Chan Hsiao-Lung, Siao You-Chen, Chen Szi-Wen, Yu Shih-Fan
Department of Electrical Engineering, Chang Gung University, Kweishan, Taoyuan 333, Taiwan.
Comput Methods Programs Biomed. 2008 Apr;90(1):1-8. doi: 10.1016/j.cmpb.2007.11.006. Epub 2007 Dec 27.
Efficient electrocardiogram (ECG) compression can reduce the payload of real-time ECG transmission as well as reduce the amount of data storage in long-term ECG recording. In this paper an ECG compression/decompression architecture based on the bit-field preserving (BFP) and running length encoding (RLE)/decoding schemes incorporated with the discrete wavelet transform (DWT) is proposed. Compared to complex and repetitive manipulations in the set partitioning in hierarchical tree (SPIHT) coding and the vector quantization (VQ), the proposed algorithm has advantages of simple manipulations and a feedforward structure that would be suitable to implement on very-large-scale integrated circuits and general microcontrollers.
高效的心电图（ECG）压缩可以减少实时心电图传输的有效载荷，同时减少长期心电图记录中的数据存储量。本文提出了一种基于位场保留（BFP）和游程编码（RLE）/解码方案并结合离散小波变换（DWT）的心电图压缩/解压缩架构。与分层树集合分割（SPIHT）编码和矢量量化（VQ）中复杂且重复的操作相比，该算法具有操作简单和前馈结构的优点，适合在超大规模集成电路和通用微控制器上实现。
