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Blind extraction of ECG signals based on similarity in the phase space

Author

Listed:
  • Li, Yin
  • Li, Fagang
  • Lyu, Shanxiang
  • Xu, Meng
  • Wang, Shiyuan

Abstract

Electrocardiogram (ECG), as a biological signal that contains important information about the cardiac activities of heart, exhibits chaotic characteristics. Since a clean ECG signal is of vital importance in the diagnosis and analysis of heart diseases, we address the task of extracting ECG for a set of noisy observations. Based on the phase space similarity of ECG, we propose an objective called similarity index which fully describes this similarity. A low-complexity algorithm is presented for the similarity index. Simulation results confirm the effectiveness of the proposed method by making comparisons with conventional benchmarks.

Suggested Citation

  • Li, Yin & Li, Fagang & Lyu, Shanxiang & Xu, Meng & Wang, Shiyuan, 2021. "Blind extraction of ECG signals based on similarity in the phase space," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:chsofr:v:147:y:2021:i:c:s0960077921003040
    DOI: 10.1016/j.chaos.2021.110950
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    References listed on IDEAS

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    1. Shang, Li-Jen & Shyu, Kuo-Kai, 2009. "A method for extracting chaotic signal from noisy environment," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 1120-1125.
    2. Zhao, Yibo & Jiang, Yi & Feng, Jiuchao & Wu, Lifu, 2016. "Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 12-16.
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    Cited by:

    1. Huang, Pengfei & Chai, Yi & Chen, Xiaolong, 2022. "Multiple dynamics analysis of Lorenz-family systems and the application in signal detection," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    2. Deng, Jiarui & Lao, Huimin & Lyu, Shanxiang, 2023. "Compressed chaotic signal reconstruction based on deep learning," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    3. Lou, Shuting & Deng, Jiarui & Lyu, Shanxiang, 2022. "Chaotic signal denoising based on simplified convolutional denoising auto-encoder," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).

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