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Evolutionary Intelligence

, Volume 9, Issue 3, pp 55–66 | Cite as

Population based ant colony optimization for reconstructing ECG signals

  • Yih-Chun Cheng
  • Tom Hartmann
  • Pei-Yun Tsai
  • Martin Middendorf
Special Issue

Abstract

A population based ant colony optimization algorithm (PACO) for the reconstruction of electrocardiogram (ECG) signals is proposed. Specifically, the PACO finds a subset of nonzero positions of a sparse wavelet domain ECG signal vector that is used for the reconstruction of the signal. A time window is used by the proposed PACO for fixing certain decisions of the ants during the run of the algorithm. The optimization behaviour of the PACO is compared with various algorithms from the literature for ECG signal reconstruction, and with two random search heuristics. Experimental results are presented for ECG signals from the MIT-BIT Arrhythmia database. The influence of several algorithmic parameters and of a local search procedure is evaluated. The results show that the proposed PACO algorithm reconstructs ECG signals with high accuracy.

Keywords

Population based ACO ECG signals Signal reconstruction Subset selection problem 

Notes

Acknowledgments

YCC received financial support granted by German Academic Exchange Service (DAAD) through the Taiwan Summer Institute Programme within 57190416. TH was funded by the German Israeli Foundation (GIF) through the project “Novel gene order analysis methods based on pattern identification in gene interaction networks” within G-2343-407.6/2014.

Supplementary material

12065_2016_139_MOESM1_ESM.pdf (154 kb)
Supplementary material 1 (pdf 154 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Electrical EngineeringNational Central UniversityTaoyuan CityTaiwan
  2. 2.Parallel Computing and Complex Systems Group, Institute of Computer ScienceUniversity LeipzigLeipzigGermany

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