Department of Electronics and Communication Engineering, Camellia Institute of Technology, Kolkata 700129, Calcutta, India.
Comput Biol Med. 2011 May;41(5):278-84. doi: 10.1016/j.compbiomed.2011.03.003. Epub 2011 Apr 2.
This paper illustrates a method for time-plane feature extraction from digitized ECG sample using statistical approach. The algorithm detects the position and magnitude of the QRS complex, P and T wave for a single lead ECG dataset. The processing is broadly based on relative comparison of magnitude and slopes of ECG samples. Then the baseline modulation in the dataset is removed. The R-peak detection and baseline modulation is tested MIT-BIH arrhythmia database as well as 12-lead datasets in MIT-PTB database (PTBDB) and available under Physionet. The overall accuracy obtained is more than 99%.
本文介绍了一种使用统计方法从数字化 ECG 样本中提取时平面特征的方法。该算法用于检测单个导联 ECG 数据集的 QRS 复合波、P 波和 T 波的位置和幅度。该处理过程主要基于 ECG 样本幅度和斜率的相对比较。然后，去除数据集的基线调制。在 MIT-BIH 心律失常数据库以及 MIT-PTB 数据库（PTBDB）的 12 导联数据集上测试了 R 波峰检测和基线调制，这些数据集可在 Physionet 上获得。获得的总体准确率超过 99%。
