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To Determinate PEP and LVET Through Analyzing LPC of Heart Sounds

机译:通过分析心脏声音的LPC来确定PEP和LVET

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To determine the pre-ejection period (PEP) and the left ventricular ejection time (LVET) thorough heart sounds and ECG are major tasks in this paper. The first step was to determine the event time of PEP, which detected the feature point of the first heart sound (SI) of PCG about 0.02-0.07 s after the It-peak of the ECG, and then obtained the prominent peaks of PCG during changes of signal slope with drastic change of peak value. The second step was taking R-peak to define a period of sound signal, making LPC and FFT, and moving certain few points to make another section, which was repeated to find out changes from the coefficient and frequency. Taking the sections with changes occurred, and FFT results as references got the time of PEP and LVET. Comparing the proposed results to the annotations, the average error of PEP detection is approximately 36.4 ms, and that of LVET is approximately 6.95 ms. With the error of the PEP, 83.4% and 33.9% accuracy are achieved within the time of 40 ms and 20 ms. With the error of the LVET, 94.2% and 25.8% accuracy are achieved at the time of 80 ms and 60 ms. The advantage of this method is that although the signals are very small, finding out the peak value of PCG, and analyzing the PEP and LVET are not hard tasks. Another advantage is that if the noise of the signal is not big enough to affect the original characteristic, the ECG signal could be applied to find out the peak value perfectly, and could be cut into piece by piece. The "NaN" point is hard to be defined in the testing data. Some issues are required to be improved or verified by other methods.
机译:为了确定预喷射时期(PEP)和左心室喷射时间(火球)彻底的心声,心电图是本文的主要任务。第一步是确定PEP的事件时间,它在心电图的IT峰值之后检测到PCG的第一心声(SI)的特征点,然后获得PCG的显着峰值峰值激烈变化信号斜率的变化。第二步采用R峰值来定义声音信号的时期,使LPC和FFT制作,并移动某些点以制造另一个部分,这被重复地找到从系数和频率的变化。将这些部分发生在发生的变化中,并且FFT结果随着参考的结果得到了PEP和LVET的时间。将所提出的结果与注释进行比较,PEP检测的平均误差约为36.4ms,即达到6.95毫秒。通过PEP的错误,在40 ms和20毫秒的时间内实现了83.4%和33.9%的精度。随着误差的误差,在80毫秒和60毫秒的时间内实现了94.2%和25.8%的精度。这种方法的优点是,尽管信号非常小,但找出PCG的峰值,并分析PEP和LVET不是硬任务。另一个优点是,如果信号的噪声不足以影响原始特性,则可以施加ECG信号以完美地找出峰值,并且可以通过件切成块。在测试数据中难以定义“NaN”点。需要通过其他方法改进或验证一些问题。

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