Coding of biosignals using the discrete wavelet decomposition

  • Authors:

  • Ramon Reig-Bolaño;Pere Marti-Puig;Jordi Solé-Casals;Vladimir Zaiats;Vicenç Parisi

  • Affiliations:

  • Digital Technologies Group, University of Vic, Vic, Spain, EU;Digital Technologies Group, University of Vic, Vic, Spain, EU;Digital Technologies Group, University of Vic, Vic, Spain, EU;Digital Technologies Group, University of Vic, Vic, Spain, EU;Electronic Eng. Dep. Polith, Univ. of Catalonia

  • Venue:
  • NOLISP'09 Proceedings of the 2009 international conference on Advances in Nonlinear Speech Processing
  • Year:
  • 2009

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Abstract

Wavelet derived codification techniques are widespread used in image codifiers. The wavelet based compression methods are adequate for representing transients. In this paper we explore the use of the discrete wavelet transform analysis of biological signals in order to improve the data compression capability of data coders. The wavelet analysis provides a subband decomposition of any signal, and this enables a lossless or a lossy implementation with the same architecture. The signals could range from speech to sounds or music, but the approach is more orientated to other biosignals like medical signals EEG, ECG or discrete series. Experimental results based on wavelet coefficients quantification, show a lossless compression of 2:1 in all kind of signals, with a fidelity, measured using PSNR, from 79dB to 100dB, and lossy results preserving most of the signal waveform, with a compression ratio from 3:1 to 5:1, with a fidelity from 25dB to 35 dB.