Title :
Denoising knee joint vibration signals using adaptive time-frequency representations
Author :
Krishnan, Sridhar ; Rangayyan, Rangaraj M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
Abstract :
A novel denoising method for improving the signal-to-noise ratio (SNR) of knee joint vibration signals (also known as vibroarthrographic or VAG signals) is proposed. The denoising methods considered are based on signal decomposition techniques such as wavelets, wavelet packets, and the matching pursuit method. Performance evaluation with synthetic signals simulated with characteristics expected of VAG signals indicated good denoising results with the matching pursuit method. Nonstationary signal features extracted and identified from time-frequency distributions of denoised VAG signals have shown good potential in screening for articular cartilage pathology.
Keywords :
acoustic signal processing; adaptive filters; bioacoustics; biomechanics; biomedical measurement; feature extraction; medical signal processing; orthopaedics; patient monitoring; time-frequency analysis; vibrations; wavelet transforms; SNR; VAG signals; adaptive time-frequency representations; articular cartilage pathology; denoised VAG signals; denoising method; knee joint vibration signals; matching pursuit method; nonstationary signal features; screening; signal decomposition techniques; signal-to-noise ratio; synthetic signals; time-frequency distributions; vibroarthrographic signals; wavelet packets; wavelets; Feature extraction; Knee; Matching pursuit algorithms; Noise reduction; Pathology; Signal processing; Signal resolution; Signal to noise ratio; Time frequency analysis; Wavelet packets;
Conference_Titel :
Electrical and Computer Engineering, 1999 IEEE Canadian Conference on
Conference_Location :
Edmonton, Alberta, Canada
Print_ISBN :
0-7803-5579-2
DOI :
10.1109/CCECE.1999.804930