Haberl R, Schels H F, Steinbigler P, Jilge G, Steinbeck G
Medical Hospital I, University of Munich, FRG.
Circulation. 1990 Oct;82(4):1183-92. doi: 10.1161/01.cir.82.4.1183.
Frequency analysis of the electrocardiogram with Fourier transform is a sensitive method of detecting late potentials. However, information about localization of late potentials is lost, frequency resolution is poor, and window functions have to be applied. We therefore analyzed multiple segments (25 msec long) of the surface electrocardiogram ("spectrotemporal mapping") with adaptive frequency determination (AFD), an autoregressive algorithm that is characterized by high-frequency resolution in very short segments without the use of window functions. Results were compared with those from Fourier transform and the Simson method. We studied 38 patients after myocardial infarction (MI) with sustained ventricular tachycardia (VT), 21 patients after MI without VT, and 18 healthy subjects. Frequency peaks could be clearly differentiated until a minimal interval of 6 Hz; with fast Fourier transform (Blackman Harris window) in a much longer segment (80 msec), the spectral peaks merged into one another at an interval of about 30 Hz. AFD revealed high-frequency components as narrow peaks in the range of 40-160 Hz in 28 of 38 patients (74%) after MI with VT. Because of the short segment size, exact localization of late potentials was possible; in most of the patients, the peaks occurred in segments inside the QRS complex and ended 20 +/- 10 msec after termination of the QRS complex. In patients after MI without VT, only four of 21 patients (19%) had spectral peaks in segments after the end of the QRS complex; however, 13 of 21 patients demonstrated microvolt potentials in segments within the QRS complex. These potentials did not extend beyond the end of normal ventricular activation. Only two of 18 healthy subjects showed abnormal AFD results. Patients with bundle branch block did not need to be excluded. AFD allowed good differentiation between late potentials and noise by a characteristic pattern of the spectral peaks. For the Simson method, patients with bundle branch block had to be excluded, and overall sensitivity was 42%. In five cases, the cause of failure of the Simson method could be identified as incorrect determination of the QRS limits due to noise. Thus, AFD is a promising method for detailed analysis of late potentials; it combines the advantages of frequency analysis (good differentiation between signal and noise and high-pass filters not necessary) and time domain analysis (localization of late potentials).
采用傅里叶变换对心电图进行频率分析是检测晚电位的一种敏感方法。然而,晚电位定位信息丢失,频率分辨率差,且必须应用窗函数。因此,我们采用自适应频率测定(AFD)对体表心电图的多个节段(25毫秒长)进行分析(“频谱时间映射”),AFD是一种自回归算法,其特点是在非常短的节段内具有高频率分辨率,且无需使用窗函数。将结果与傅里叶变换和辛普森方法的结果进行比较。我们研究了38例心肌梗死(MI)后发生持续性室性心动过速(VT)的患者、21例MI后无VT的患者和18名健康受试者。直到最小间隔为6Hz时,频率峰值仍能清晰区分;在更长的节段(80毫秒)中采用快速傅里叶变换(布莱克曼-哈里斯窗)时,频谱峰值在约30Hz的间隔处相互融合。AFD显示,38例MI后发生VT的患者中有28例(74%)在40-160Hz范围内出现高频成分,表现为窄峰。由于节段尺寸短,晚电位的精确定位成为可能;在大多数患者中,峰值出现在QRS复合波内部的节段,并在QRS复合波终止后20±10毫秒结束。在MI后无VT的患者中,21例患者中只有4例(19%)在QRS复合波结束后的节段出现频谱峰值;然而,21例患者中有13例在QRS复合波内部的节段显示出微伏电位。这些电位未超过正常心室激活结束时间。18名健康受试者中只有2例显示AFD结果异常。束支传导阻滞患者无需排除。AFD通过频谱峰值的特征模式能够很好地区分晚电位和噪声。对于辛普森方法,必须排除束支传导阻滞患者,总体敏感性为42%。在5例病例中,辛普森方法失败的原因可确定为由于噪声导致QRS界限测定错误。因此,AFD是一种用于详细分析晚电位的有前景的方法;它结合了频率分析(信号与噪声区分良好且无需高通滤波器)和时域分析(晚电位定位)的优点。