A novel attempt for diagnosing Outerbridge classification of articular cartilage damage via vibration transmission

Abstract

This study as primary research to propose a non-invasive technique to diagnose the Outerbridge grade of cartilage damage by impact signals. A knee model was experimented with the novel attempt instead of a real knee. The knee model is made by a 3D model converted from magnetic resonance images (MRI) and then assembled by true scale and position. The impact signal is input from the calf and output from the thigh, and the absorption of the impact signal is contended differently by different Outerbridge grades of cartilage. The absorbed impact signals collected by sensors were time-frequency analyzed by continuous Gabor transform (CGT). In addition, the absorbed jerk signal is interpreted by the singular spectrum analysis (SSA) for its oscillation components. The analysis of the signals in this study found that the features derived have abilities to distinguish Outerbridge classification. Therefore, the proposed method can be considered for carrying the experiment onto real knees. This study provides a novel idea to make the diagnostic technique of cartilage damage efficient. Combined with the feature engineering and classification technique, it will help in the clinical diagnosis of knees, this study expects that the method can be applied not only to the diagnosis of the overall knee, but also that the method can diagnose more tiny areas in the early stages of the knee disorder.