Skip to main content

Wavelet-Domain L  ∞ -Constrained Two-Stage Near-Lossless EEG Coder

  • Conference paper
Information Processing and Management (BAIP 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 70))

Abstract

In this paper, a two-stage coder based near-lossless compression of Electroencephalogram (EEG) is discussed. It consists of wavelet based lossy coding layer (until bitplane n d ) followed by entropy coding of the wavelet domain residuals. L  ∞ -error bound is fixed in wavelet domain and the corresponding time-domain absolute error variation is studied. Studies show that intermediate demarcating bit-planes (n d ) register a higher compression and gives a nearly constant time-domain error. Both the normal and epileptic EEG registered a comparable compression performance.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Antoniol, G., Tonella, P.: EEG data compression techniques. IEEE Transactions on Biomedical Engineering 44(2), 105–114 (1997)

    Article  Google Scholar 

  2. Calderbank, R., Daubechies, I., Sweldens, W., Yeo, B.L.: Wavelet transforms that map integers to integers. Appl. Comput. Harmon. Anal. 5(3), 332–369 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  3. Lu, Z., Kim, D.Y., Pearlman, W.: Wavelet compression of ECG signals by the set partitioning in hierarchial trees algorithm. IEEE Transactions on Biomedical Engineering 47(7), 849–855 (2000)

    Article  Google Scholar 

  4. Memon, N., Kong, X., Cinkler, J.: Context-based lossless and near-lossless compression of EEG signals. IEEE Transactions on information technology in Biomedicine 3(3), 231–238 (1999)

    Article  Google Scholar 

  5. Sriraam, N., Eswaran, C.: Performance evaluation of neural network and linear predictors for near-lossless compression of EEG signals. IEEE Transactions on Information Technology in Biomedicine 12(1), 87–93 (2008)

    Article  Google Scholar 

  6. Srinivasan, K., Reddy, M.R.: Efficient pre-processing technnique for real-time lossless EEG compression. IET Electrionics Letters (in press)

    Google Scholar 

  7. Srinivasan, K., Reddy, M.R.: Selection of optimal wavelet for lossless EEG compression for real-time applications. In: 2nd National conference on Bio-mechanics, IIT Roorke, India (March 2009)

    Google Scholar 

  8. Yea, S., Pearlman, W.: A wavelet-based two stage near lossless coder. IEEE transactions in Image processing 15(11), 3488–3500 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Srinivasan, K., Reddy, M.R. (2010). Wavelet-Domain L  ∞ -Constrained Two-Stage Near-Lossless EEG Coder. In: Das, V.V., et al. Information Processing and Management. BAIP 2010. Communications in Computer and Information Science, vol 70. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12214-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-12214-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12213-2

  • Online ISBN: 978-3-642-12214-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics