A new method for denoising knee joint vibroarthrographic signals

Sundar, Aditya; Pahwa, Vivek; Das, Chinmay

doi:10.1109/indicon.2015.7443443

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…Hence, a better pre-processing model for denoising VAG signals is required. Compared with the denoising process for electrocardiogram (ECG), the denoising process for VAG signals is harder because there are few fixed-shape waveforms and inconspicuous peaks and valleys in VAG signals [7]. The VAG signal waveforms vary significantly, depending on whether the knee joints are affected by cartilage or ligament disorders [8].…”

Section: Introductionmentioning

confidence: 99%

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

Gong

Hase

Ohtsu

et al. 2021

Int. j. eng. technol. innov.

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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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Section: Introductionmentioning

confidence: 99%