Broadband Prosthetic Interfaces: Combining Nerve Transfers and Implantable Multichannel EMG Technology to Decode Spinal Motor Neuron Activity
Author(s)
Type
Journal Article
Abstract
Modern robotic hands/upper limbs may replace multiple degrees of freedom of extremity function. However, their intuitive use requires a high number of control signals, which current man-machine interfaces do not provide. Here, we discuss a broadband control interface that combines targeted muscle reinnervation, implantable multichannel electromyographic sensors, and advanced decoding to address the increasing capabilities of modern robotic limbs. With targeted muscle reinnervation, nerves that have lost their targets due to an amputation are surgically transferred to residual stump muscles to increase the number of intuitive prosthetic control signals. This surgery re-establishes a nerve-muscle connection that is used for sensing nerve activity with myoelectric interfaces. Moreover, the nerve transfer determines neurophysiological effects, such as muscular hyper-reinnervation and cortical reafferentation that can be exploited by the myoelectric interface. Modern implantable multichannel EMG sensors provide signals from which it is possible to disentangle the behavior of single motor neurons. Recent studies have shown that the neural drive to muscles can be decoded from these signals and thereby the user's intention can be reliably estimated. By combining these concepts in chronic implants and embedded electronics, we believe that it is in principle possible to establish a broadband man-machine interface, with specific applications in prosthesis control. This perspective illustrates this concept, based on combining advanced surgical techniques with recording hardware and processing algorithms. Here we describe the scientific evidence for this concept, current state of investigations, challenges, and alternative approaches to improve current prosthetic interfaces.
Date Issued
2017-07-19
Online Publication Date
2017-07-19
2017-10-16T09:55:11Z
Date Acceptance
2017-07-05
ISSN
1662-453X
Publisher
FRONTIERS MEDIA SA
Journal / Book Title
FRONTIERS IN NEUROSCIENCE
Volume
11
Copyright Statement
© 2017 Bergmeister, Vujaklija, Muceli, Sturma, Hruby, P
rahm, Riedl,
Salminger, Manzano-Szalai, Aman, Russold, Hofer, Principe,
Farina and Aszmann.
This is an open-access article distributed under the terms o
f the Creative Commons
Attribution License (CC BY https://creativecommons.org/licenses/by/4.0/). The use, distribution or repro
duction in other forums
is permitted, provided the original author(s) or licensor a
re credited and that the
original publication in this journal is cited, in accordanc
e with accepted academic
practice. No use, distribution or reproduction is permitte
d which does not comply
with these terms.
rahm, Riedl,
Salminger, Manzano-Szalai, Aman, Russold, Hofer, Principe,
Farina and Aszmann.
This is an open-access article distributed under the terms o
f the Creative Commons
Attribution License (CC BY https://creativecommons.org/licenses/by/4.0/). The use, distribution or repro
duction in other forums
is permitted, provided the original author(s) or licensor a
re credited and that the
original publication in this journal is cited, in accordanc
e with accepted academic
practice. No use, distribution or reproduction is permitte
d which does not comply
with these terms.
Source Database
pubmed
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000406591600001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Life Sciences & Biomedicine
Neurosciences
Neurosciences & Neurology
myoelectric prosthesis
prosthetic interface
EMG
nerve transfers
TMR
targeted muscle reinnervation
prosthetic control
SUBSEQUENT TARGETED REINNERVATION
UPPER-LIMB AMPUTATION
OF-THE-ART
CROSS INNERVATION
UPPER EXTREMITY
MUSCLE REINNERVATION
HYPER-REINNERVATION
MYOELECTRIC SENSORS
AMPUTEES
SYSTEM
1109 Neurosciences
1702 Cognitive Science
Publication Status
Published
Article Number
ARTN 421