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
Link To Document :
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