Extraction and Screening of Knee Joint Vibroarthrographic Signals Using Independent Component Analysis Method
نویسندگان
چکیده
This study presents a novel method for the extraction and screening of knee joint vibroarthrographic (VAG) signals using an independent component analysis (ICA) technique. Compared to existing VAG methods, the proposed technique has the advantages of a lower computational complexity, a rapid convergence speed, and feature detection. A continuous wavelet transformation (CWT) technique is proposed to carry out knee joint diagnosis based on the extracted vibration signals. The performance of the combined ICA/CWT technique is verified experimentally. The results confirm that the proposed approach represents a viable approach for the noninvasive diagnosis and monitoring of articular cartilage pathology.
منابع مشابه
Screening of knee-joint vibroarthrographic signals using probability density functions estimated with Parzen windows
Pathological conditions of knee joints have been observed to cause changes in the characteristics of vibroarthrographic (VAG) signals. Several studies have proposed many parameters for the analysis and classification of VAG signals; however, no statistical modeling methods have been explored to analyze the distinctions in the probability density functions (PDFs) between normal and abnormal VAG ...
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