HapticV1, PubMed, Corpus, bibRecord, 000E93

Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery.

Identifieur interne : 000E93 ( PubMed/Corpus ); précédent : 000E92; suivant : 000E94

Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery.

Auteurs : M. Gomez-Rodriguez ; J. Peters ; J. Hill ; B. Schölkopf ; A. Gharabaghi ; M. Grosse-Wentrup

Source :

Journal of neural engineering [ 1741-2552 ] ; 2011.

RBID : pubmed:21474878

English descriptors

KwdEn :
- Brain (physiology), Evoked Potentials, Motor (physiology), Evoked Potentials, Somatosensory (physiology), Feedback, Physiological (physiology), Female, Humans, Imagination (physiology), Male, Movement (physiology), Robotics (methods), Touch (physiology), User-Computer Interface.
MESH :
- methods : Robotics.
- physiology : Brain, Evoked Potentials, Motor, Evoked Potentials, Somatosensory, Feedback, Physiological, Imagination, Movement, Touch.
- Female, Humans, Male, User-Computer Interface.

Abstract

The combination of brain-computer interfaces (BCIs) with robot-assisted physical therapy constitutes a promising approach to neurorehabilitation of patients with severe hemiparetic syndromes caused by cerebrovascular brain damage (e.g. stroke) and other neurological conditions. In such a scenario, a key aspect is how to reestablish the disrupted sensorimotor feedback loop. However, to date it is an open question how artificially closing the sensorimotor feedback loop influences the decoding performance of a BCI. In this paper, we answer this issue by studying six healthy subjects and two stroke patients. We present empirical evidence that haptic feedback, provided by a seven degrees of freedom robotic arm, facilitates online decoding of arm movement intention. The results support the feasibility of future rehabilitative treatments based on the combination of robot-assisted physical therapy with BCIs.

DOI: 10.1088/1741-2560/8/3/036005
PubMed: 21474878

Links to Exploration step

pubmed:21474878

Le document en format XML

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<author><name sortKey="Gomez Rodriguez, M" sort="Gomez Rodriguez, M" uniqKey="Gomez Rodriguez M" first="M" last="Gomez-Rodriguez">M. Gomez-Rodriguez</name>
<affiliation><nlm:affiliation>MPI for Biological Cybernetics, Tübingen, Germany. manuelgr@stanford.edu</nlm:affiliation>
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<author><name sortKey="Peters, J" sort="Peters, J" uniqKey="Peters J" first="J" last="Peters">J. Peters</name>
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<author><name sortKey="Hill, J" sort="Hill, J" uniqKey="Hill J" first="J" last="Hill">J. Hill</name>
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<author><name sortKey="Scholkopf, B" sort="Scholkopf, B" uniqKey="Scholkopf B" first="B" last="Schölkopf">B. Schölkopf</name>
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<author><name sortKey="Gharabaghi, A" sort="Gharabaghi, A" uniqKey="Gharabaghi A" first="A" last="Gharabaghi">A. Gharabaghi</name>
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<author><name sortKey="Grosse Wentrup, M" sort="Grosse Wentrup, M" uniqKey="Grosse Wentrup M" first="M" last="Grosse-Wentrup">M. Grosse-Wentrup</name>
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<author><name sortKey="Peters, J" sort="Peters, J" uniqKey="Peters J" first="J" last="Peters">J. Peters</name>
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<author><name sortKey="Hill, J" sort="Hill, J" uniqKey="Hill J" first="J" last="Hill">J. Hill</name>
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<author><name sortKey="Scholkopf, B" sort="Scholkopf, B" uniqKey="Scholkopf B" first="B" last="Schölkopf">B. Schölkopf</name>
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<author><name sortKey="Grosse Wentrup, M" sort="Grosse Wentrup, M" uniqKey="Grosse Wentrup M" first="M" last="Grosse-Wentrup">M. Grosse-Wentrup</name>
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<series><title level="j">Journal of neural engineering</title>
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<term>Evoked Potentials, Motor (physiology)</term>
<term>Evoked Potentials, Somatosensory (physiology)</term>
<term>Feedback, Physiological (physiology)</term>
<term>Female</term>
<term>Humans</term>
<term>Imagination (physiology)</term>
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<term>Movement (physiology)</term>
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<front><div type="abstract" xml:lang="en">The combination of brain-computer interfaces (BCIs) with robot-assisted physical therapy constitutes a promising approach to neurorehabilitation of patients with severe hemiparetic syndromes caused by cerebrovascular brain damage (e.g. stroke) and other neurological conditions. In such a scenario, a key aspect is how to reestablish the disrupted sensorimotor feedback loop. However, to date it is an open question how artificially closing the sensorimotor feedback loop influences the decoding performance of a BCI. In this paper, we answer this issue by studying six healthy subjects and two stroke patients. We present empirical evidence that haptic feedback, provided by a seven degrees of freedom robotic arm, facilitates online decoding of arm movement intention. The results support the feasibility of future rehabilitative treatments based on the combination of robot-assisted physical therapy with BCIs.</div>
</front>
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<MeshHeading><DescriptorName MajorTopicYN="N" UI="D014110">Touch</DescriptorName>
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</MeshHeading>
<MeshHeading><DescriptorName MajorTopicYN="N" UI="D014584">User-Computer Interface</DescriptorName>
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Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery.

Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery.

Source :

English descriptors

Abstract

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki