Comparison of countershock prediction features based on autoregressive and fourier transformed spectral analysis
Comparison of countershock prediction features based on autoregressive and fourier transformed spectral analysis
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基于自回归和傅里叶变换谱分析的反震预测特征比较
DOI：
10.1109/cic.2008.4749084
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
H. Strohmenger
中科院分区：
文献类型：
--
作者：
C. Nowak;G. Fischer;A. Neurauter;L. Wieser;B. Tilg;H. Strohmenger
心室颤动（VF）心电图的频谱分析已被用于预测反击成功，其中快速傅立叶变换（FFT）是标准的频谱估计器。自回归（AR）谱估计需要用较少的计算时间来计算谱。本研究比较了基于FFT和AR方法的特征预测能力和计算性能。在VF动物模型中，对25头猪进行了41次电击。本研究开发了两个新的基于AR的预测特征。为了验证概念，实现了一个微控制器程序。计算受试者工作特征（ROC）曲线下的面积（AUC），使用AR建模的特征结果（85%;89%）优于基于FFT的常见参数（72%;78%）。在计算时间的比较中，基于AR的参数比基于FFT的参数产生更好的结果（快近2.5倍）。综上所述，由于计算速度和更好的预测结果，与FFT相比，AR谱估计器是一个有吸引力的选择。
Spectral analysis of ventricular fibrillation (VF) ECG has been used for predicting countershock success, where the Fast Fourier Transformation (FFT) is the standard spectral estimator. Autoregressive (AR) spectral estimation should compute the spectrum with less computation time. This study compares the predictive power and computational performance of features based on FFT and AR methods. In an animal model of VF, 41 shocks were delivered in 25 swine. Two new AR based prediction features were developed in this study. For a proof of concept a microcontroller program was implemented. Calculating the area under the receiver operating characteristic (ROC) curve (AUC), the results of the features using AR modeling (85 %; 89 %) are better than common parameters based on FFT (72 %; 78 %). In the calculation time comparison the AR based parameters yield better results (nearly 2.5 times faster) than FFT based parameters. Summing up, AR spectral estimators are an attractive option compared to FFT due to the computational speed and the better prediction outcome.