Romero Iñaki, Grubb Neil R, Clegg Gareth R, Robertson Colin E, Addison Paul S, Watson James N
Department of Medical Physics, German National Institute of Metrology, Berlin D-10587, Germany.
IEEE Trans Biomed Eng. 2008 Nov;55(11):2658-65. doi: 10.1109/TBME.2008.923912.
Ventricular tachyarrhythmias are potentially lethal cardiac pathologies and the commonest cause of sudden cardiac death. Efforts to predict the onset of such events are based on feature extraction from the surface ECG. T-wave alternans (TWAs) are considered a marker of abnormal ventricular function that may be associated with ventricular tachycardia (VT) and ventricular fibrillation. A novel TWA detection algorithm utilizing the continuous wavelet transform is described in this paper. Simulated ECGs containing artificial TWA were used to test the algorithm that achieved a sensitivity of 91.40% and a specificity of 94.00%. The algorithm was subsequently used to analyze the ECGs of eight patients prior to the onset of VT. Of these, the algorithm indicated that five patients exhibited TWA prior to the onset of the tachyarrhythmic events, while the remaining three patients did not exhibit identifiable TWA. Healthy individuals were also studied in which one short TWA episode was detected by the algorithm. However, closer visual inspection of the data revealed this to be a likely false positive result.
室性快速性心律失常是潜在致命的心脏疾病，也是心源性猝死最常见的原因。预测此类事件发作的努力基于体表心电图的特征提取。T波交替（TWA）被认为是心室功能异常的标志物，可能与室性心动过速（VT）和心室颤动有关。本文描述了一种利用连续小波变换的新型TWA检测算法。使用包含人工TWA的模拟心电图来测试该算法，其灵敏度达到91.40%，特异性达到94.00%。该算法随后被用于分析8例患者在VT发作前的心电图。其中，该算法表明5例患者在快速性心律失常事件发作前出现了TWA，而其余3例患者未出现可识别的TWA。还对健康个体进行了研究，算法检测到其中一人出现了一次短暂的TWA发作。然而，对数据的仔细目视检查显示这可能是一个假阳性结果。
