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JSM-2 based joint ECG compressed sensing with partially known support establishment

  • University of Science and Technology of China

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Compressed sensing (CS) is a technique that enables sparse signal reconstruction from much fewer samples. In this paper, we propose ECG compressed sensing methods based on distributed compressed sensing to exploit the joint sparsity for both single- and multi-lead ECG signals. We apply JSM-2 (joint sparse model type 2) for jointly sparse ECG signals and formulate how to establish a partially known support based on this type of sparse model. Through careful analysis of joint partially known support, two-step ECG signal reconstruction schemes for single-lead and multi-lead ECG signals are developed. Simulation results show that the proposed schemes based on partially known support establishment outperforms existing schemes with enhanced performance measured by percentage root mean square difference (PRD).

Original languageEnglish
Title of host publication2012 IEEE 14th International Conference on e-Health Networking, Applications and Services, Healthcom 2012
Pages435-438
Number of pages4
DOIs
StatePublished - 2012
Event2012 IEEE 14th International Conference on e-Health Networking, Applications and Services, Healthcom 2012 - Beijing, China
Duration: Oct 10 2012Oct 13 2012

Publication series

Name2012 IEEE 14th International Conference on e-Health Networking, Applications and Services, Healthcom 2012

Conference

Conference2012 IEEE 14th International Conference on e-Health Networking, Applications and Services, Healthcom 2012
Country/TerritoryChina
CityBeijing
Period10/10/1210/13/12

Keywords

  • ECG compression
  • JSM-2
  • compressed sensing
  • joint sparse model
  • signal reconstruction

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