通过分析心电图 (ECG)在相邻采样点和相邻心跳周期存在的冗余信息，提出了一种基于二维离散余弦变换 (DCT)的 ECG信号压缩方法，并提出了采用数据重排和分段编码技术来进一步提高压缩比.对 MIT- BIHarrhythmia database部分数据进行压缩，实验结果表明，该方法在均方根误差 (PRD)约 4.5 %时，压缩比可达到10∶ 1到 2 0∶ 1.运算量为 2.75次乘法 /采样点和 7.2 5次加法 /采样点.其比 L ee的 2 - D DCT算法提高近一倍，与Hilton和 L u的离散小波方法压缩效果基本相当，但计算量有较大幅度减少.该方法是目前 ECG信号压缩算法中计算量小、压缩比较高的一种方法.

In this paper, an ECG data compression method based on 2-D DCT transform has been proposed, which utilizes the fact that ECG signals have two types of redundancies—between adjacent samples and between adjacent heartbeats. Furthermore, the technology of the data realignment and the subsection encoding are proposed so as to speed up the coding rate. When the percent root-mean-square difference(PRD) is about 4.5, this method can get the coding rate of 10∶1 to 20∶1 and the computing complexity of 2.75 multiplicative operations and 7.25 additive operations per sample by the expemiment on MIT-BIHarrhythmia database data. This method can improve almost one time above the 2-D DCT method of H.Lee' s. And its coding rate is almost the same with the discrete wavelet method in M.Hilton and Z.Lu' s paper, but the calculator is much less.The compare indicates this method is a low-complexity and high-coding-rate method among the current ECG data compression methods.