• DocumentCode
    2723745
  • Title

    Compression of morphologically similar ECG complexes using neural networks

  • Author

    Hamilton, D.J. ; Sandham, W.A. ; Thomson, D.C.

  • Author_Institution
    Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK
  • fYear
    1995
  • fDate
    34759
  • Firstpage
    42644
  • Lastpage
    42649
  • Abstract
    The authors outline a compression approach capable of achieving low bit rates while reconstructing the signal with a high fidelity. The approach does not involve any clinical classification or parameterisation. It can be seen from the results presented that the use of this neural network compression system can provide excellent compression performance, especially where low bit rates and low reconstruction errors are required. Current work is focusing on a full implementation of the compression system, including the precompression classification stage. Particular emphasis is now being placed on the compression of low SNR ECG signals such as those found in a realistic ambulatory recording environment
  • Keywords
    data compression; electrocardiography; medical signal processing; neural nets; clinical classification; compression performance; electrodiagnostics; high fidelity signal reconstruction; low SNR ECG signals; low bit rates; low reconstruction errors; morphologically similar ECG complexes compression; neural network compression system; parameterisation; precompression classification stage; realistic ambulatory recording environment;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Signal Processing in Cardiography, IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19950282
  • Filename
    478260