• DocumentCode
    807664
  • Title

    Deconvolution estimation of motor unit conduction velocity distribution

  • Author

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

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Dalhousie Univ., Halifax, NS, Canada
  • Volume
    49
  • Issue
    9
  • fYear
    2002
  • Firstpage
    955
  • Lastpage
    962
  • Abstract
    A conduction velocity distribution (CVD) estimator that incorporates volume conductor modeling of the muscle voluntary response is introduced in this paper. The CVD estimates are obtained from two correlation functions, an autocorrelation and a cross, computed from myoelectric signal recorded at the skin surface. The performance of the proposed estimator is evaluated for simulated and experimental data. The study includes assessment of the estimator bias and standard deviation, as well as its sensitivity to errors in the model parameters. Simulations show its good performance in terms of estimator bias. A filtering technique also helps reduce its variance. However, the inaccuracy introduced in the estimation of model parameters considerably deteriorates the estimator performance.
  • Keywords
    deconvolution; electromyography; medical signal processing; parameter estimation; physiological models; velocity measurement; deconvolution estimation; estimator bias; filtering technique; model parameters errors; model parameters estimation; motor unit conduction velocity distribution; muscle voluntary response; skin surface-recorded signal; variance reduction; volume conductor; Autocorrelation; Computational modeling; Conductors; Deconvolution; Delay effects; Delay estimation; Filtering; Muscles; Pediatrics; Skin; Action Potentials; Computer Simulation; Electromyography; Evoked Potentials, Motor; Humans; Models, Neurological; Models, Statistical; Neural Conduction; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Statistics as Topic;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2002.802011
  • Filename
    1028419