• DocumentCode
    1341520
  • Title

    Using evoked EMG as a synthetic force sensor of isometric electrically stimulated muscle

  • Author

    Erfanian, Abbas ; Chizeck, Howard Jay ; Hashemi, Reza M.

  • Author_Institution
    Dept. of Biomed. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran
  • Volume
    45
  • Issue
    2
  • fYear
    1998
  • Firstpage
    188
  • Lastpage
    202
  • Abstract
    A method for the estimation of the force generated by electrically stimulated muscle during isometric contraction is developed here. It is based upon measurements of the evoked electromyogram (EMG) [EEMG] signal. Muscle stimulation is provided to the quadriceps muscle of a paralyzed human subject using percutaneous intramuscular electrodes, and EEMG signals are collected using surface electrodes. Through the use of novel signal acquisition and processing techniques, as well, as a mathematical model that reflects both the excitation and activation phenomena involved in isometric muscle force generation, accurate prediction of stimulated muscle forces is obtained for large time horizons. This approach yields synthetic muscle force estimates for both unfatigued and fatigued states of the stimulated muscle. In addition, a method is developed that accomplishes automatic recalibration of the model to account for day-to-day changes in pickup electrode mounting as well as other factors contributing to EEMG gain variations. It is demonstrated that the use of the measured EEMG as the input to a predictive model of muscle torque generation is superior to the use of the electrical stimulation signal as the model input. This is because the measured EEMG signal captures all of the neural excitation, whereas stimulation-to-torque models only reflect that portion of the neural excitation that results directly from stimulation. The time-varying properties of the excitation process cannot be captured by existing stimulation-to-torque models, but they are tracked by the EEMG-to-torque models that are developed here. This work represents a promising approach to the real-time estimation of stimulated muscle force in functional neuromuscular stimulation applications.
  • Keywords
    biomechanics; electromyography; force measurement; medical signal processing; muscle; neurophysiology; physiological models; signal detection; evoked EMG; fatigued state; functional neuromuscular stimulation; isometric electrically stimulated muscle; isometric muscle force generation; mathematical model; muscle torque generation; paralyzed human subject; percutaneous intramuscular electrodes; pickup electrode mounting; quadriceps muscle; signal acquisition; synthetic force sensor; time-varying properties; unfatigued state; Electrodes; Electromyography; Force sensors; Humans; Life estimation; Mathematical model; Muscles; Predictive models; Signal generators; Signal processing; Artifacts; Calibration; Electric Stimulation Therapy; Electrodes; Electromyography; Humans; Isometric Contraction; Knee Joint; Linear Models; Paraplegia; Signal Processing, Computer-Assisted; Stochastic Processes;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.661267
  • Filename
    661267