Vibroarthrographic Signals De-Noising Using Wavelet Subband Thresholding
S. H. Rahangdale1, A. K. Mittra2
1S. H. Rahangdale, Department of Electronics Engineering, Manoharbhai Patel Institute of Engineering & Technology, Gondia, India.
2Dr. A. K. Mittra, Department of Electronics Engineering, Manoharbhai Patel Institute of Engineering & Technology, Gondia, India.
Manuscript received on November 27, 2013. | Revised Manuscript received on December 13, 2013. | Manuscript published on December 30, 2013. | PP: 286-289 | Volume-3, Issue-2, December 2013. | Retrieval Number: B2463123213/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Externally recorded knee-joint vibroarthrographic (VAG) signals bear diagnostic information related to degenerative conditions of cartilage disorders in a knee. The VAG technique is passive and can be used for long term monitoring. In order to improve the diagnostic capabilities of VAG, robust signal processing techniques are needed for de-noising of the signals. Traditional de-noising techniques apply a linear filter to remove the noise and interference from the VAG signals. These methods have certain limitations for the non-stationary VAG signals. In this paper, an improved technique for de-noising of VAG signals is presented. The acquired VAG signals are decomposed, de-noised and reconstructed by utilizing matlab wavelet transform toolbox. The proposed approach improves the signal to noise ratio (SNR) of these signals. The presented technique can be used in pre-processing stage of all VAG based knee joint monitoring and screening of articular cartilage pathology.
Keywords: Wavelets, de-noising, Vibroarthrographic signal, Knee-joint.