VENTRICULAR-FIBRILLATION DETECTION BY A REGRESSION TEST ON THE AUTOCORRELATION FUNCTION
VENTRICULAR-FIBRILLATION DETECTION BY A REGRESSION TEST ON THE AUTOCORRELATION FUNCTION
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DOI：
10.1007/bf02447420
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发表时间：
1987-05-01
影响因子：
3.2
通讯作者：
MOWER, MM
中科院分区：
文献类型：
--
作者：
CHEN, S;THAKOR, NV;MOWER, MM
本文研究了心室颤动（VF）和其他心律失常的信号特征的定量差异。分析过程包括两个步骤：计算短期自相关函数（ACF），然后对ACF的峰值幅度与滞后值的关系图（ACF/滞后图）进行回归测试。我们通过测试VF的ACF/滞后图未通过线性回归测试的假设来检测VF。分析31个独立事件（VF和其他室性心律失常），每个包括三个连续的1.5s的片段，每个片段产生以下结果：（1）在分析第一片段后，100%的灵敏度（Se），62%的特异性（Sp）和74%的测试效率（TE）;（2）第二段后为100%Se、86%Sp和90%TE;（3）第三段后为100%Se、100%Sp和100%TE。该方法量化了VF信号是具有随机幅度分布的非周期性的概念，而室性心动过速（VT）信号通常是具有更均匀幅度分布的周期性的。VF的准确辨别和识别在重症监护环境中以及在自动心律转复器和除颤器的设计中非常重要。
The paper investigates quantitative differences in the signal characteristics of ventricular fibrillation (VF) and other cardiac arrhythmias. The analysis procedure comprises two steps: calculation of a short-term autocorrelation function (ACF) followed by a regression test on a plot of peak magnitudes of the ACF against lag values (the ACF/lag plot). We detect VF by testing the hypothesis that the ACF/lag plot of VF does not pass a linear regression test. Analysis of 31 separate episodes (of VF and other ventricular arrhythmias), each comprising three successive segments of 1.5s each produced the following results: (1) 100 percent sensitivity (Se), 62 percent specificity (Sp) and 74 percent test efficiency (TE) after analysis of the first segment; (2) 100 percent Se, 86 percent Sp and 90 percent TE after the second segment; and (3) 100 percent Se, 100 percent Sp and 100 percent TE after the third segment. This method quantifies the notion that VF signals are nonperiodic with a random amplitude distribution, whereas ventricular tachycardia (VT) signals are usually periodic with more uniform amplitude distributions. Accurate discrimination and identification of VF can be very important in intensive-care settings, as well as in the design of automatic cardioverters and defibrillators.