Literature DB >> 23494615

Brain-machine interface in chronic stroke rehabilitation: a controlled study.

Ander Ramos-Murguialday1, Doris Broetz, Massimiliano Rea, Leonhard Läer, Ozge Yilmaz, Fabricio L Brasil, Giulia Liberati, Marco R Curado, Eliana Garcia-Cossio, Alexandros Vyziotis, Woosang Cho, Manuel Agostini, Ernesto Soares, Surjo Soekadar, Andrea Caria, Leonardo G Cohen, Niels Birbaumer.   

Abstract

OBJECTIVE: Chronic stroke patients with severe hand weakness respond poorly to rehabilitation efforts. Here, we evaluated efficacy of daily brain-machine interface (BMI) training to increase the hypothesized beneficial effects of physiotherapy alone in patients with severe paresis in a double-blind sham-controlled design proof of concept study.
METHODS: Thirty-two chronic stroke patients with severe hand weakness were randomly assigned to 2 matched groups and participated in 17.8 ± 1.4 days of training rewarding desynchronization of ipsilesional oscillatory sensorimotor rhythms with contingent online movements of hand and arm orthoses (experimental group, n = 16). In the control group (sham group, n = 16), movements of the orthoses occurred randomly. Both groups received identical behavioral physiotherapy immediately following BMI training or the control intervention. Upper limb motor function scores, electromyography from arm and hand muscles, placebo-expectancy effects, and functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent activity were assessed before and after intervention.
RESULTS: A significant group × time interaction in upper limb (combined hand and modified arm) Fugl-Meyer assessment (cFMA) motor scores was found. cFMA scores improved more in the experimental than in the control group, presenting a significant improvement of cFMA scores (3.41 ± 0.563-point difference, p = 0.018) reflecting a clinically meaningful change from no activity to some in paretic muscles. cFMA improvements in the experimental group correlated with changes in fMRI laterality index and with paretic hand electromyography activity. Placebo-expectancy scores were comparable for both groups.
INTERPRETATION: The addition of BMI training to behaviorally oriented physiotherapy can be used to induce functional improvements in motor function in chronic stroke patients without residual finger movements and may open a new door in stroke neurorehabilitation.
Copyright © 2013 American Neurological Association.

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Year:  2013        PMID: 23494615      PMCID: PMC3700597          DOI: 10.1002/ana.23879

Source DB:  PubMed          Journal:  Ann Neurol        ISSN: 0364-5134            Impact factor:   10.422


  46 in total

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Authors:  Marko Wilke; Karen Lidzba
Journal:  J Neurosci Methods       Date:  2007-02-14       Impact factor: 2.390

2.  Rehabilitation of reaching and grasping function in severe hemiplegic patients using functional electrical stimulation therapy.

Authors:  T Adam Thrasher; Vera Zivanovic; William McIlroy; Milos R Popovic
Journal:  Neurorehabil Neural Repair       Date:  2008 Nov-Dec       Impact factor: 3.919

Review 3.  Motor recovery after stroke: a systematic review.

Authors:  Peter Langhorne; Fiona Coupar; Alex Pollock
Journal:  Lancet Neurol       Date:  2009-08       Impact factor: 44.182

Review 4.  Plasticity during stroke recovery: from synapse to behaviour.

Authors:  Timothy H Murphy; Dale Corbett
Journal:  Nat Rev Neurosci       Date:  2009-11-04       Impact factor: 34.870

Review 5.  Brain-computer interfaces: communication and restoration of movement in paralysis.

Authors:  Niels Birbaumer; Leonardo G Cohen
Journal:  J Physiol       Date:  2007-01-18       Impact factor: 5.182

6.  Priming the motor system enhances the effects of upper limb therapy in chronic stroke.

Authors:  Cathy M Stinear; P Alan Barber; James P Coxon; Melanie K Fleming; Winston D Byblow
Journal:  Brain       Date:  2008-03-20       Impact factor: 13.501

7.  Hierarchical properties of the motor function sections of the Fugl-Meyer assessment scale for people after stroke: a retrospective study.

