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Brain Computer Interface Treatment for Motor Rehabilitation of Upper Extremity of Stroke Patients-A Feasibility Study

Overview
Journal Front Neurosci
Date 2020 Nov 16
PMID 33192277
Citations 35
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Abstract

Introduction: Numerous recent publications have explored Brain Computer Interfaces (BCI) systems as rehabilitation tools to help subacute and chronic stroke patients recover upper extremity movement. Recent work has shown that BCI therapy can lead to better outcomes than conventional therapy. BCI combined with other techniques such as Functional Electrical Stimulation (FES) and Virtual Reality (VR) allows to the user restore the neurological function by inducing the neural plasticity through improved real-time detection of motor imagery (MI) as patients perform therapy tasks.

Methods: Fifty-one stroke patients with upper extremity hemiparesis were recruited for this study. All participants performed 25 sessions with the MI BCI and assessment visits to track the functional changes before and after the therapy.

Results: The results of this study demonstrated a significant increase in the motor function of the paretic arm assessed by Fugl-Meyer Assessment (FMA-UE), ΔFMA-UE = 4.68 points, < 0.001, reduction of the spasticity in the wrist and fingers assessed by Modified Ashworth Scale (MAS), ΔMAS-wrist = -0.72 points ( = 0.83), < 0.001, ΔMAS-fingers = -0.63 points ( = 0.82), < 0.001. Other significant improvements in the grasp ability were detected in the healthy hand. All these functional improvements achieved during the BCI therapy persisted 6 months after the therapy ended. Results also showed that patients with Motor Imagery accuracy (MI) above 80% increase 3.16 points more in the FMA than patients below this threshold (95% CI; [1.47-6.62], = 0.003). The functional improvement was not related with the stroke severity or with the stroke stage.

Conclusion: The BCI treatment used here was effective in promoting long lasting functional improvements in the upper extremity in stroke survivors with severe, moderate and mild impairment. This functional improvement can be explained by improved neuroplasticity in the central nervous system.

Citing Articles

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Virtual Reality Enhanced Exercise Training in Upper Limb Function of Patients With Stroke: Meta-Analytic Study.

Xu S, Xu Y, Wen R, Wang J, Qiu Y, Chan C J Med Internet Res. 2025; 27:e66802.

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Brain-Computer Interfaces for Upper Limb Motor Recovery after Stroke: Current Status and Development Prospects (Review).

Mokienko O, Lyukmanov R, Bobrov P, Suponeva N, Piradov M Sovrem Tekhnologii Med. 2025; 15(6):63-73.

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Efficacy of brain-computer interface training with motor imagery-contingent feedback in improving upper limb function and neuroplasticity among persons with chronic stroke: a double-blinded, parallel-group, randomized controlled trial.

Kim M, Park H, Kwon I, An K, Kim H, Park G J Neuroeng Rehabil. 2025; 22(1):1.

PMID: 39757218 PMC: 11702034. DOI: 10.1186/s12984-024-01535-2.


Electroencephalography-Based Brain-Computer Interfaces in Rehabilitation: A Bibliometric Analysis (2013-2023).

Angulo Medina A, Aguilar Bonilla M, Rodriguez Giraldo I, Montenegro Palacios J, Caceres Gutierrez D, Liscano Y Sensors (Basel). 2024; 24(22).

PMID: 39598903 PMC: 11598414. DOI: 10.3390/s24227125.


References
1.
Ang K, Guan C, Phua K, Wang C, Zhou L, Tang K . Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke. Front Neuroeng. 2014; 7:30. PMC: 4114185. DOI: 10.3389/fneng.2014.00030. View

2.
Prabhakaran S, Zarahn E, Riley C, Speizer A, Chong J, Lazar R . Inter-individual variability in the capacity for motor recovery after ischemic stroke. Neurorehabil Neural Repair. 2007; 22(1):64-71. DOI: 10.1177/1545968307305302. View

3.
Peng Y, Liu J, Hua M, Liang M, Yu C . Enhanced Effective Connectivity From Ipsilesional to Contralesional M1 in Well-Recovered Subcortical Stroke Patients. Front Neurol. 2019; 10:909. PMC: 6736556. DOI: 10.3389/fneur.2019.00909. View

4.
Irimia D, Sabathiel N, Ortner R, Poboroniuc M, Coon W, Allison B . recoveriX: a new BCI-based technology for persons with stroke. Annu Int Conf IEEE Eng Med Biol Soc. 2017; 2016:1504-1507. DOI: 10.1109/EMBC.2016.7590995. View

5.
Correa-Agudelo E, Ferrin C, Velez P, Gomez J . Computer Imagery and Neurological Rehabilitation: On the Use of Augmented Reality in Sensorimotor Training to Step Up Naturally Occurring Cortical Reorganization in Patients Following Stroke. Stud Health Technol Inform. 2016; 220:71-6. View