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Title:Noninvasive, accurate assessment of the behavior of representative populations of motor units in targeted reinnervated muscles
Authors:ID Farina, Dario (Author)
ID Rehbaum, Hubertus (Author)
ID Holobar, Aleš (Author)
ID Vujaklija, Ivan (Author)
ID Jiang, Ning (Author)
ID Hofer, Christian (Author)
ID Salminger, Stefan (Author)
ID van Vliet, Hans-Willem (Author)
ID Aszmann, Oskar (Author)
Files: This document has no files. This document may have a physical copy in the library of the organization, check the status via COBISS. Link is opened in a new window
Language:English
Work type:Unknown
Typology:1.01 - Original Scientific Article
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Targeted muscle reinnervation (TMR) redirects nerves that have lost their target, due to amputation, to remaining muscles in the region of the stump with the intent of establishing intuitive myosignals to control a complex prosthetic device. In order to directly recover the neural code underlying an attempted limb movement, in this paper, we present the decomposition of high-density surface electromyographic (EMG) signals detected from three TMR patients into the individual motor unit spike trains. The aim was to prove, for the first time, the feasibility of decoding the neural drive that would reach muscles of the missing limb in TMR patients, to show the accuracy of the decoding, and to demonstrate the representativeness of the pool of extracted motor units. Six to seven flexible EMG electrode grids of 64 electrodes each were mounted over the reinnervated muscles of each patient, resulting in up to 448 EMG signals. The subjects were asked to attempt elbow extension and flexion, hand open and close, wrist extension and flexion, wrist pronation and supination, of their missing limb. The EMG signals were decomposed using the Convolution Kernel Compensation technique and the decomposition accuracy was evaluated with a signal-based index of accuracy, called pulse-to-noise ratio (PNR). The results showed that the spike trains of 3 to 27 motor units could be identified for each task, with a sensitivity of the decomposition > 90%, as revealed by PNR. The motor unit discharge rates were within physiological values of normally innervated muscles. Moreover, the detected motor units showed a high degree of common drive so that the set of extracted units per task was representative of the behavior of the population of active units. The results open a path for a new generation of human-machine interfaces in which the control signals are extracted from noninvasive recordings and the obtained neural information is based directly on the spike trains of motor neurons.
Keywords:electromyographic, EMG, decomposition, high-density EMG, motor neuron, motor unit, myoelectronic control, neural drive to muscle, target muscle reinervation, TMR
Publication status:Published
Year of publishing:2014
Number of pages:str. 810-819
Numbering:#Vol. #22, #no. #4
PID:20.500.12556/DKUM-48145 New window
UDC:007.5:61
ISSN on article:1534-4320
COBISS.SI-ID:18017558 New window
NUK URN:URN:SI:UM:DK:PP2PPZU4
Publication date in DKUM:25.05.2015
Views:1521
Downloads:0
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Categories:Misc.
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Record is a part of a journal

Title:IEEE transactions on neural systems and rehabilitation engineering
Shortened title:IEEE trans. neural syst. rehabil. eng.
Publisher:IEEE
ISSN:1534-4320
COBISS.SI-ID:320873 New window

Document is financed by a project

Funder:EC - European Commission
Funding programme:FP7
Project number:287739
Name:A novel conceptfor support to diagnosis and remote management of tremor’
Acronym:NeuroTREMOR

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