Authors:  J Lesley Crow; Barbara C Harmeling-van der Wel
Journal:  Phys Ther       Date:  2008-10-16

Review 8.  Brain-computer interfaces in neurological rehabilitation.

Authors:  Janis J Daly; Jonathan R Wolpaw
Journal:  Lancet Neurol       Date:  2008-10-02       Impact factor: 44.182

9.  Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke.

Authors:  Ethan Buch; Cornelia Weber; Leonardo G Cohen; Christoph Braun; Michael A Dimyan; Tyler Ard; Jurgen Mellinger; Andrea Caria; Surjo Soekadar; Alissa Fourkas; Niels Birbaumer
Journal:  Stroke       Date:  2008-02-07       Impact factor: 7.914

10.  Direct control of paralysed muscles by cortical neurons.

Authors:  Chet T Moritz; Steve I Perlmutter; Eberhard E Fetz
Journal:  Nature       Date:  2008-10-15       Impact factor: 49.962

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  221 in total

1.  Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface.

Authors:  Natalie Mrachacz-Kersting; Ning Jiang; Andrew James Thomas Stevenson; Imran Khan Niazi; Vladimir Kostic; Aleksandra Pavlovic; Sasa Radovanovic; Milica Djuric-Jovicic; Federica Agosta; Kim Dremstrup; Dario Farina
Journal:  J Neurophysiol       Date:  2015-12-30       Impact factor: 2.714

2.  Brain-computer interface: current and emerging rehabilitation applications.

Authors:  Janis J Daly; Jane E Huggins
Journal:  Arch Phys Med Rehabil       Date:  2015-03       Impact factor: 3.966

Review 3.  New Directions in Treatments Targeting Stroke Recovery.

Authors:  David J Lin; Seth P Finklestein; Steven C Cramer
Journal:  Stroke       Date:  2018-12       Impact factor: 7.914

4.  BCI-FES: could a new rehabilitation device hold fresh promise for stroke patients?

Authors:  Brittany M Young; Justin Williams; Vivek Prabhakaran
Journal:  Expert Rev Med Devices       Date:  2014-07-25       Impact factor: 3.166

5.  Brain oscillatory signatures of motor tasks.

Authors:  Ander Ramos-Murguialday; Niels Birbaumer
Journal:  J Neurophysiol       Date:  2015-03-25       Impact factor: 2.714

Review 6.  Physiological properties of brain-machine interface input signals.

Authors:  Marc W Slutzky; Robert D Flint
Journal:  J Neurophysiol       Date:  2017-06-14       Impact factor: 2.714

Review 7.  Closed-loop brain training: the science of neurofeedback.

Authors:  Ranganatha Sitaram; Tomas Ros; Luke Stoeckel; Sven Haller; Frank Scharnowski; Jarrod Lewis-Peacock; Nikolaus Weiskopf; Maria Laura Blefari; Mohit Rana; Ethan Oblak; Niels Birbaumer; James Sulzer
Journal:  Nat Rev Neurosci       Date:  2016-12-22       Impact factor: 34.870

8.  Controlling pre-movement sensorimotor rhythm can improve finger extension after stroke.

Authors:  S L Norman; D J McFarland; A Miner; S C Cramer; E T Wolbrecht; J R Wolpaw; D J Reinkensmeyer
Journal:  J Neural Eng       Date:  2018-07-31       Impact factor: 5.379

9.  The advantages of the surface Laplacian in brain-computer interface research.

Authors:  Dennis J McFarland
Journal:  Int J Psychophysiol       Date:  2014-08-01       Impact factor: 2.997

10.  Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

Authors:  Jane E Huggins; Christoph Guger; Brendan Allison; Charles W Anderson; Aaron Batista; Anne-Marie A-M Brouwer; Clemens Brunner; Ricardo Chavarriaga; Melanie Fried-Oken; Aysegul Gunduz; Disha Gupta; Andrea Kübler; Robert Leeb; Fabien Lotte; Lee E Miller; Gernot Müller-Putz; Tomasz Rutkowski; Michael Tangermann; David Edward Thompson
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2014-01
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