On the estimation of T-wave alternans using the spectral fast fourier transform method.
On the estimation of T-wave alternans using the spectral fast fourier transform method.
复制标题
利用谱快速傅立叶变换方法估计T波交替。
DOI：
10.1016/j.hrthm.2011.10.013
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发表时间：
2012
期刊：
影响因子：
5.5
通讯作者：
Merchant,FaisalM
中科院分区：
文献类型：
--
作者：
Armoundas,AntonisA;Mela,Theofanie;Merchant,FaisalM
背景T波交替（TWA）与室性快速心律失常和心源性猝死的易感性增加有关。然而，随机（白）噪声和（病理）生理过程（即室性早搏、心率和呼吸频率）可能会妨碍 TWA 估计，从而降低其在风险分层中的临床实用性。 目的 使用快速傅立叶变换方法研究随机噪声和某些（病理）生理过程对 TWA 估计的影响，并开发克服这些潜在误差源的方法。 方法我们结合使用人体心电图数据和计算机模拟来评估 TWA 的估计。室性早搏以及随机和有色噪声对 TWA 估计准确性的影响。结果我们定量地证明，用奇数/偶数中位心搏替换“坏”心搏比用总体平均值或总体中位心搏替换更准确。我们还表明，相位重置可能对交替估计有显着影响，并且在 128 点快速傅立叶变换中使用 >0.4922 周期/节拍的频率来估计交替，为可能发生相位重置时估计交替提供了最准确的方法。此外，我们的数据表明，当交替电压超过新的更高阈值时，可以减少由于高噪声水平而导致的不确定 TWA 测试的数量。此外，随机噪声的幅度对交替估计有显着影响，并且应针对 >1.8 μV 的噪声水平调整交替电压阈值。最后，我们定量证明有色噪声可能导致假阳性或假阴性结果。我们提出了估计这些（病理）生理过程对交替估计的影响的方法，以确定 TWA 测试是否可能是真阳性或真阴性。结论本研究引入了新方法来克服 TWA 估计中潜在的误差源。这些方法可以提高 TWA 在动态监测或室性心律失常和心源性猝死的临床风险分层方面的实用性。
BACKGROUNDT-wave alternans (TWA) has been associated with increased vulnerability to ventricular tachyarrhythmias and sudden cardiac death. However, both random (white) noise and (patho)physiologic processes (ie, premature ventricular contractions and heart and respiration rates) may hamper TWA estimation and therefore lessen its clinical utility for risk stratification.OBJECTIVETo investigate the effect of random noise and certain (patho)physiologic processes on the estimation of TWA by using the fast Fourier transform method and to develop methods to overcome these potential sources of error.METHODSWe used a combination of human electrocardiogram data and computer simulations to assess the effects of a premature ventricular contraction and random and colored noise on the accuracy of TWA estimation.RESULTSWe quantitatively demonstrate that replacing a “bad” beat with an odd/even median beat is a more accurate approach than replacing it with the overall average or the overall median beat. We also show that phase resetting may have a significant effect on alternans estimation and that estimation of alternans by using frequencies >0.4922 cycles/beat in a 128-point fast Fourier transform provides the most accurate approach for estimating the alternans when phase resetting is likely to occur. In addition, our data demonstrate that the number of indeterminate TWA tests due to high levels of noise can be reduced when the alternans voltage exceeds a new higher threshold. Furthermore, the amplitude of random noise has a significant effect on alternans estimation and the alternans voltage threshold should be adjusted for noise levels >1.8 μV. Finally, we quantitatively demonstrate that colored noise may lead to a false-positive or a false-negative result. We propose methods to estimate the effect of these (patho)physiologic processes on the alternans estimation in order to determine whether a TWA test is likely to be a true positive or a true negative.CONCLUSIONThis study introduces novel methods to overcome potential sources of error in the estimation of TWA. These methods may improve the utility of TWA either for ambulatory monitoring or for clinical risk stratification for ventricular arrhythmias and sudden cardiac death.