Brain–Machine Interfaces in Stroke Neurorehabilitation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Surjo R. Soekadar , Stefano Silvoni , Leonardo G. Cohen , Niels Birbaumer

ABSTRACT

Stroke is one of the leading causes for severe adult long-term disability. The number of people who depend on assistance in their daily life activities has drastically increased over the last years and will further accumulate due to demographic factors. Besides impact on cognitive and affective brain function, motor paralysis is the heaviest burden of stroke. While recent studies demonstrated the human brain’s remarkable capacity to reorganize and restore function under effective learning conditions, most rehabilitation strategies require residual movements that, however, are lacking in up to 30–50 % of stroke survivors. For these patients, there is currently no standardized or accepted treatment strategy. Recently it was shown that brain–machine interfaces (BMI) translating electric or metabolic brain signals into control signals of computers or machines provide two strategies that play an increasing role for the recovery of these stroke survivors’ motor function: first, assistive BMIs striving for continuous high-dimensional brain control of robotic devices or functional electric stimulation (FES) to assist in performing daily life activities and, second, rehabilitative BMIs aiming at augmentation of neuroplasticity facilitating recovery of brain function. Recent demonstrations of such assistive and rehabilitative BMI system’s clinical applicability, safety, and efficacy suggest that BMIs will play a substantial role in rehabilitation strategies for severe motor paralysis after stroke. More... »

PAGES

3-14

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  • Book

    TITLE

    Clinical Systems Neuroscience

    ISBN

    978-4-431-55036-5
    978-4-431-55037-2

    From Grant

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-4-431-55037-2_1

    DOI

    http://dx.doi.org/10.1007/978-4-431-55037-2_1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1005622601


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