• DocumentCode
    1559358
  • Title

    Deconvolution estimation of nerve conduction velocity distribution

  • Author

    González-Cueto, José A. ; Parker, Philip A.

  • Author_Institution
    Inst. of Biomed. Eng., New Brunswick Univ., Fredericton, NB, Canada
  • Volume
    49
  • Issue
    2
  • fYear
    2002
  • Firstpage
    140
  • Lastpage
    151
  • Abstract
    A conduction velocity distribution (CVD) estimator that incorporates volume conductor modeling of the nerve-evoked response is introduced in this paper. The CVD estimates are obtained from two compound nerve action potentials (CNAP) recorded at the skin surface. A third channel is introduced in order to assess the estimator performance in the experimental case. The relevance of using an accurate signal model is shown by comparing the performance of the proposed estimator with a previous approach based on a different CNAP model. The performance of the proposed estimator is evaluated for simulated and experimental data. The study assesses signal-to-noise ratio immunity and sensitivity to errors in the model parameters.
  • Keywords
    Legendre polynomials; bioelectric potentials; biomembrane transport; deconvolution; inverse problems; least mean squares methods; medical signal processing; neurophysiology; physiological models; Legendre polynomial; accurate signal model; compound nerve action potentials; constrained optimization problem; deconvolution estimation; error sensitivity; estimator performance; extracellular potential; inverse problem; mean square error; nerve conduction velocity distribution; nerve-evoked response; noninvasive techniques; signal-to-noise ratio immunity; skin surface; surface single fiber action potential; time convolution operation; volume conductor modeling; Conductors; Deconvolution; Diabetes; Nervous system; Neuromuscular; Niobium; Pathology; Signal to noise ratio; Skin; Testing; Action Potentials; Algorithms; Computer Simulation; Humans; Models, Neurological; Models, Theoretical; Neural Conduction; Reproducibility of Results; Stochastic Processes;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.979353
  • Filename
    979353