Ville distribution followed by the reassignment method. Finally, based on the positional information, the $S_{3}$ is distinguished and confirmed by measuring time delays between the $S_{2}$ and $S_{3}$. In total, 82 sets of cardiac cycles collected from different databases including Texas Heart Institute database are examined for evaluation of the proposed method. The result analysis shows that the proposed method can detect the $S_{3}$ correctly, even when the - ormalized temporal energy of $S_{3}$ is larger than 0.16, and the frequency of those is larger than 34 Hz. In a performance analysis, the proposed method demonstrates that the accuracy rate of $S_{3}$ detection is as high as 93.9%, which is significantly higher compared with the other methods. Such findings prove the robustness of the proposed idea for detecting substantially low-energized $S_{3}$ .
机译:这项研究提出了一种精确的方法来检测第三种($ S_ {3} $)心音,这是基于非线性单一分解和时频定位的公认的心力衰竭的重要指标。由于$ S_ {3} $的能量和频率都非常低,因此检测不到。甚至,检测到的$ S_ {3} $可能会被误解为具有固定裂口的异常第二心音,这在文献中没有解决。为了检测这样的$ S_ {3} $,使用希尔伯特振动分解方法将心音分解为一定数量的子分量,同时完整地保留相位信息。因此,所有分解分量的时间信息不变,这进一步加快了信号的任何模块/部分的正确识别和定位。接下来,通过使用平滑的伪Wigner-Ville分布以及随后的重新分配方法,将建议的定位步骤应用于分解后的子组件。最后,基于位置信息,通过测量$ S_ {2} $和$ S_ {3} $之间的时间延迟来区分和确认$ S_ {3} $。总共检查了82个从不同数据库(包括德克萨斯心脏研究所数据库)收集的心动周期,以评估所提出的方法。结果分析表明,即使$ S_ {3} $的正规时间能量大于0.16,且其频率大于34 Hz,所提出的方法也可以正确检测$ S_ {3} $。在性能分析中,所提出的方法表明$ S_ {3} $检测的准确率高达93.9%,与其他方法相比明显更高。这些发现证明了所提出的思想对于检测实质上低能量的$ S_ {3} $的鲁棒性。

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