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dc.contributor.author
Raspopovic, Stanisa
dc.contributor.author
Carpaneto, Jacopo
dc.contributor.author
Udina, Esther
dc.contributor.author
Navarro, Xavier
dc.contributor.author
Micera, Silvestro
dc.date.accessioned
2018-08-22T12:31:01Z
dc.date.available
2017-06-09T09:24:00Z
dc.date.available
2018-08-22T12:31:01Z
dc.date.issued
2010-04
dc.identifier.issn
1743-0003
dc.identifier.other
10.1186/1743-0003-7-17
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/30243
dc.identifier.doi
10.3929/ethz-b-000030243
dc.description.abstract
Background Several groups have shown that the performance of motor neuroprostheses can be significantly improved by detecting specific sensory events related to the ongoing motor task (e.g., the slippage of an object during grasping). Algorithms have been developed to achieve this goal by processing electroneurographic (ENG) afferent signals recorded by using single-channel cuff electrodes. However, no efforts have been made so far to understand the number and type of detectable sensory events that can be differentiated from whole nerve recordings using this approach. Methods To this aim, ENG afferent signals, evoked by different sensory stimuli were recorded using single-channel cuff electrodes placed around the sciatic nerve of anesthetized rats. The ENG signals were digitally processed and several features were extracted and used as inputs for the classification. The work was performed on integral datasets, without eliminating any noisy parts, in order to be as close as possible to real application. Results The results obtained showed that single-channel cuff electrodes are able to provide information on two to three different afferent (proprioceptive, mechanical and nociceptive) stimuli, with reasonably good discrimination ability. The classification performances are affected by the SNR of the signal, which in turn is related to the diameter of the fibers encoding a particular type of neurophysiological stimulus. Conclusions Our findings indicate that signals of acceptable SNR and corresponding to different physiological modalities (e.g. mediated by different types of nerve fibers) may be distinguished.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/2.0/
dc.subject
Support Vector Machine
en_US
dc.subject
Majority Vote
en_US
dc.subject
Functional Electrical Stimulation
en_US
dc.subject
Nociceptive Stimulus
en_US
dc.subject
Cuff Electrode
en_US
dc.title
On the identification of sensory information from mixed nerves by using single-channel cuff electrodes
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 2.0 Generic
ethz.journal.title
Journal of NeuroEngineering and Rehabilitation
ethz.journal.volume
7
en_US
ethz.journal.abbreviated
J. neuroeng. rehabilitat.
ethz.pages.start
17
en_US
ethz.size
15 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.nebis
005571264
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03428 - Kreuzer, Michael / Kreuzer, Michael
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03428 - Kreuzer, Michael / Kreuzer, Michael
ethz.date.deposited
2017-06-09T09:24:21Z
ethz.source
ECIT
ethz.identifier.importid
imp59364da63057421678
ethz.ecitpid
pub:49916
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-14T22:29:25Z
ethz.rosetta.lastUpdated
2020-02-15T14:30:33Z
ethz.rosetta.versionExported
true
ethz.COinS
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