基于小波变换和矢量量化的二维ECG数据压缩算法

A 2-D ECG Compression Algorithm Based on Wavelet Transform and Vector Quantization

本研究针对心电数据的压缩问题,提出了一种新的基于小波变换的二维心电(ECG)数据压缩算法。该算法首先将一维原始ECG信号转化为二维序列信号,从而使ECG数据的两种相关性可得到充分地利用;然后对二维ECG序列进行小波变换,并对变换后的系数应用了一种改进的矢量量化(VQ)方法。在改进的VQ方法中,根据小波变换后系数的特点,构造了一种新的树矢量(TV)。利用本算法与已有基于小波变换的压缩算法和其他二维ECG信号的压缩算法,对MIT/BIH数据库中的心律不齐数据进行了对比压缩实验。结果表明:本算法适用于各种波形特征的ECG信号,并且在保证压缩质量的前提下,可以获得较大的压缩比,具有一定的应用价值。

In this paper, we investigated the compression problem of electrocardiogram （ECG） signal and proposed a new two-dimensional （2-D） wavelet-based ECG data compression algorithm. A 1-D ECG data were first sliced and aligned to a 2-D data array. And then 2-D wavelet transform was applied to the constructed 2-D ECG data array. A modified vector quantization （VQ） was employed to the wavelet coefficients. This modified VQ algorithm constructed a new tree vector （TV） that well utilized the characteristics of the wavelet coefficients. Records selected from the MIT/BIH arrhythmia database were tested contrastively using the proposed algorithm. The results was compared with that obtained by other 2-D ECG compression algorithms. The experimental results show that the proposed method is suitable for various morphologies of ECG data, and achieves higher compression ratio with the characteristic features well preserved. The proposed algorithm is promising for practical use.