Alesanco Alvaro, García José
Communications Technologies Group, Aragón Institute of Engineering Research, University of Zaragoza, Zaragoza 50018, Spain.
IEEE Trans Biomed Eng. 2008 Nov;55(11):2519-27. doi: 10.1109/TBME.2008.2001263.
This paper introduces a new methodology for compressing ECG signals in an automatic way guaranteeing signal interpretation quality. The approach is based on noise estimation in the ECG signal that is used as a compression threshold in the coding stage. The Set Partitioning in Hierarchical Trees algorithm is used to code the signal in the wavelet domain. Forty different ECG records from two different ECG databases commonly used in ECG compression have been considered to validate the approach. Three cardiologists have participated in the clinical trial using mean opinion score tests in order to rate the signals quality. Results showed that the approach not only achieves very good ECG reconstruction quality but also enhances the visual quality of the ECG signal.
本文介绍了一种以自动方式压缩心电图（ECG）信号的新方法，该方法能保证信号的解读质量。该方法基于对ECG信号中的噪声估计，此估计值在编码阶段用作压缩阈值。分层树中的集合划分（Set Partitioning in Hierarchical Trees）算法用于在小波域对信号进行编码。为验证该方法，考虑了来自ECG压缩中常用的两个不同ECG数据库的40条不同ECG记录。三位心脏病专家参与了临床试验，使用平均意见得分测试来对信号质量进行评级。结果表明，该方法不仅能实现非常好的ECG重建质量，还能提高ECG信号的视觉质量。
