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基于增强型分层树集分割算法的多通道心电图数据小波压缩

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

作者信息

Sharifahmadian Ershad

机构信息

Department of Biomedical Engineering, Shahed University, Tehran, Iran.

出版信息

Conf Proc IEEE Eng Med Biol Soc. 2006;2006:5238-43. doi: 10.1109/IEMBS.2006.259415.

Abstract

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

摘要

分层树中的集合划分(SPIHT)算法是一种用于图像和信号压缩的非常有效且计算简单的技术。在此,作者对该算法进行了改进,改进后的算法性能比SPIHT算法更好。增强型分层树中的集合划分(ESPIHT)算法的性能比SPIHT算法更快。此外,所提出的算法减少了存储或传输的比特流中的比特数。我将其应用于多通道心电图数据的压缩。同时,我提出了一种基于改进算法的具体程序,用于更高效地压缩多通道心电图数据。该方法应用于麻省理工学院 - 贝斯以色列女执事医疗中心(MIT - BIH)心律失常数据库中的选定记录。根据实验,所提出的方法在多通道心电图数据压缩方面取得了显著成果。此外,为了压缩长时间存储的一个信号,可以有效地利用所提出的多通道压缩方法。

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