分段心房电图的高分辨率光谱分析的计算方法。
Computational method for high resolution spectral analysis of fractionated atrial electrograms.
机构信息
Department of Medicine-Division of Cardiology Columbia University Medical Center, 630 West 168th Street, New York, NY, USA.
出版信息
Comput Biol Med. 2013 Oct;43(10):1573-82. doi: 10.1016/j.compbiomed.2013.07.033. Epub 2013 Aug 12.
BACKGROUND
The discrete Fourier transform (DFT) is often used as a spectral estimator for analysis of complex fractionated atrial electrograms (CFAE) acquired during atrial fibrillation (AF). However, time resolution can be unsatisfactory, as the frequency resolution is proportional to rate/time interval. In this study we compared the DFT to a new spectral estimator with improved time-frequency resolution.
METHOD
Recently, a novel spectral estimator (NSE) based upon signal averaging was derived and implemented computationally. The NSE is similar to the DFT in that both estimators model the autocorrelation function to form the power spectrum. However, as derived in this study, NSE frequency resolution is proportional to rate/period(2) and thus unlike the DFT, is not directly dependent on the window length. We hypothesized that the NSE would provide improved time resolution while maintaining satisfactory frequency resolution for computation of CFAE spectral parameters. Window lengths of 8s, 4s, 2s, 1s, and 0.5s were used for analysis. Two criteria gauged estimator performance. Firstly, a periodic electrogram pattern with phase jitter was embedded in interference. The error in detecting the frequency of the periodic pattern was determined. Secondly, significant differences in spectral parameters for paroxysmal versus persistent AF data, which have known dissimilarities, were determined using the DFT versus NSE methods. The parameters measured were the dominant amplitude, dominant frequency, and mean spectral profile.
RESULTS
At all time resolutions, the error in detecting the frequency of the repeating electrogram pattern was less for NSE than for DFT (p<0.001). The DFT was accurate to 2s time resolution/0.5 Hz frequency resolution, while the NSE was accurate to 0.5s time resolution/0.05 Hz frequency resolution. At all time resolutions, significant differences in the dominant amplitude spectral parameter for paroxysmal versus persistent CFAE were greater using NSE than DFT (p<0.0001). For three of five time resolutions, the NSE had greater significant differences than DFT for discriminating the dominant frequency and mean spectral profile parameters between AF types.
CONCLUSIONS
The results suggest that the NSE has improved performance versus DFT for measurement of CFAE spectral properties.
背景
离散傅里叶变换（DFT）常用于分析心房颤动（AF）期间获取的复杂碎裂心房电图（CFAE）的频谱估计。然而，时间分辨率可能不理想，因为频率分辨率与率/时间间隔成正比。在这项研究中，我们比较了 DFT 与具有改进的时频分辨率的新频谱估计器。
方法
最近，基于信号平均的新型频谱估计器（NSE）已被推导出来并在计算上实现。NSE 与 DFT 相似，因为两种估计器都通过建模自相关函数来形成功率谱。然而，如本研究中推导的那样，NSE 的频率分辨率与率/周期（2）成正比，因此与 DFT 不同，它不直接依赖于窗口长度。我们假设 NSE 将提供改进的时间分辨率，同时保持用于计算 CFAE 频谱参数的令人满意的频率分辨率。使用 8s、4s、2s、1s 和 0.5s 的窗口长度进行分析。两个标准衡量估计器的性能。首先，在干扰中嵌入具有相位抖动的周期性电图模式。确定检测周期性模式频率的误差。其次，使用 DFT 和 NSE 方法确定具有已知差异的阵发性与持续性 AF 数据的频谱参数之间的显著差异。测量的参数是主导幅度、主导频率和平均频谱分布。
结果
在所有时间分辨率下，检测重复电图模式频率的误差均小于 NSE 时的误差（p<0.001）。DFT 的时间分辨率为 2s/0.5Hz 频率分辨率，而 NSE 的时间分辨率为 0.5s/0.05Hz 频率分辨率。在所有时间分辨率下，使用 NSE 比 DFT 时，阵发性与持续性 CFAE 之间的主导幅度频谱参数的差异更大（p<0.0001）。在五个时间分辨率中的三个中，NSE 比 DFT 更能区分 AF 类型之间的主导频率和平均频谱分布参数。
结论
结果表明，NSE 在测量 CFAE 频谱特性方面优于 DFT。
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