Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation
Identifieur interne : 003196 ( Ncbi/Merge ); précédent : 003195; suivant : 003197Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation
Auteurs : Anusha Venkatakrishnan ; Gerard E. Francisco ; Jose L. Contreras-VidalSource :
- Current physical medicine and rehabilitation reports [ 2167-4833 ] ; 2014.
Abstract
Stroke is a leading cause of disability, significantly impacting the quality of life (QOL) in survivors, and rehabilitation remains the mainstay of treatment in these patients. Recent engineering and technological advances such as brain-machine interfaces (BMI) and robotic rehabilitative devices are promising to enhance stroke neu-rorehabilitation, to accelerate functional recovery and improve QOL. This review discusses the recent applications of BMI and robotic-assisted rehabilitation in stroke patients. We present the framework for integrated BMI and robotic-assisted therapies, and discuss their potential therapeutic, assistive and diagnostic functions in stroke rehabilitation. Finally, we conclude with an outlook on the potential challenges and future directions of these neurotechnologies, and their impact on clinical rehabilitation.
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DOI: 10.1007/s40141-014-0051-4
PubMed: 25110624
PubMed Central: 4122129
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation</title><author><name sortKey="Venkatakrishnan, Anusha" sort="Venkatakrishnan, Anusha" uniqKey="Venkatakrishnan A" first="Anusha" last="Venkatakrishnan">Anusha Venkatakrishnan</name></author><author><name sortKey="Francisco, Gerard E" sort="Francisco, Gerard E" uniqKey="Francisco G" first="Gerard E." last="Francisco">Gerard E. Francisco</name></author><author><name sortKey="Contreras Vidal, Jose L" sort="Contreras Vidal, Jose L" uniqKey="Contreras Vidal J" first="Jose L." last="Contreras-Vidal">Jose L. Contreras-Vidal</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25110624</idno><idno type="pmc">4122129</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4122129</idno><idno type="RBID">PMC:4122129</idno><idno type="doi">10.1007/s40141-014-0051-4</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">001875</idno><idno type="wicri:Area/Pmc/Curation">001875</idno><idno type="wicri:Area/Pmc/Checkpoint">000E16</idno><idno type="wicri:Area/Ncbi/Merge">003196</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation</title><author><name sortKey="Venkatakrishnan, Anusha" sort="Venkatakrishnan, Anusha" uniqKey="Venkatakrishnan A" first="Anusha" last="Venkatakrishnan">Anusha Venkatakrishnan</name></author><author><name sortKey="Francisco, Gerard E" sort="Francisco, Gerard E" uniqKey="Francisco G" first="Gerard E." last="Francisco">Gerard E. Francisco</name></author><author><name sortKey="Contreras Vidal, Jose L" sort="Contreras Vidal, Jose L" uniqKey="Contreras Vidal J" first="Jose L." last="Contreras-Vidal">Jose L. Contreras-Vidal</name></author></analytic><series><title level="j">Current physical medicine and rehabilitation reports</title><idno type="eISSN">2167-4833</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="P1">Stroke is a leading cause of disability, significantly impacting the quality of life (QOL) in survivors, and rehabilitation remains the mainstay of treatment in these patients. Recent engineering and technological advances such as brain-machine interfaces (BMI) and robotic rehabilitative devices are promising to enhance stroke neu-rorehabilitation, to accelerate functional recovery and improve QOL. This review discusses the recent applications of BMI and robotic-assisted rehabilitation in stroke patients. We present the framework for integrated BMI and robotic-assisted therapies, and discuss their potential therapeutic, assistive and diagnostic functions in stroke rehabilitation. Finally, we conclude with an outlook on the potential challenges and future directions of these neurotechnologies, and their impact on clinical rehabilitation.</p></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">101614169</journal-id><journal-id journal-id-type="pubmed-jr-id">42033</journal-id><journal-id journal-id-type="nlm-ta">Curr Phys Med Rehabil Rep</journal-id><journal-id journal-id-type="iso-abbrev">Curr Phys Med Rehabil Rep</journal-id><journal-title-group><journal-title>Current physical medicine and rehabilitation reports</journal-title></journal-title-group><issn pub-type="epub">2167-4833</issn></journal-meta><article-meta><article-id pub-id-type="pmid">25110624</article-id><article-id pub-id-type="pmc">4122129</article-id><article-id pub-id-type="doi">10.1007/s40141-014-0051-4</article-id><article-id pub-id-type="manuscript">NIHMS588181</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Venkatakrishnan</surname><given-names>Anusha</given-names></name><email>avenkatakrishnan@uh.edu</email><aff id="A1">Laboratory for Non-invasive Brain–Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA</aff></contrib><contrib contrib-type="author"><name><surname>Francisco</surname><given-names>Gerard E.</given-names></name><aff id="A2">Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center, Houston, TX, USA</aff><aff id="A3">NeuroRecovery Research Center, TIRR Memorial Hermann Houston, Houston, TX, USA</aff></contrib><contrib contrib-type="author"><name><surname>Contreras-Vidal</surname><given-names>Jose L.</given-names></name><aff id="A4">Laboratory for Non-invasive Brain–Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA</aff></contrib></contrib-group><pub-date pub-type="nihms-submitted"><day>22</day><month>5</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>22</day><month>4</month><year>2014</year></pub-date><pub-date pub-type="ppub"><day>1</day><month>6</month><year>2014</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>6</month><year>2015</year></pub-date><volume>2</volume><issue>2</issue><fpage>93</fpage><lpage>105</lpage><pmc-comment>elocation-id from pubmed: 10.1007/s40141-014-0051-4</pmc-comment>
<permissions><copyright-statement>© Springer Science + Business Media New York 2014</copyright-statement><copyright-year>2014</copyright-year></permissions><abstract><p id="P1">Stroke is a leading cause of disability, significantly impacting the quality of life (QOL) in survivors, and rehabilitation remains the mainstay of treatment in these patients. Recent engineering and technological advances such as brain-machine interfaces (BMI) and robotic rehabilitative devices are promising to enhance stroke neu-rorehabilitation, to accelerate functional recovery and improve QOL. This review discusses the recent applications of BMI and robotic-assisted rehabilitation in stroke patients. We present the framework for integrated BMI and robotic-assisted therapies, and discuss their potential therapeutic, assistive and diagnostic functions in stroke rehabilitation. Finally, we conclude with an outlook on the potential challenges and future directions of these neurotechnologies, and their impact on clinical rehabilitation.</p></abstract><kwd-group><kwd>Brain–machine interfaces</kwd><kwd>Robotic-assisted rehabilitation</kwd><kwd>Robotic exoskeletons</kwd><kwd>Stroke</kwd><kwd>Neurorehabilitation</kwd><kwd>Functional recovery</kwd><kwd>Neuroplasticity</kwd><kwd>Clinical trials</kwd></kwd-group></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Contreras Vidal, Jose L" sort="Contreras Vidal, Jose L" uniqKey="Contreras Vidal J" first="Jose L." last="Contreras-Vidal">Jose L. Contreras-Vidal</name><name sortKey="Francisco, Gerard E" sort="Francisco, Gerard E" uniqKey="Francisco G" first="Gerard E." last="Francisco">Gerard E. Francisco</name><name sortKey="Venkatakrishnan, Anusha" sort="Venkatakrishnan, Anusha" uniqKey="Venkatakrishnan A" first="Anusha" last="Venkatakrishnan">Anusha Venkatakrishnan</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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