Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human

Abstract Neuroprosthetics that combine a brain computer interface (BCI) with functional electrical stimulation (FES) can restore voluntary control of a patients’ own paralyzed limbs. To date, human studies have demonstrated an “all-or-none” type of control for a fixed number of pre-determined states...

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Autores principales:	David A. Friedenberg, Michael A. Schwemmer, Andrew J. Landgraf, Nicholas V. Annetta, Marcia A. Bockbrader, Chad E. Bouton, Mingming Zhang, Ali R. Rezai, W. Jerry Mysiw, Herbert S. Bresler, Gaurav Sharma
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d59a282e6e5741bd9dc9de34844ee611
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spelling	oai:doaj.org-article:d59a282e6e5741bd9dc9de34844ee6112021-12-02T11:50:57ZNeuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human10.1038/s41598-017-08120-92045-2322https://doaj.org/article/d59a282e6e5741bd9dc9de34844ee6112017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-08120-9https://doaj.org/toc/2045-2322Abstract Neuroprosthetics that combine a brain computer interface (BCI) with functional electrical stimulation (FES) can restore voluntary control of a patients’ own paralyzed limbs. To date, human studies have demonstrated an “all-or-none” type of control for a fixed number of pre-determined states, like hand-open and hand-closed. To be practical for everyday use, a BCI-FES system should enable smooth control of limb movements through a continuum of states and generate situationally appropriate, graded muscle contractions. Crucially, this functionality will allow users of BCI-FES neuroprosthetics to manipulate objects of different sizes and weights without dropping or crushing them. In this study, we present the first evidence that using a BCI-FES system, a human with tetraplegia can regain volitional, graded control of muscle contraction in his paralyzed limb. In addition, we show the critical ability of the system to generalize beyond training states and accurately generate wrist flexion states that are intermediate to training levels. These innovations provide the groundwork for enabling enhanced and more natural fine motor control of paralyzed limbs by BCI-FES neuroprosthetics.David A. FriedenbergMichael A. SchwemmerAndrew J. LandgrafNicholas V. AnnettaMarcia A. BockbraderChad E. BoutonMingming ZhangAli R. RezaiW. Jerry MysiwHerbert S. BreslerGaurav SharmaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q David A. Friedenberg Michael A. Schwemmer Andrew J. Landgraf Nicholas V. Annetta Marcia A. Bockbrader Chad E. Bouton Mingming Zhang Ali R. Rezai W. Jerry Mysiw Herbert S. Bresler Gaurav Sharma Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human
description	Abstract Neuroprosthetics that combine a brain computer interface (BCI) with functional electrical stimulation (FES) can restore voluntary control of a patients’ own paralyzed limbs. To date, human studies have demonstrated an “all-or-none” type of control for a fixed number of pre-determined states, like hand-open and hand-closed. To be practical for everyday use, a BCI-FES system should enable smooth control of limb movements through a continuum of states and generate situationally appropriate, graded muscle contractions. Crucially, this functionality will allow users of BCI-FES neuroprosthetics to manipulate objects of different sizes and weights without dropping or crushing them. In this study, we present the first evidence that using a BCI-FES system, a human with tetraplegia can regain volitional, graded control of muscle contraction in his paralyzed limb. In addition, we show the critical ability of the system to generalize beyond training states and accurately generate wrist flexion states that are intermediate to training levels. These innovations provide the groundwork for enabling enhanced and more natural fine motor control of paralyzed limbs by BCI-FES neuroprosthetics.
format	article
author	David A. Friedenberg Michael A. Schwemmer Andrew J. Landgraf Nicholas V. Annetta Marcia A. Bockbrader Chad E. Bouton Mingming Zhang Ali R. Rezai W. Jerry Mysiw Herbert S. Bresler Gaurav Sharma
author_facet	David A. Friedenberg Michael A. Schwemmer Andrew J. Landgraf Nicholas V. Annetta Marcia A. Bockbrader Chad E. Bouton Mingming Zhang Ali R. Rezai W. Jerry Mysiw Herbert S. Bresler Gaurav Sharma
author_sort	David A. Friedenberg
title	Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human
title_short	Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human
title_full	Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human
title_fullStr	Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human
title_full_unstemmed	Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human
title_sort	neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/d59a282e6e5741bd9dc9de34844ee611
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Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human

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