Department of Physics, University of Kuopio, Kuopio, Finland.
IEEE Trans Biomed Eng. 2010 May;57(5):1062-9. doi: 10.1109/TBME.2009.2037492. Epub 2010 Feb 5.
The time interval between Q-wave onset and T-wave offset, i.e., QT interval, in an ECG corresponds to the total ventricular activity, including both depolarization and repolarization times. It has been suggested that abnormal QT variability could be a marker of cardiac diseases such as ventricular arrhythmias, and QT-interval has also been observed to lengthen during hypoglycemia. In this paper, we propose a robust method for estimating ventricular repolarization characteristics such as QT interval and T-wave amplitude. The method is based on principal component regression. In the method, QT epochs are first extracted from ECG in respect of R-waves. Then, correlation matrix of the extracted epochs is formed and its eigenvectors computed. The most significant eigenvectors are then fitted to the data to obtain noise-free estimates of QT epochs. Nonstationarities in QT-epoch characteristics can also be modeled by updating the eigenvectors dynamically. The main benefit of the proposed method is robustness to noise, i.e., it works also when using ECGs that have low SNR, for example, signals measured during normal-life environments. One application of the proposed method could be the detection of the hypoglycemia.
心电图中 Q 波起始与 T 波结束之间的时间间隔，即 QT 间期，对应于心室活动的总时间，包括去极化和复极化时间。已经有人提出，异常的 QT 变异性可能是心脏疾病的一个标志，如室性心律失常，并且在低血糖期间也观察到 QT 间期延长。在本文中，我们提出了一种稳健的方法来估计心室复极特征，如 QT 间期和 T 波幅度。该方法基于主成分回归。在该方法中，首先从 ECG 中根据 R 波提取 QT 时段。然后，形成提取时段的相关矩阵，并计算其特征向量。然后，将最重要的特征向量拟合到数据中，以获得 QT 时段的无噪声估计。QT 时段特征的非平稳性也可以通过动态更新特征向量来建模。所提出方法的主要优点是对噪声具有鲁棒性，即在使用 SNR 较低的 ECG 时，例如在正常生活环境中测量的信号，也可以工作。该方法的一个应用可能是检测低血糖。
