Literature DB >> 25623294

Brain-machine interface (BMI) in paralysis.

U Chaudhary1, N Birbaumer2, M R Curado3.   

Abstract

INTRODUCTION: Brain-machine interfaces (BMIs) use brain activity to control external devices, facilitating paralyzed patients to interact with the environment. In this review, we focus on the current advances of non-invasive BMIs for communication in patients with amyotrophic lateral sclerosis (ALS) and for restoration of motor impairment after severe stroke. BMI FOR ALS PATIENTS: BMI represents a promising strategy to establish communication with paralyzed ALS patients as it does not need muscle engagement for its use. Distinct techniques have been explored to assess brain neurophysiology to control BMI for patients' communication, especially electroencephalography (EEG) and more recently near-infrared spectroscopy (NIRS). Previous studies demonstrated successful communication with ALS patients using EEG-BMI when patients still showed residual eye control, but patients with complete paralysis were unable to communicate with this system. We recently introduced functional NIRS (fNIRS)-BMI for communication in ALS patients in the complete locked-in syndrome (i.e., when ALS patients are unable to engage any muscle), opening new doors for communication in ALS patients after complete paralysis. BMI FOR STROKE MOTOR RECOVERY: In addition to assisted communication, BMI is also being extensively studied for motor recovery after stroke. BMI for stroke motor recovery includes intensive BMI training linking brain activity related to patient's intention to move the paretic limb with the contingent sensory feedback of the paretic limb movement guided by assistive devices. BMI studies in this area are mainly focused on EEG- or magnetoencephalography (MEG)-BMI systems due to their high temporal resolution, which facilitates online contingency between intention to move and sensory feedback of the intended movement. EEG-BMI training was recently demonstrated in a controlled study to significantly improve motor performance in stroke patients with severe paresis. Neural basis for BMI-induced restoration of motor function and perspectives for future BMI research for stroke motor recovery are discussed.
Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  ALS; Amyotrophic lateral sclerosis; BCI; BMI; Brain computer interface; Brain machine interface; Stroke

Mesh:

Year:  2015        PMID: 25623294     DOI: 10.1016/j.rehab.2014.11.002

Source DB:  PubMed          Journal:  Ann Phys Rehabil Med        ISSN: 1877-0657


  28 in total

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Authors:  Ujwal Chaudhary; Niels Birbaumer; Ander Ramos-Murguialday
Journal:  Nat Rev Neurol       Date:  2016-08-19       Impact factor: 42.937

2.  Decoding different working memory states during an operation span task from prefrontal fNIRS signals.

Authors:  Ting Chen; Cui Zhao; Xingyu Pan; Junda Qu; Jing Wei; Chunlin Li; Ying Liang; Xu Zhang
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3.  Correction of motion artifacts and serial correlations for real-time functional near-infrared spectroscopy.

Authors:  Jeffrey W Barker; Andrea L Rosso; Patrick J Sparto; Theodore J Huppert
Journal:  Neurophotonics       Date:  2016-05-23       Impact factor: 3.593

4.  Combined real-time fMRI and real time fNIRS brain computer interface (BCI): Training of volitional wrist extension after stroke, a case series pilot study.

Authors:  Avi K Matarasso; Jake D Rieke; Keith White; M Minhal Yusufali; Janis J Daly
Journal:  PLoS One       Date:  2021-05-06       Impact factor: 3.240

5.  Brain-Computer Interface-Based Communication in the Completely Locked-In State.

Authors:  Ujwal Chaudhary; Bin Xia; Stefano Silvoni; Leonardo G Cohen; Niels Birbaumer
Journal:  PLoS Biol       Date:  2017-01-31       Impact factor: 8.029

6.  Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: three-class classification of rest, right-, and left-hand motor execution.

Authors:  Thanawin Trakoolwilaiwan; Bahareh Behboodi; Jaeseok Lee; Kyungsoo Kim; Ji-Woong Choi
Journal:  Neurophotonics       Date:  2017-09-14       Impact factor: 3.593

Review 7.  Simultaneous functional near-infrared spectroscopy and electroencephalography for monitoring of human brain activity and oxygenation: a review.

Authors:  Antonio M Chiarelli; Filippo Zappasodi; Francesco Di Pompeo; Arcangelo Merla
Journal:  Neurophotonics       Date:  2017-08-22       Impact factor: 3.593

8.  Effects of Light and Sound on the Prefrontal Cortex Activation and Emotional Function: A Functional Near-Infrared Spectroscopy Study.

Authors:  Shota Hori; Koichi Mori; Takehisa Mashimo; Akitoshi Seiyama
Journal:  Front Neurosci       Date:  2017-06-09       Impact factor: 4.677

9.  EEG power spectral density in locked-in and completely locked-in state patients: a longitudinal study.

Authors:  Arianna Secco; Alessandro Tonin; Aygul Rana; Andres Jaramillo-Gonzalez; Majid Khalili-Ardali; Niels Birbaumer; Ujwal Chaudhary
Journal:  Cogn Neurodyn       Date:  2020-10-23       Impact factor: 5.082

Review 10.  Neural Substrate Expansion for the Restoration of Brain Function.

Authors:  H Isaac Chen; Dennis Jgamadze; Mijail D Serruya; D Kacy Cullen; John A Wolf; Douglas H Smith
Journal:  Front Syst Neurosci       Date:  2016-01-25
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