• DocumentCode
    380759
  • Title

    Decomposition of superimposed waveforms using the cross time frequency transform

  • Author

    Bonato, P. ; Erim, Z. ; Gonzalez-Cueto, J.A.

  • Author_Institution
    NeuroMuscular Res. Center, Boston Univ., MA, USA
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1066
  • Abstract
    The identification of the timing of the discharges of groups of muscle fibers (motor units) is of utmost importance in research into the strategies employed by the central nervous system in producing muscle force and in the diagnosis of neuromuscular diseases. The process involves the recognition of unique shapes (action potentials) contributed by different motor units at random times throughout a muscle contraction. This paper addresses a specific aspect of the identification process: the decomposition of the compound signal when the action potentials of two or more motor units are superimposed. We propose a cross-time-frequency-based procedure to identify which two (out of a previously identified collection of waveforms) are included in a superposition.
  • Keywords
    electromyography; filtering theory; medical signal processing; signal classification; signal representation; time-frequency analysis; waveform analysis; action potentials; central nervous system strategies; classification procedure; cross time frequency transform; cross-ambiguity function; discharges timing identification; filtering; motor units; muscle contraction; muscle fibers; muscle force; neuromuscular diseases; superimposed waveforms decomposition; Central nervous system; Diseases; Filtering; Interference; Muscles; Neuromuscular; Shape; Signal processing; Time frequency analysis; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-7211-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2001.1020373
  • Filename
    1020373