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Analysis of the High-Frequency Content in Human QRS Complexes by the Continuous Wavelet Transform: An Automatized Analysis for the Prediction of Sudden Cardiac Death

机译:连续小波变换分析人QRS络合物中的高频含量:心脏猝死预测的自动化分析

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摘要

Background: Fragmentation and delayed potentials in the QRS signal of patients have been postulated as risk markers for Sudden Cardiac Death (SCD). The analysis of the high-frequency spectral content may be useful for quantification. Methods: Forty-two consecutive patients with prior history of SCD or malignant arrhythmias (patients) where compared with 120 healthy individuals (controls). The QRS complexes were extracted with a modified Pan-Tompkins algorithm and processed with the Continuous Wavelet Transform to analyze the high-frequency content (85–130 Hz). Results: Overall, the power of the high-frequency content was higher in patients compared with controls (170.9 vs. 47.3 103nV2Hz−1; p = 0.007), with a prolonged time to reach the maximal power (68.9 vs. 64.8 ms; p = 0.002). An analysis of the signal intensity (instantaneous average of cumulative power), revealed a distinct function between patients and controls. The total intensity was higher in patients compared with controls (137.1 vs. 39 103nV2Hz−1s−1; p = 0.001) and the time to reach the maximal intensity was also prolonged (88.7 vs. 82.1 ms; p < 0.001). Discussion: The high-frequency content of the QRS complexes was distinct between patients at risk of SCD and healthy controls. The wavelet transform is an efficient tool for spectral analysis of the QRS complexes that may contribute to stratification of risk.
机译:背景:已假定患者QRS信号中的碎裂和延迟电位是心脏猝死(SCD)的危险标志。高频频谱含量的分析对于量化可能有用。方法:与120名健康个体(对照组)相比,有42名连续的SCD病史或恶性心律失常的患者(患者)。用改进的Pan-Tompkins算法提取QRS络合物,并用连续小波变换处理以分析高频含量(85–130 Hz)。结果:总体而言,患者的高频成分功率比对照组高(170.9 vs. 47.3 10 3 nV 2 Hzs −1 ; p = 0.007),达到最大功率的时间延长(68.9 vs. 64.8 ms; p = 0.002)。信号强度(累积功率的瞬时平均值)的分析显示,患者和对照之间有明显的功能。患者的总强度高于对照组(137.1 vs. 39 10 3 nV 2 Hz -1 s -1 < / sup>; p = 0.001),达到最大强度的时间也延长了(88.7 vs. 82.1 ms; p <0.001)。讨论:在有SCD风险的患者和健康对照组之间,QRS络合物的高频含量是明显的。小波变换是一种有效的工具,可对QRS络合物进行光谱分析,这可能有助于风险分层。

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