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Population based ant colony optimization for reconstructing ECG signals

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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.

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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.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Central University, Taoyuan City, Taiwan

    Yih-Chun Cheng & Pei-Yun Tsai

  2. Parallel Computing and Complex Systems Group, Institute of Computer Science, University Leipzig, Leipzig, Germany

    Tom Hartmann & Martin Middendorf

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  1. Yih-Chun Cheng
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  2. Tom Hartmann
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  3. Pei-Yun Tsai
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  4. Martin Middendorf
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Correspondence to Martin Middendorf.

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Cheng, YC., Hartmann, T., Tsai, PY. et al. Population based ant colony optimization for reconstructing ECG signals. Evol. Intel. 9, 55–66 (2016). https://doi.org/10.1007/s12065-016-0139-0

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