Literature DB >> 30269808

Brain Computer Interfaces in Rehabilitation Medicine.

Marcia A Bockbrader1, Gerard Francisco2, Ray Lee3, Jared Olson4, Ryan Solinsky5, Michael L Boninger6.   

Abstract

One innovation currently influencing physical medicine and rehabilitation is brain-computer interface (BCI) technology. BCI systems used for motor control record neural activity associated with thoughts, perceptions, and motor intent; decode brain signals into commands for output devices; and perform the user's intended action through an output device. BCI systems used for sensory augmentation transduce environmental stimuli into neural signals interpretable by the central nervous system. Both types of systems have potential for reducing disability by facilitating a user's interaction with the environment. Investigational BCI systems are being used in the rehabilitation setting both as neuroprostheses to replace lost function and as potential plasticity-enhancing therapy tools aimed at accelerating neurorecovery. Populations benefitting from motor and somatosensory BCI systems include those with spinal cord injury, motor neuron disease, limb amputation, and stroke. This article discusses the basic components of BCI for rehabilitation, including recording systems and locations, signal processing and translation algorithms, and external devices controlled through BCI commands. An overview of applications in motor and sensory restoration is provided, along with ethical questions and user perspectives regarding BCI technology.
Copyright © 2018 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2018        PMID: 30269808     DOI: 10.1016/j.pmrj.2018.05.028

Source DB:  PubMed          Journal:  PM R        ISSN: 1934-1482            Impact factor:   2.298


  18 in total

1.  Injecting Information into the Mammalian Cortex: Progress, Challenges, and Promise.

Authors:  Kevin A Mazurek; Marc H Schieber
Journal:  Neuroscientist       Date:  2020-07-10       Impact factor: 7.519

2.  How individuals with spinal cord injury in the United States access and assess information about experimental therapies and clinical trials: results of a clinical survey.

Authors:  Clara Farrehi; Carlotta Pazzi; Maclain Capron; Kim Anderson; Bonnie Richardson; Michael Stillman
Journal:  Spinal Cord Ser Cases       Date:  2020-11-23

3.  BCI-FES With Multimodal Feedback for Motor Recovery Poststroke.

Authors:  Alexander B Remsik; Peter L E van Kan; Shawna Gloe; Klevest Gjini; Leroy Williams; Veena Nair; Kristin Caldera; Justin C Williams; Vivek Prabhakaran
Journal:  Front Hum Neurosci       Date:  2022-07-06       Impact factor: 3.473

4.  Concerns in the Blurred Divisions between Medical and Consumer Neurotechnology.

Authors:  Andrew Y Paek; Justin A Brantley; Barbara J Evans; Jose L Contreras-Vidal
Journal:  IEEE Syst J       Date:  2020-12-18       Impact factor: 4.802

5.  An Assessment of Which Sociodemographic and Spinal Cord Injury-Specific Characteristics Influence Engagement With Experimental Therapies and Participation in Clinical Trials.

Authors:  Carlotta Pazzi; Clara Farrehi; Maclain Capron; Kim Anderson; Bonnie Richardson; Michael Stillman
Journal:  Top Spinal Cord Inj Rehabil       Date:  2021-11-17

6.  Electrocorticogram (ECoG) Is Highly Informative in Primate Visual Cortex.

Authors:  Sidrat Tasawoor Kanth; Supratim Ray
Journal:  J Neurosci       Date:  2020-02-17       Impact factor: 6.167

7.  Brain-Computer Interfaces in Neurorecovery and Neurorehabilitation.

Authors:  Michael J Young; David J Lin; Leigh R Hochberg
Journal:  Semin Neurol       Date:  2021-03-19       Impact factor: 3.212

8.  Weighted Brain Network Metrics for Decoding Action Intention Understanding Based on EEG.

Authors:  Xingliang Xiong; Zhenhua Yu; Tian Ma; Ning Luo; Haixian Wang; Xuesong Lu; Hui Fan
Journal:  Front Hum Neurosci       Date:  2020-07-02       Impact factor: 3.169

9.  A Comprehensive sLORETA Study on the Contribution of Cortical Somatomotor Regions to Motor Imagery.

Authors:  Mustafa Yazici; Mustafa Ulutas; Mukadder Okuyan
Journal:  Brain Sci       Date:  2019-12-13

Review 10.  Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces.

Authors:  Roberto Portillo-Lara; Bogachan Tahirbegi; Christopher A R Chapman; Josef A Goding; Rylie A Green
Journal:  APL Bioeng       Date:  2021-07-20
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