Frank C B, Rangayyan R M, Bell G D
Calgary Univ., Alta.
IEEE Eng Med Biol Mag. 1990;9(1):65-8. doi: 10.1109/51.62910.
The need for a safe, objective, noninvasive tool for the early detection, localization, and quantification of both hyaline articular cartilage and meniscal pathology in the knee is discussed, and the possible use of joint sounds for this purpose is examined. A historical survey of joint sound analysis is given, and the authors' own research is described. The analysis of the knee joint sounds, using time-domain signal plots and three-dimensional spectral plots, supported the authors' assumptions regarding the nature of various degrees of chondromalacia and meniscal lesions, and the associated sounds. Quantitative features such as energy, frequency peaks, duration of signal components, and bandwidths can be easily computed from the data. Further subclassification, however, would require more accurate quantification or parametric representation of signal features, which should be possible by modeling techniques such as linear prediction.
讨论了对一种安全、客观、非侵入性工具的需求,该工具用于早期检测、定位和量化膝关节中的透明关节软骨和半月板病变,并研究了关节声音在此目的上的可能用途。给出了关节声音分析的历史综述,并描述了作者自己的研究。使用时域信号图和三维频谱图对膝关节声音进行分析,支持了作者关于不同程度软骨软化和半月板损伤的性质以及相关声音的假设。诸如能量、频率峰值、信号成分持续时间和带宽等定量特征可以很容易地从数据中计算出来。然而,进一步的细分将需要对信号特征进行更准确的量化或参数表示,这应该可以通过线性预测等建模技术来实现。