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Post-processing algorithm for removing soft-tissue movement artifacts from vibroarthrographic knee-joint signal

机译:后处理算法,可从震动性膝关节炎信号中去除软组织运动伪影

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Vibroarthrographic (VAG) signals are sounds or vibrations caused when a knee joint is flexed or stretched. VAG signal collection is noninvasive and can be performed using an accelerometer or microphone attached to the skin. However, the sensor attached to the skin will move with the soft tissue caused by flexion and extension, causing the baseline of the VAG signal to drift. We call these interferences soft tissue movement artifacts (STMAs). In this study, an algorithm is proposed to filter out STMAs. We compare the proposed method’s results with noises collected by an accelerometer. The noise reduction effect is evaluated, revealing an 11.85% increase in the peak signal-to-noise ratio and a 28.18% increase in signal-to-noise ratio compared with the case in which STMA noise was not removed.Clinical Relevance-This study focuses on a proposed post-processing method that can remove soft tissue movement artifacts that cause baseline wander and could thus improve the accuracy of clinical applications of VAG signals.
机译:颤动(VAG)信号是弯曲或拉伸膝关节时引起的声音或振动。 VAG信号采集是非侵入性的,可以使用附着在皮肤上的加速度计或麦克风进行采集。但是,附着在皮肤上的传感器会因弯曲和伸展而与软组织一起移动,从而导致VAG信号的基线漂移。我们将这些干扰称为软组织运动伪影(STMA)。在这项研究中,提出了一种算法来过滤出STMA。我们将建议方法的结果与加速度计收集到的噪声进行比较。评估了降噪效果,与未去除STMA噪声的情况相比,峰值信噪比提高了11.85%,信噪比提高了28.18%。重点介绍了一种提议的后处理方法,该方法可以消除引起基线漂移的软组织运动伪影,从而可以提高VAG信号临床应用的准确性。

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