一种从数字化 ECG 中确定时间平面特征的统计方法。
A statistical approach for determination of time plane features from digitized ECG.
机构信息
Department of Electronics and Communication Engineering, Camellia Institute of Technology, Kolkata 700129, Calcutta, India.
出版信息
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%。
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