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一种电子健康设备的实时心电图数据压缩和传输算法。

A real-time ECG data compression and transmission algorithm for an e-health device.

机构信息

Department of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Korea.

出版信息

IEEE Trans Biomed Eng. 2011 Sep;58(9):2448-55. doi: 10.1109/TBME.2011.2156794. Epub 2011 May 19.

DOI:10.1109/TBME.2011.2156794
PMID:21606020
Abstract

This paper introduces a real-time data compression and transmission algorithm between e-health terminals for a periodic ECGsignal. The proposed algorithm consists of five compression procedures and four reconstruction procedures. In order to evaluate the performance of the proposed algorithm, the algorithm was applied to all 48 recordings of MIT-BIH arrhythmia database, and the compress ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), rms, SNR, and quality score (QS) values were obtained. The result showed that the CR was 27.9:1 and the PRD was 2.93 on average for all 48 data instances with a 15% window size. In addition, the performance of the algorithm was compared to those of similar algorithms introduced recently by others. It was found that the proposed algorithm showed clearly superior performance in all 48 data instances at a compression ratio lower than 15:1, whereas it showed similar or slightly inferior PRD performance for a data compression ratio higher than 20:1. In light of the fact that the similarity with the original data becomes meaningless when the PRD is higher than 2, the proposed algorithm shows significantly better performance compared to the performance levels of other algorithms. Moreover, because the algorithm can compress and transmit data in real time, it can be served as an optimal biosignal data transmission method for limited bandwidth communication between e-health devices.

摘要

本文介绍了一种针对周期性 ECG 信号的电子健康终端实时数据压缩和传输算法。该算法由五个压缩过程和四个重构过程组成。为了评估该算法的性能,将该算法应用于 MIT-BIH 心律失常数据库的所有 48 个记录,得到了压缩比(CR)、均方根差百分比(PRD)、均方根差归一化百分比(PRDN)、rms、信噪比(SNR)和质量得分(QS)值。结果表明,对于所有 48 个数据实例,窗口大小为 15%时,CR 平均为 27.9:1,PRD 平均为 2.93。此外,还将该算法的性能与最近其他人提出的类似算法进行了比较。发现该算法在所有 48 个数据实例中,在低于 15:1 的压缩比下表现出明显优于其他算法的性能,而在高于 20:1 的数据压缩比下,其 PRD 性能则相似或略有下降。鉴于 PRD 高于 2 时与原始数据的相似度变得毫无意义,该算法的性能明显优于其他算法。此外,由于该算法可以实时压缩和传输数据,因此可以作为电子健康设备之间有限带宽通信的最佳生物信号数据传输方法。

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