Analysis of knee joint vibration signals in patella-nonresurfacing TKA patients
Date Issued
2008
Date
2008
Author(s)
Chiu, Sheng-Hui
Abstract
Abstract The joint of human body is just like the machine.It liable to cause the damage and degeneration when use it excessively or incorrectly.There is a phenomenon which abnormal joint sound arises from knee joint pathology during knee motion can be detected in the clinical diagnosis.The knee joint could produce vibration signals during normal flexion-extension motion.The objective of this study is to diagnose and discriminate the pathologies of the knee joint by analyzing these vibration signals. This study applied Autoregressive Model and Hilbert-Huang transform--adaptive signal-analysis methodology to the knee joint vibration signal analysis.The methods were tested on the signals of the groups of normal、anterior cruciate ligament(ACL) reconstruction patients and degenerative osteoarthristis patients,and the groups of normal、patella-resurfacing and patella-nonresurfacing TKA patients.The objective of this study is to extract and identify the relevant features in the time domain、frequency domain and time-frequency domain which could differentiate the varieties of pathologies. We have found that application of Hilbert-Huang transform in knee joint vibration signals which are nonstationary and nonlinear in nature gives better ability of analysis.The features extracted from time-frequency distribution show better discriminative ability.We can estimate the knee joint angle which has discrimination between the different knee joint pathologies by analyzing the time-frequency distribution of signal.If this method can be applied to examine the knee joint pathologies in the future,the doctor will make more precise clinical diagnosis. Therefore, time-frequency analysis methods are suitable and have shown good potential for analysis of knee joint vibration signals which are nonstationary and nonlinear in nature. Vibration Arthrometry provided a noninvasive、convenient and cheap clinic tool for diagnosing knee joints. Patients can avoid aches,and the medical resources can be reserve by appropriate therapy.If this research can be continued advancing,the achievements will be the significant clinical diagnosis tools in the future .
Subjects
Vibration Arthrometry
knee joint vibration signals
Type
thesis
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