ECG data compression based on wave atom transform

Hongteng Xu, Guangtao Zhai
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引用次数: 7

Abstract

In this paper, a new ECG signal compression algorithm based on wave atom transform is presented. According to an assumption that ECG is oscillatory signal, we decompose ECG signal by wave atoms and trimmed insignificant coefficients. The wave atom decomposition has been proved to have a significantly sparser solution than other existing transform methods when it comes to oscillatory signal. In our experiment, the convergence of the energy of wave atoms' coefficients is faster than that of wavelet indeed. The most significant advantage of our algorithm is that unlike many conventional methods, the performance of our algorithm is not dependent on QRS detection, which simplifies the architecture of compression system and is beneficial to telemedicine application. After wave atom transform, the data stream is divided and coded by a hybrid entropy coding strategy combining delta coding, run-length-coding and arithmetic coding. The experimental results on MIT-BIH arrhythmia database proved that our algorithm has high compression ratio (CR > 10) with percentage root mean square difference (PRD) under 1%.
基于波原子变换的心电数据压缩
提出了一种新的基于波原子变换的心电信号压缩算法。根据心电是振荡信号的假设,对心电信号进行波原子分解,并对不显著系数进行裁剪。当涉及到振荡信号时,波原子分解已被证明比其他现有的变换方法具有明显的稀疏解。在我们的实验中,波原子系数能量的收敛速度确实比小波的收敛速度快。该算法最大的优点是与许多传统方法不同,该算法的性能不依赖于QRS检测,简化了压缩系统的架构,有利于远程医疗应用。经过波原子变换后的数据流,采用增量编码、行程编码和算术编码相结合的混合熵编码策略对数据流进行分割和编码。在MIT-BIH心律失常数据库上的实验结果证明,该算法具有较高的压缩比(CR bbb10),且百分比均方根差(PRD)小于1%。
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