基于多周期相关的ECG信号压缩编码方法

An ECG Signal Compression Encoding Scheme Based on Multi-Cycle-Related Statistical Model

提出了一种ECG信号压缩编码方案.该方案根据ECG信号类周期性的结构特征分割出信号周期,对一个周期进行提升小波变换,对生成的提升小波系数进行带截止区的均匀量化,再把量化系数分解成重要位置流、符号流、最高位位置流以及剩余比特流,然后对前3种数据流分别建立多周期相关的概率统计模型,进而实现自适应算术编码.实验数据结果表明:本方案在保证ECG信号压缩编码高效性的同时,比较好地实现了压缩编码的实时性.

In order to store and transmit electrocardiograms（ECG）,the realization of real-time ECG data compression has practical significance in the aspect of remote medical services.This paper presents an ECG signal compression encoding scheme.According to the periodic structural features of ECG,the signal cycle is split,and each cycle of the ECG signal is processed with lifting wavelet transformation.The resulting coefficients are done through a dead-zone of the uniform quantizer.Then the quantized coefficients are decomposed into important position quantization coefficient stream,symbol stream,PMSB and RB,and the first three data streams are related to models the probability of a multi-cycle statistical for the realization of adaptive arithmetic coding.Experimental results show that this scheme not only ensures the ECG signal compression coding efficiency,it also raises a very good compression in real time.