Taha B, Reddy S, Xue Q, Swiryn S
Algorithms and Sensor Technology, GE Marquette Medical Systems, Inc., Milwaukee 53223, USA.
J Electrocardiol. 2000;33 Suppl:123-5. doi: 10.1054/jelc.2000.20303.
Computerized time-domain analysis of the QRST-subtracted 12-lead electrocardiogram (ECG) has been used successfully to determine several atrial activity patterns. These time-domain methods are particularly useful for low-frequency signals such as those originating at the sinus node. However, high frequency atrial fibrillation (AFIB) and atrial flutter (AFL) waves can be better estimated by using spectral methods. In this study, we investigated the use of spectral entropy (SE) and spectral peak detection to distinguish fibrillatory from flutter activity in the QRST-subtracted ECG. In a set of 4,172 cardiologist-overread ECGs, a computerized ECG analysis program (12SL MAC-Rhythm, GE-Marquette Medical Systems, Milwaukee, WI) detected 270 AFIB rhythms and 100 AFL rhythms. Compared to the cardiologist's reading, the AFIB versus AFL miss-classification error was 5.6%. The Fourier Transform was used to estimate the power spectral density of the QRST-subtracted ECG data. Individual lead spectra were then averaged and SE was computed for each of the ECGs originally called AFIB or AFL by the computer program. Additional criteria that included SE, spectral peak frequencies, and time-domain measures of atrial activity were then applied to discriminate between the 2 rhythms. Employing these criteria resulted in a decrease of miss-classification error to 2.5%.
对减去QRST的12导联心电图（ECG）进行计算机时域分析已成功用于确定多种心房活动模式。这些时域方法对于低频信号（如起源于窦房结的信号）特别有用。然而，高频心房颤动（AFIB）和心房扑动（AFL）波通过频谱方法能得到更好的估计。在本研究中，我们研究了使用频谱熵（SE）和频谱峰值检测来区分减去QRST的ECG中的颤动活动和扑动活动。在一组4172份经心脏病专家复查的ECG中，一个计算机化的ECG分析程序（12SL MAC-Rhythm，通用电气-马奎特医疗系统公司，威斯康星州密尔沃基）检测到270例AFIB节律和100例AFL节律。与心脏病专家的诊断相比，AFIB与AFL的误分类误差为5.6%。使用傅里叶变换来估计减去QRST的ECG数据的功率谱密度。然后对各个导联的频谱进行平均，并为最初由计算机程序判定为AFIB或AFL的每份ECG计算SE。随后应用包括SE、频谱峰值频率和心房活动时域测量在内的其他标准来区分这两种节律。采用这些标准可将误分类误差降低至2.5%。
