【摘要】 目前对心电数据压缩的研究主要集中在对低采样率心电数据的压缩,我们提出了一种基于BW(Bur-rows-Wheeler)算法对高采样率心电数据的无损压缩算法。首先对原始心电数据进行差分变换,将部分16位二进制差值表示为8位,然后对差分结果进行前移编码,使得相同字符集中于某一段区域,最后通过算术编码得到高压缩比。结果表明,该算法不仅适用于高采样率体表心电数据的压缩,而且也适用于心内心电数据的压缩,平均压缩比分别达到3.547和3.608。同现有的心电无损压缩算法相比,它在压缩效果上获得了较大改进。另外针对高采样率心电数据,使用该算法进行无损压缩也可以得到较好的压缩效果。更多还原

【Abstract】 Now researches of ECG data compression mainly focus on compressing the ECG data of low sampling rate. A BW-based high sampling rate ECG data lossless compression algorithm is proposed in this paper. We apply difference operation to the original ECG data first and take part of the 16-bit binary differential value as 8-bit binary. Then the differential results are coded with the move-to-front coding method in order to make the same characters centralizing in a certain area. Last, we gain a high compression ratio by using the arithmetic coding method further. Our experimental results indicate that this is an efficient lossless compression method suitable for body surface ECG data as well as for heart ECG data. The average compression ratios come up to 3.547 and 3.608, respectively. By comparison with current ECG compression algorithms, our algorithm has gained much improvement in terms of the compression ratio, especially when applied to the high sampling rate ECG data.更多还原