A novel approach for ECG data compression in healthcare monitoring system

Shun Ren Siao, Chih Cheng Hsu, Mark Po Hung Lin, Shuenn Yuh Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper presents a novel approach for electrocardiogram (ECG) data compression in a healthcare monitoring system, which helps to reduce power consumption during wireless communication. The proposed ECG data compression approach consists of multilevel vector (MLV) compression, integer-linear- programming (ILP)-based compression, and Huffman coding. The MLV compression provides different compression levels for different parts of ECG signal. The ILP-based compression achieves even higher compression ratio while satisfying tolerable error rate. The Huffman coding encodes compressed ECG data without data loss. Experimental results based on the MIT-BIH arrhythmia database show that our approach result in the best quality and accuracy in terms of compression ratio and error rate compared with the previous works.

Original languageEnglish
Title of host publication2014 IEEE International Symposium on Bioelectronics and Bioinformatics, IEEE ISBB 2014
PublisherIEEE Computer Society
ISBN (Print)9781479927708
DOIs
Publication statusPublished - 2014 Jan 1
Event2014 IEEE International Symposium on Bioelectronics and Bioinformatics, IEEE ISBB 2014 - Chung Li, Taiwan
Duration: 2014 Apr 112014 Apr 14

Publication series

Name2014 IEEE International Symposium on Bioelectronics and Bioinformatics, IEEE ISBB 2014

Other

Other2014 IEEE International Symposium on Bioelectronics and Bioinformatics, IEEE ISBB 2014
CountryTaiwan
CityChung Li
Period14-04-1114-04-14

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Health Informatics

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  • Cite this

    Siao, S. R., Hsu, C. C., Lin, M. P. H., & Lee, S. Y. (2014). A novel approach for ECG data compression in healthcare monitoring system. In 2014 IEEE International Symposium on Bioelectronics and Bioinformatics, IEEE ISBB 2014 [6820946] (2014 IEEE International Symposium on Bioelectronics and Bioinformatics, IEEE ISBB 2014). IEEE Computer Society. https://doi.org/10.1109/ISBB.2014.6820946