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Automatic de-noising of knee-joint vibration signals using adaptive time-frequency representations

Medical and Biological Engineering and Computing volume 38, pages 2–8 (2000)Cite this article

Abstract

A novel de-noising method for improving the signal-to-noise ratio of knee-joint vibration signals (also known as vibro-arthrographic (VAG) signals) is proposed. The de-noising methods considered are based on signal decomposition techniques, such as wavelets, wavelet packets and the matching pursuit (MP) method. Performance evaluation with synthetic signals simulated with the characteristics expected of VAG signals indicates good de-noising results with the MP method. Statistical pattern classification of non-stationary signal features extracted from time-frequency distributions of 37 (19 normal and 18 abnormal) MP method-de-noised VAG signals shows a sensitivity of 83.3%, a specificity of 84.2% and an overall accuracy of 83.8%.

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Authors and Affiliations

  1. Department of Electrical & Computer Engineering, Ryerson Polytechnic University, Toronto, Ontario, Canada

    S. Krishnan

  2. Department of Electrical & Computer Engineering, University of Calgary, Calgary, Alberta, Canada

    R. M. Rangayyan

Authors
  1. S. Krishnan
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  2. R. M. Rangayyan
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Correspondence to R. M. Rangayyan.

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Krishnan, S., Rangayyan, R.M. Automatic de-noising of knee-joint vibration signals using adaptive time-frequency representations. Med. Biol. Eng. Comput. 38, 2–8 (2000). https://doi.org/10.1007/BF02344681

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  • DOI: https://doi.org/10.1007/BF02344681

Keywords

  • De-noising
  • Time-frequency distributions
  • Matching pursuit
  • Knee-joint sounds
  • Vibro-arthrography