Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation
Identifieur interne : 003196 ( Ncbi/Checkpoint ); 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.
Url:
DOI: 10.1007/s40141-014-0051-4
PubMed: 25110624
PubMed Central: 4122129
Affiliations:
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PMC:4122129Le document en format XML
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<author><name sortKey="Francisco, Gerard E" sort="Francisco, Gerard E" uniqKey="Francisco G" first="Gerard E." last="Francisco">Gerard E. Francisco</name>
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<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>
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<name sortKey="Venkatakrishnan, Anusha" sort="Venkatakrishnan, Anusha" uniqKey="Venkatakrishnan A" first="Anusha" last="Venkatakrishnan">Anusha Venkatakrishnan</name>
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