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Discovering Differences in Acoustic Emission Between Healthy and Osteoarthritic Knees Using a Four-Phase Model of Sit-Stand-Sit Movements

机译:使用坐姿-站立-坐姿运动的四阶段模型发现健康与骨关节炎的膝盖之间的声发射差异

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By performing repeated sit-stand-sit movements to create stress on knee joints, short transient bursts of high frequency acoustic emission (AE) released by the knee joints were acquired from two age matched groups consisting of healthy and osteoarthritic (OA) knees, and significant differences between these two groups were discovered from the signal analysis performed. The analysis is based on a four-phase model of sit-stand-sit movements and a two-feature descriptor of AE bursts. The four phases are derived from joint angle measurement during movement, and they consist of the ascending-acceleration and ascending-deceleration phases in the sit-to-stand movement, followed by the descending-acceleration and descending-deceleration phases in the stand-to-sit movement. The two features are extracted from AE measurement during movement, and they consist of the peak magnitude value and average signal level of each AE burst. The proposed analysis method is shown to provide a high sensitivity for differentiation of the two age matched healthy and OA groups, with the most significant difference found to come from the peak magnitude value in the ascending-deceleration phase, clear quantity and strength differences in the image based visual display of their AE feature profiles due to substantially more AE bursts from OA knee joints with higher peak magnitude values and higher average signal levels, and two well separated clusters in the space formed by the principal components. These results provide ample support for further development of AE as a novel tool to facilitate dynamic integrity assessment of knee joints in clinic and home settings.
机译:通过执行反复的坐立运动,以在膝关节上产生压力,从健康和骨关节炎(OA)膝关节组成的两个年龄匹配组中获得了膝关节释放的短暂短暂的高频声发射(AE)突发脉冲。从执行的信号分析中发现了两组之间的显着差异。该分析基于坐姿-坐姿运动的四阶段模型和AE爆发的两个特征描述符。这四个阶段是从运动过程中的关节角度测量得出的,它们包括从坐到站运动的上升-加速和上升-减速阶段,然后是从站立到站立的下降-加速和下降-减速阶段。坐运动。这两个特征是在移动过程中从AE测量中提取的,它们由每个AE突发的峰值和平均信号电平组成。结果表明,所提出的分析方法对区分年龄和年龄的健康人群和OA组具有很高的敏感性,其中最显着的差异来自上升-减速阶段的峰值幅度,明显的数量和强度差异。基于OA膝关节的大量AE突发,具有更高的峰值幅度和更高的平均信号水平,以及由主成分形成的空间中的两个分隔良好的簇,这是基于图像的AE特征轮廓的视觉显示。这些结果为AE的进一步发展提供了充足的支持,AE是一种新颖的工具,可在临床和家庭环境中促进膝关节的动态完整性评估。

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