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

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

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

http://www.wikidata.org/entity/Q36979996

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Computational neurorehabilitation: modeling plasticity and learning to predict recovery Magnetoencephalography in Stroke Recovery and Rehabilitation A Review of Techniques for Detection of Movement Intention Using Movement-Related Cortical Potentials Upper Limb Immobilisation: A Neural Plasticity Model with Relevance to Poststroke Motor Rehabilitation Current Challenges Facing the Translation of Brain Computer Interfaces from Preclinical Trials to Use in Human Patients Neurophysiology of robot-mediated training and therapy: a perspective for future use in clinical populations Control of an Ambulatory Exoskeleton with a Brain-Machine Interface for Spinal Cord Injury Gait Rehabilitation Common neural correlates of real and imagined movements contributing to the performance of brain-machine interfaces Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia Brain Computer Interface on Track to Home Combinations of stroke neurorehabilitation to facilitate motor recovery: perspectives on Hebbian plasticity and homeostatic metaplasticity Brain state-dependent robotic reaching movement with a multi-joint arm exoskeleton: combining brain-machine interfacing and robotic rehabilitation Movement Anticipation and EEG: Implications for BCI-Contingent Robot Therapy.Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.Kinematic and neurophysiological consequences of an assisted-force-feedback brain-machine interface training: a case study.Case report: post-stroke interventional BCI rehabilitation in an individual with preexisting sensorineural disability.Movement related slow cortical potentials in severely paralyzed chronic stroke patients Combined Action Observation and Motor Imagery Neurofeedback for Modulation of Brain Activity.Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task.Contralesional Brain-Computer Interface Control of a Powered Exoskeleton for Motor Recovery in Chronic Stroke Survivors.Changes in functional connectivity correlate with behavioral gains in stroke patients after therapy using a brain-computer interface device Changes in functional brain organization and behavioral correlations after rehabilitative therapy using a brain-computer interface Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke.Applications of Brain-Machine Interface Systems in Stroke Recovery and Rehabilitation.Functional recovery from chronic writer's cramp by brain-computer interface rehabilitation: a case report.Cortex integrity relevance in muscle synergies in severe chronic stroke.BCI-FES: could a new rehabilitation device hold fresh promise for stroke patients?A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke.Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation.Continuous decoding of movement intention of upper limb self-initiated analytic movements from pre-movement EEG correlates.The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications.Learned self-regulation of the lesioned brain with epidural electrocorticography Decoding upper limb residual muscle activity in severe chronic stroke.The advantages of the surface Laplacian in brain-computer interface research.Reinforcement learning for adaptive threshold control of restorative brain-computer interfaces: a Bayesian simulation.Estimating cognitive load during self-regulation of brain activity and neurofeedback with therapeutic brain-computer interfaces Brain self-regulation in criminal psychopaths Brain-computer interface: current and emerging rehabilitation applications EEG classification of different imaginary movements within the same limb Brain computer interface learning for systems based on electrocorticography and intracortical microelectrode arrays

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

http://www.wikidata.org/entity/Q36979996

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

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

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

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Annals of Neurology

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

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Alexandros Vyziotis

http://www.w3.org/2001/XMLSchema#string

Andrea Caria

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Doris Broetz

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Eliana Garcia-Cossio

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Ernesto Soares

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Leonardo G Cohen

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Leonhard Läer

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Manuel Agostini

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Marco R Curado

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Massimiliano Rea

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P2860

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.

Neural basis of reinforcement learning and decision making

The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance

Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial

Reward improves long-term retention of a motor memory through induction of offline memory gains

Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills

Hierarchical Properties of the Motor Function Sections of the Fugl-Meyer Assessment Scale for People After Stroke: A Retrospective Study

A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task.

High-performance neuroprosthetic control by an individual with tetraplegia.

Stroke rehabilitation.

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100-108

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scholarly article

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10.1002/ANA.23879

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1

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74

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Niels Birbaumer

Fabrício Lima Brasil

Ander Ramos-Murguialday

Giulia Liberati

P577

2013-07-01T00:00:00Z

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P698

23494615

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3700597

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