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ORIGINAL RESEARCH article

Front. Neuroinform.
Volume 18 - 2024 | doi: 10.3389/fninf.2024.1454244
This article is part of the Research Topic Recent Applications of Noninvasive Physiological Signals and Artificial Intelligence View all 5 articles

Research on ECG signal reconstruction based on improved weighted nuclear norm minimization and approximate message passing algorithm

Provisionally accepted
Bing Zhang Bing Zhang 1Xishun Zhu Xishun Zhu 2*Fadia A. Khan Fadia A. Khan 3Sajjad S. Jamal Sajjad S. Jamal 4Alanoud A. Mazroa Alanoud A. Mazroa 5Rab Nawaz Rab Nawaz 6
  • 1 Nanyang Institute of Technology, Nanyang, China
  • 2 Hainan Normal University, Haikou, Hainan Province, China
  • 3 HITEC University, Taxila, Punjab, Pakistan
  • 4 King Khalid University, Abha, Saudi Arabia
  • 5 Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
  • 6 University of Essex, Colchester, East of England, United Kingdom

The final, formatted version of the article will be published soon.

    In order to improve the energy efficiency of wearable devices, it is necessary to compress and reconstruct the collected electrocardiogram data. The compressed data may be mixed with noise during the transmission process. The denoising-based Approximate Message Passing (AMP) algorithm performs well in reconstructing noisy signals, so the denoising-based AMP algorithm is introduced into electrocardiogram signal reconstruction. The weighted nuclear norm minimization algorithm (WNNM) uses the low-rank characteristics of similar signal blocks for denoising, and averages the signal blocks after low-rank decomposition to obtain the final denoised signal. However, under the influence of noise, there may be errors in searching for similar blocks, resulting in dissimilar signal blocks being grouped together, affecting the denoising effect. Based on this, this paper improves the WNNM algorithm and proposes to use weighted averaging instead of direct averaging for the signal blocks after low-rank decomposition in the denoising process, and validating its effectiveness on electrocardiogram signals. Experimental results demonstrate that the IWNNM-AMP algorithm achieves the best reconstruction performance under different compression ratios and noise conditions, obtaining the lowest PRD and RMSE values. Compared with the WNNM-AMP algorithm, the PRD value is reduced by 0.17~4.56, the P-SNR value is improved by 0.12~2.70.Keywords ECG, compressed sensing, non-local similarity, weighted nuclear norm minimization, approximate message passing algorithm 参考文献 [1] Balouehestani M, Raahemifar K, Krishnan S. New sampling approach for wireless ECG systems with compressed sensing theory [C]. Medical Measurements and Applications Proceedings (MeMeA), 2013.213-218.

    Keywords: ECG, compressed sensing, Non-local similarity, Weighted nuclear norm minimization, approximate message passing algorithm

    Received: 24 Jun 2024; Accepted: 09 Sep 2024.

    Copyright: © 2024 Zhang, Zhu, Khan, Jamal, Mazroa and Nawaz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Xishun Zhu, Hainan Normal University, Haikou, 571 158, Hainan Province, China

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