基于小波变换的混合二维ECG数据压缩方法

提出了一种新的基于小波变换的混合二维心电(electrocardiogram,ECG)数据压缩方法。基于ECG数据的两种相关性,该方法首先将一维ECG信号转化为二维信号序列。然后对二维序列进行了小波变换,并利用改进的编码方法对变换后的系数进行了压缩编码:即先根据不同系数子带的各自特点和系数子带之间的相似性,改进了等级树集合分裂(setpartitioninghierarchicaltrees,SPIHT)算法和矢量量化(vectorquantization,VQ)算法;再利用改进后的SPIHT与VQ相混合的算法对小波变换后的系数进行了编码。利用所提算法与已有具有代表性的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:所提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。

Hybrid 2-D ECG compression method based on wavelet transform

In this paper,the authors proposed a new hybrid two-dimensional(2-D)wavelet-based electrocardiogram(ECG)data compression method.A 1-D ECG data was first segmented and aligned to a 2-D data array,which fully utilizing the two kinds of correlation of heartbeat signals.And then 2-D wavelet transform was applied to the constructed 2-D data array.A modified coding method was employed to the wavelet coefficients.First,modified the set partitioning hierarchical trees(SPIHT)method and the vector quantization(VQ)method,according to the individual characteristic of different coefficient subband and the similarity between the subbands.Second,a hybrid compression method of the modified SPIHT and VQ was employed to the wavelet coefficients.Records selected from the MIT/BIH arrhythmia database were tested.The experimental results showed that the proposed method was suitable for various morphologies of ECG data,and that it achieved high compression ratio with the characteristic features well preserved.