• DocumentCode
    830598
  • Title

    Skin contact forces extracted from human nerve signals - a possible feedback signal for FES-aided control of standing

  • Author

    Andreasen, Lotte N S ; Struijk, Johannes J.

  • Author_Institution
    Center for Sensory Motor Interaction, Aalborg Univ., Denmark
  • Volume
    50
  • Issue
    12
  • fYear
    2003
  • Firstpage
    1320
  • Lastpage
    1325
  • Abstract
    Information about stance related skin contact forces was extracted from nerve cuff electrode recordings of human neural signals. Forces measured under the heel during standing were scaled and applied to the innervation area of the sural nerve on the side of the foot using a hand held force probe. The neural response to the stimuli was measured with a cuff chronically implanted around the sural nerve in one hemiplegic person. An artificial neural network was used for extraction of the applied force from the recorded nerve signal. The results showed that it is possible to extract information about absolute skin contact forces from the nerve signal with an average goodness of fit of 69.3% for all trials and 82.2% for the more dynamic trials. This information may be applicable as a feedback signal in control of standing.
  • Keywords
    biocontrol; bioelectric phenomena; biomechanics; biomedical electrodes; feedback; handicapped aids; medical signal processing; neural nets; neuromuscular stimulation; neurophysiology; patient rehabilitation; prosthetics; skin; ENG response; FES-aided standing control; applied force; artificial neural network; chronically implanted cuff; dynamic trials; feedback signal; foot; goodness of fit; hand held force probe; heel; hemiplegic person; human nerve signals; human neural signals; innervation area; nerve cuff electrode recordings; neural response; recorded nerve signal; rehabilitation; spinal cord injured individuals; stance related skin contact forces; sural nerve; Area measurement; Data mining; Electrodes; Foot; Force control; Force feedback; Force measurement; Humans; Neurofeedback; Skin; Action Potentials; Adult; Algorithms; Electric Stimulation Therapy; Electrophysiology; Feedback; Female; Foot; Humans; Neural Networks (Computer); Signal Processing, Computer-Assisted; Skin Physiology; Statistics as Topic; Stress, Mechanical; Sural Nerve;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2003.819848
  • Filename
    1246371