Literature DB >> 30056435

Brain-machine interfaces for rehabilitation in stroke: A review.

E López-Larraz1, A Sarasola-Sanz1,2,3, N Irastorza-Landa1,2,4, N Birbaumer1,5, A Ramos-Murguialday1,3.   

Abstract

BACKGROUND: Motor paralysis after stroke has devastating consequences for the patients, families and caregivers. Although therapies have improved in the recent years, traditional rehabilitation still fails in patients with severe paralysis. Brain-machine interfaces (BMI) have emerged as a promising tool to guide motor rehabilitation interventions as they can be applied to patients with no residual movement.
OBJECTIVE: This paper reviews the efficiency of BMI technologies to facilitate neuroplasticity and motor recovery after stroke.
METHODS: We provide an overview of the existing rehabilitation therapies for stroke, the rationale behind the use of BMIs for motor rehabilitation, the current state of the art and the results achieved so far with BMI-based interventions, as well as the future perspectives of neural-machine interfaces.
RESULTS: Since the first pilot study by Buch and colleagues in 2008, several controlled clinical studies have been conducted, demonstrating the efficacy of BMIs to facilitate functional recovery in completely paralyzed stroke patients with noninvasive technologies such as the electroencephalogram (EEG).
CONCLUSIONS: Despite encouraging results, motor rehabilitation based on BMIs is still in a preliminary stage, and further improvements are required to boost its efficacy. Invasive and hybrid approaches are promising and might set the stage for the next generation of stroke rehabilitation therapies.

Entities:  

Keywords:  Brain-machine interfaces (BMI); motor recovery; neuroplasticity; rehabilitation; stroke

Mesh:

Year:  2018        PMID: 30056435     DOI: 10.3233/NRE-172394

Source DB:  PubMed          Journal:  NeuroRehabilitation        ISSN: 1053-8135            Impact factor:   2.138


  16 in total

Review 1.  The science and engineering behind sensitized brain-controlled bionic hands.

Authors:  Chethan Pandarinath; Sliman J Bensmaia
Journal:  Physiol Rev       Date:  2021-09-20       Impact factor: 37.312

Review 2.  Pathological changes of brain oscillations following ischemic stroke.

Authors:  Yoshimichi Sato; Oliver Schmitt; Zachary Ip; Gratianne Rabiller; Shunsuke Omodaka; Teiji Tominaga; Azadeh Yazdan-Shahmorad; Jialing Liu
Journal:  J Cereb Blood Flow Metab       Date:  2022-06-25       Impact factor: 6.960

3.  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

4.  Longitudinal Electroencephalography Analysis in Subacute Stroke Patients During Intervention of Brain-Computer Interface With Exoskeleton Feedback.

Authors:  Shugeng Chen; Lei Cao; Xiaokang Shu; Hewei Wang; Li Ding; Shui-Hua Wang; Jie Jia
Journal:  Front Neurosci       Date:  2020-08-14       Impact factor: 4.677

5.  Event-related desynchronization during movement attempt and execution in severely paralyzed stroke patients: An artifact removal relevance analysis.

Authors:  Eduardo López-Larraz; Thiago C Figueiredo; Ainhoa Insausti-Delgado; Ulf Ziemann; Niels Birbaumer; Ander Ramos-Murguialday
Journal:  Neuroimage Clin       Date:  2018-10-04       Impact factor: 4.881

6.  Design and effectiveness evaluation of mirror myoelectric interfaces: a novel method to restore movement in hemiplegic patients.

Authors:  Andrea Sarasola-Sanz; Nerea Irastorza-Landa; Eduardo López-Larraz; Farid Shiman; Martin Spüler; Niels Birbaumer; Ander Ramos-Murguialday
Journal:  Sci Rep       Date:  2018-11-12       Impact factor: 4.379

7.  Optimization of Surface Electromyography-Based Neurofeedback Rehabilitation Intervention System.

Authors:  Wenlin Sun; Yujun Qi; Yang Sun; Tiantian Zhao; Xiaoyong Su; Yang Liu
Journal:  J Healthc Eng       Date:  2021-03-17       Impact factor: 2.682

8.  Effects of a Brain-Computer Interface-Operated Lower Limb Rehabilitation Robot on Motor Function Recovery in Patients with Stroke.

Authors:  Chao Li; Jinyu Wei; Xiaoqun Huang; Qiang Duan; Tingting Zhang
Journal:  J Healthc Eng       Date:  2021-12-20       Impact factor: 2.682

Review 9.  Challenges and Opportunities for the Future of Brain-Computer Interface in Neurorehabilitation.

Authors:  Colin Simon; David A E Bolton; Niamh C Kennedy; Surjo R Soekadar; Kathy L Ruddy
Journal:  Front Neurosci       Date:  2021-07-02       Impact factor: 4.677

10.  On the design of EEG-based movement decoders for completely paralyzed stroke patients.

Authors:  Martin Spüler; Eduardo López-Larraz; Ander Ramos-Murguialday
Journal:  J Neuroeng Rehabil       Date:  2018-11-20       Impact factor: 4.262

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