Nilsson Frida, Stridh Martin, Bollmann Andreas, Sörnmo Leif
Signal Processing Group, Department of Electrical Engineering, Lund University, Box 118, S-221 00 Lund, Sweden.
Med Eng Phys. 2006 Oct;28(8):802-8. doi: 10.1016/j.medengphy.2005.11.010. Epub 2006 Jan 25.
By recognizing and characterizing conditions under which atrial fibrillation (AF) is likely to terminate spontaneously or be sustained, improved treatment of sustained AF may result and unnecessary treatment of self-terminating AF avoided. Time-frequency measures that characterize AF, such as fibrillatory frequency, amplitude, and waveform shape (exponential decay), are extracted from the residual ECG following QRST cancellation. Three complexity measures are also studied, characterizing the degree of organization of atrial activity. All measures are analysed using a training set, consisting of 20 recordings of AF with known termination properties, and a test set of 30 recordings. Spontaneous termination was best predicted by a low and stable fibrillatory frequency and a low exponential decay. Using these predictors, 90% of the test set was correctly classified into terminating and sustained AF. Neither fibrillation amplitude nor the complexity measures differed significantly between the two sets.
通过识别和描述心房颤动（AF）可能自发终止或持续的条件，可能会改善持续性AF的治疗，并避免对自限性AF进行不必要的治疗。从QRST消除后的残余心电图中提取表征AF的时频测量值，如颤动频率、幅度和波形形状（指数衰减）。还研究了三种复杂性测量方法，以表征心房活动的组织程度。使用由20份具有已知终止特性的AF记录组成的训练集和30份记录的测试集对所有测量值进行分析。颤动频率低且稳定以及指数衰减低最能预测自发终止。使用这些预测指标，测试集中90%被正确分类为终止性和持续性AF。两组之间的颤动幅度和复杂性测量值均无显著差异。
