Vibroarthrographic Signals De-Noising Using Wavelet Subband Thresholding
Vibroarthrographic Signals De-Noising Using Wavelet Subband Thresholding
复制标题
使用小波子带阈值进行振动关节信号去噪
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
A. Mittra
中科院分区：
文献类型：
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作者：
S. Rahangdale;A. Mittra
外部记录的膝关节振动关节造影（VAG）信号承载与膝关节中的软骨疾病的退行性病症相关的诊断信息。VAG技术是被动的，可用于长期监测。为了提高VAG的诊断能力，需要稳健的信号处理技术来对信号进行去噪。传统的去噪技术应用线性滤波器从VAG信号中去除噪声和干扰。这些方法对于非平稳的VAG信号都有一定的局限性。本文提出了一种改进的VAG信号去噪方法。利用matlab小波变换工具箱对采集到的VAG信号进行分解、去噪和重构。所提出的方法提高了这些信号的信噪比（SNR）。该技术可用于所有基于VAG的膝关节监测的预处理阶段和关节软骨病理的筛查。
Externally recorded knee-joint vibroarthrographic (VAG) signals bear diagnostic information related to degenerative conditions of cartilage disorders in a knee. The VAG technique is passive and can be used for long term monitoring. In order to improve the diagnostic capabilities of VAG, robust signal processing techniques are needed for de-noising of the signals. Traditional de-noising techniques apply a linear filter to remove the noise and interference from the VAG signals. These methods have certain limitations for the non-stationary VAG signals. In this paper, an improved technique for de-noising of VAG signals is presented. The acquired VAG signals are decomposed, de-noised and reconstructed by utilizing matlab wavelet transform toolbox. The proposed approach improves the signal to noise ratio (SNR) of these signals. The presented technique can be used in pre-processing stage of all VAG based knee joint monitoring and screening of articular cartilage pathology.