IEEE Trans Biomed Eng. 2022 May;69(5):1685-1695. doi: 10.1109/TBME.2021.3127030. Epub 2022 Apr 21.
Considering the knee as a fluid-lubricated system, articulating surfaces undergo different lubrication modes and generate joint acoustic emissions (JAEs). The goal of this study is to compare knee biomechanical signals against synchronously recorded joint sounds and assess the hypothesis that JAEs are attributed to tribological origins.
JAE, electromyography, ground reaction force signals, and motion capture markers were synchronously recorded from ten healthy subjects while performing two-leg and one-leg squat exercises. The biomechanical signals were processed to calculate a tribological parameter, lubrication coefficient, and JAEs were divided into short windows and processed to extract 64-time-frequency features. The lubrication coefficients and JAE features of two-leg squats were used to label the windows and train a classifier that discriminates the knee lubrication modes only based on JAE features.
The classifier was used to predict the label of one-leg squat JAE windows and it achieved a high test-accuracy of 84%. The Pearson correlation coefficient between the estimated friction coefficient and predicted JAE scores was 0.83 ± 0.08. Furthermore, the lubrication coefficient threshold, separating two lubrication modes, decreased by half from two-leg to one-leg squats. This result was consistent with tribological changes in the knee load as it was inversely doubled in one-leg squats.
This study supports the potential use of JAEs as a quantitative biomarker to extract tribological information. Since arthritis and similar disease impact the roughness of the joint cartilage, the use of JAEs could have broad implications for studying joint frictions and monitoring joint structural changes with wearable devices.
将膝关节视为一个液力润滑系统,其关节面会经历不同的润滑模式并产生关节声发射(JAEs)。本研究旨在比较膝关节生物力学信号与同步记录的关节声音,并验证 JAEs 归因于摩擦学起源的假设。
本研究同步记录了 10 名健康受试者在进行双腿和单腿深蹲运动时的 JAEs、肌电图、地面反力信号和运动捕捉标记。对生物力学信号进行处理以计算摩擦学参数——润滑系数,将 JAEs 分为短窗口并进行处理以提取 64 个时频特征。使用双腿深蹲的润滑系数和 JAE 特征对窗口进行标记,并训练一个分类器,该分类器仅基于 JAE 特征即可区分膝关节的润滑模式。
该分类器用于预测单腿深蹲 JAE 窗口的标签,其测试准确率高达 84%。估计摩擦系数与预测 JAE 得分之间的 Pearson 相关系数为 0.83±0.08。此外,从双腿到单腿深蹲,区分两种润滑模式的润滑系数阈值降低了一半。这一结果与膝关节负荷的摩擦学变化一致,因为单腿深蹲时膝关节负荷反向增加了一倍。
本研究支持 JAEs 作为提取摩擦学信息的定量生物标志物的潜在用途。由于关节炎和类似疾病会影响关节软骨的粗糙度,因此 JAEs 的使用可能对研究关节摩擦和使用可穿戴设备监测关节结构变化具有广泛意义。