Robotic neurorehabilitation: a computational motor learning perspective
Identifieur interne : 001057 ( Ncbi/Curation ); précédent : 001056; suivant : 001058Robotic neurorehabilitation: a computational motor learning perspective
Auteurs : Vincent S. Huang [États-Unis] ; John W. Krakauer [États-Unis]Source :
- Journal of NeuroEngineering and Rehabilitation [ 1743-0003 ] ; 2009.
Abstract
Conventional neurorehabilitation appears to have little impact on impairment over and above that of spontaneous biological recovery. Robotic neurorehabilitation has the potential for a greater impact on impairment due to easy deployment, its applicability across of a wide range of motor impairment, its high measurement reliability, and the capacity to deliver high dosage and high intensity training protocols.
We first describe current knowledge of the natural history of arm recovery after stroke and of outcome prediction in individual patients. Rehabilitation strategies and outcome measures for impairment versus function are compared. The topics of dosage, intensity, and time of rehabilitation are then discussed.
Robots are particularly suitable for both rigorous testing and application of motor learning principles to neurorehabilitation. Computational motor control and learning principles derived from studies in healthy subjects are introduced in the context of robotic neurorehabilitation. Particular attention is paid to the idea of context, task generalization and training schedule. The assumptions that underlie the choice of both movement trajectory programmed into the robot and the degree of active participation required by subjects are examined. We consider rehabilitation as a general learning problem, and examine it from the perspective of theoretical learning frameworks such as supervised and unsupervised learning. We discuss the limitations of current robotic neurorehabilitation paradigms and suggest new research directions from the perspective of computational motor learning.
Url:
DOI: 10.1186/1743-0003-6-5
PubMed: 19243614
PubMed Central: 2653497
Links toward previous steps (curation, corpus...)
- to stream Pmc, to step Corpus: Pour aller vers cette notice dans l'étape Curation :000B87
- to stream Pmc, to step Curation: Pour aller vers cette notice dans l'étape Curation :000B87
- to stream Pmc, to step Checkpoint: Pour aller vers cette notice dans l'étape Curation :002056
- to stream Ncbi, to step Merge: Pour aller vers cette notice dans l'étape Curation :001057
Links to Exploration step
PMC:2653497Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Robotic neurorehabilitation: a computational motor learning perspective</title>
<author><name sortKey="Huang, Vincent S" sort="Huang, Vincent S" uniqKey="Huang V" first="Vincent S" last="Huang">Vincent S. Huang</name>
<affiliation wicri:level="2"><nlm:aff id="I1">Motor Performance Laboratory, Department of Neurology, The Neurological Institute, Columbia University College of Physicians and Surgeons, New York, New York, USA</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Motor Performance Laboratory, Department of Neurology, The Neurological Institute, Columbia University College of Physicians and Surgeons, New York, New York</wicri:regionArea>
<placeName><region type="state">État de New York</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Krakauer, John W" sort="Krakauer, John W" uniqKey="Krakauer J" first="John W" last="Krakauer">John W. Krakauer</name>
<affiliation wicri:level="2"><nlm:aff id="I1">Motor Performance Laboratory, Department of Neurology, The Neurological Institute, Columbia University College of Physicians and Surgeons, New York, New York, USA</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Motor Performance Laboratory, Department of Neurology, The Neurological Institute, Columbia University College of Physicians and Surgeons, New York, New York</wicri:regionArea>
<placeName><region type="state">État de New York</region>
</placeName>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PMC</idno>
<idno type="pmid">19243614</idno>
<idno type="pmc">2653497</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2653497</idno>
<idno type="RBID">PMC:2653497</idno>
<idno type="doi">10.1186/1743-0003-6-5</idno>
<date when="2009">2009</date>
<idno type="wicri:Area/Pmc/Corpus">000B87</idno>
<idno type="wicri:Area/Pmc/Curation">000B87</idno>
<idno type="wicri:Area/Pmc/Checkpoint">002056</idno>
<idno type="wicri:Area/Ncbi/Merge">001057</idno>
<idno type="wicri:Area/Ncbi/Curation">001057</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Robotic neurorehabilitation: a computational motor learning perspective</title>
<author><name sortKey="Huang, Vincent S" sort="Huang, Vincent S" uniqKey="Huang V" first="Vincent S" last="Huang">Vincent S. Huang</name>
<affiliation wicri:level="2"><nlm:aff id="I1">Motor Performance Laboratory, Department of Neurology, The Neurological Institute, Columbia University College of Physicians and Surgeons, New York, New York, USA</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Motor Performance Laboratory, Department of Neurology, The Neurological Institute, Columbia University College of Physicians and Surgeons, New York, New York</wicri:regionArea>
<placeName><region type="state">État de New York</region>
</placeName>
</affiliation>
</author>
<author><name sortKey="Krakauer, John W" sort="Krakauer, John W" uniqKey="Krakauer J" first="John W" last="Krakauer">John W. Krakauer</name>
<affiliation wicri:level="2"><nlm:aff id="I1">Motor Performance Laboratory, Department of Neurology, The Neurological Institute, Columbia University College of Physicians and Surgeons, New York, New York, USA</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Motor Performance Laboratory, Department of Neurology, The Neurological Institute, Columbia University College of Physicians and Surgeons, New York, New York</wicri:regionArea>
<placeName><region type="state">État de New York</region>
</placeName>
</affiliation>
</author>
</analytic>
<series><title level="j">Journal of NeuroEngineering and Rehabilitation</title>
<idno type="eISSN">1743-0003</idno>
<imprint><date when="2009">2009</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p>Conventional neurorehabilitation appears to have little impact on impairment over and above that of spontaneous biological recovery. Robotic neurorehabilitation has the potential for a greater impact on impairment due to easy deployment, its applicability across of a wide range of motor impairment, its high measurement reliability, and the capacity to deliver high dosage and high intensity training protocols.</p>
<p>We first describe current knowledge of the natural history of arm recovery after stroke and of outcome prediction in individual patients. Rehabilitation strategies and outcome measures for impairment versus function are compared. The topics of dosage, intensity, and time of rehabilitation are then discussed.</p>
<p>Robots are particularly suitable for both rigorous testing and application of motor learning principles to neurorehabilitation. Computational motor control and learning principles derived from studies in healthy subjects are introduced in the context of robotic neurorehabilitation. Particular attention is paid to the idea of context, task generalization and training schedule. The assumptions that underlie the choice of both movement trajectory programmed into the robot and the degree of active participation required by subjects are examined. We consider rehabilitation as a general learning problem, and examine it from the perspective of theoretical learning frameworks such as supervised and unsupervised learning. We discuss the limitations of current robotic neurorehabilitation paradigms and suggest new research directions from the perspective of computational motor learning.</p>
</div>
</front>
<back><div1 type="bibliography"><listBibl><biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
<biblStruct></biblStruct>
</listBibl>
</div1>
</back>
</TEI>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/HapticV1/Data/Ncbi/Curation
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 001057 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Ncbi/Curation/biblio.hfd -nk 001057 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Ticri/CIDE |area= HapticV1 |flux= Ncbi |étape= Curation |type= RBID |clé= PMC:2653497 |texte= Robotic neurorehabilitation: a computational motor learning perspective }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Ncbi/Curation/RBID.i -Sk "pubmed:19243614" \ | HfdSelect -Kh $EXPLOR_AREA/Data/Ncbi/Curation/biblio.hfd \ | NlmPubMed2Wicri -a HapticV1
![]() | This area was generated with Dilib version V0.6.23. | ![]() |