Adaptive Vibrarthographic Signal Denoising via Ant Colony Optimization Using Dynamic Denoising Filter Parameters

  • Rui Gong Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan; Informatics and Computer Education Center, Mejiro University, Tokyo, Japan
  • Kazunori Hase Faculty of Systems Design, Tokyo Metropolitan University, Tokyo, Japan
  • Hajime Ohtsu Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan; Japan Society for the Promotion of Science, Tokyo, Japan
  • Susumu Ota Faculty of Rehabilitation and Care, Seijoh University, Nagoya, Japan
Keywords: ant colony optimization, denoising, ensemble empirical mode decomposition, vibrarthographic signal


This study proposes an ant colony optimization (ACO) denoising method with dynamic filter parameters. The proposed method is developed based on ensemble empirical mode decomposition (EEMD), and aims to improve the quality of vibrarthographic (VAG) signals. It mixes the original VAG signals with different white noise amplitudes, and adopts a hybrid technology that combines EEMD with a Savitzky-Golay (SG) filter containing the dynamic parameters optimized by ACO. The results show that the proposed method provides a higher peak signal-to-noise ratio (PSNR) and a smaller root-mean-square difference than the regular methods. The SNR improvement for the VAG signals of normal knees can reach 13 dB while maintaining the original signal structure, and the SNR improvement for the VAG signals of abnormal knees can reach 20 dB. The method proposed in this study can improve the quality of nonstationary VAG signals.


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How to Cite
R. Gong, K. Hase, H. Ohtsu, and S. Ota, “Adaptive Vibrarthographic Signal Denoising via Ant Colony Optimization Using Dynamic Denoising Filter Parameters”, Int. j. eng. technol. innov., vol. 12, no. 1, pp. 01-15, Dec. 2021.