Poststroke Motor, Cognitive and Speech Rehabilitation with Brain-computer Interface: a Perspective Review

Overview

Journal Stroke Vasc Neurol

Specialty Cardiology & Vascular Diseases

Date 2022 Jul 19

PMID 35853669

Authors

Ravikiran Mane

Zhenzhou Wu

David Wang

Affiliations

Soon will be listed here.

Abstract

Brain-computer interface (BCI) technology translates brain activity into meaningful commands to establish a direct connection between the brain and the external world. Neuroscientific research in the past two decades has indicated a tremendous potential of BCI systems for the rehabilitation of patients suffering from poststroke impairments. By promoting the neuronal recovery of the damaged brain networks, BCI systems have achieved promising results for the recovery of poststroke motor, cognitive, and language impairments. Also, several assistive BCI systems that provide alternative means of communication and control to severely paralysed patients have been proposed to enhance patients' quality of life. In this article, we present a perspective review of the recent advances and challenges in the BCI systems used in the poststroke rehabilitation of motor, cognitive, and communication impairments.

Citing Articles

Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis.

Liu M, Fang M, Liu M, Jin S, Liu B, Wu L Front Hum Neurosci. 2024; 18:1486167.

PMID: 39539351 PMC: 11557533. DOI: 10.3389/fnhum.2024.1486167.

Brain-computer Interaction in the Smart Era.

Yan Z, Liu P, Zhou H, Zhang J, Liu S, Xie Y Curr Med Sci. 2024; 44(6):1123-1131.

PMID: 39347924 DOI: 10.1007/s11596-024-2927-6.

[A review of functional electrical stimulation based on brain-computer interface].

Wang Y, Li Y, Cui H, Li M, Chen X Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024; 41(4):650-655.

PMID: 39218589 PMC: 11366473. DOI: 10.7507/1001-5515.202311036.

Peripheral nerve transfers for dysfunctions in central nervous system injuries: a systematic review.

Xiang Y, Wu J, Ma J, Xing X, Zhang J, Hua X Int J Surg. 2024; 110(6):3814-3826.

PMID: 38935818 PMC: 11175768. DOI: 10.1097/JS9.0000000000001267.

Advancements in brain-computer interfaces for the rehabilitation of unilateral spatial neglect: a concise review.

Gouret A, Le Bars S, Porssut T, Waszak F, Chokron S Front Neurosci. 2024; 18:1373377.

PMID: 38784094 PMC: 11111994. DOI: 10.3389/fnins.2024.1373377.

References

Cervera M, Soekadar S, Ushiba J, Millan J, Liu M, Birbaumer N . Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis. Ann Clin Transl Neurol. 2018; 5(5):651-663. PMC: 5945970. DOI: 10.1002/acn3.544. View

Mane R, Chew E, Phua K, Ang K, Robinson N, Vinod A . Prognostic and Monitory EEG-Biomarkers for BCI Upper-Limb Stroke Rehabilitation. IEEE Trans Neural Syst Rehabil Eng. 2019; 27(8):1654-1664. DOI: 10.1109/TNSRE.2019.2924742. View

Chaudhary U, Birbaumer N, Ramos-Murguialday A . Brain-computer interfaces in the completely locked-in state and chronic stroke. Prog Brain Res. 2016; 228:131-61. DOI: 10.1016/bs.pbr.2016.04.019. View

Mrachacz-Kersting N, Ibanez J, Farina D . Towards a mechanistic approach for the development of non-invasive brain-computer interfaces for motor rehabilitation. J Physiol. 2021; 599(9):2361-2374. DOI: 10.1113/JP281314. View

Mihara M, Hattori N, Hatakenaka M, Yagura H, Kawano T, Hino T . Near-infrared spectroscopy-mediated neurofeedback enhances efficacy of motor imagery-based training in poststroke victims: a pilot study. Stroke. 2013; 44(4):1091-8. DOI: 10.1161/STROKEAHA.111.674507. View

Lefaucheur J, Aleman A, Baeken C, Benninger D, Brunelin J, Di Lazzaro V . Evidence-based guidelines on the therapeutic use of repetitive transcranial magnetic stimulation (rTMS): An update (2014-2018). Clin Neurophysiol. 2020; 131(2):474-528. DOI: 10.1016/j.clinph.2019.11.002. View

Sellers E, Ryan D, Hauser C . Noninvasive brain-computer interface enables communication after brainstem stroke. Sci Transl Med. 2014; 6(257):257re7. PMC: 4711808. DOI: 10.1126/scitranslmed.3007801. View

Barsi G, Popovic D, Tarkka I, Sinkjaer T, Grey M . Cortical excitability changes following grasping exercise augmented with electrical stimulation. Exp Brain Res. 2008; 191(1):57-66. DOI: 10.1007/s00221-008-1495-5. View

Muller-Putz G, Pfurtscheller G . Control of an electrical prosthesis with an SSVEP-based BCI. IEEE Trans Biomed Eng. 2008; 55(1):361-4. DOI: 10.1109/TBME.2007.897815. View

10.

Mrachacz-Kersting N, Jiang N, Stevenson A, Niazi I, Kostic V, Pavlovic A . Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface. J Neurophysiol. 2016; 115(3):1410-21. PMC: 4808132. DOI: 10.1152/jn.00918.2015. View

11.

Renton T, Tibbles A, Topolovec-Vranic J . Neurofeedback as a form of cognitive rehabilitation therapy following stroke: A systematic review. PLoS One. 2017; 12(5):e0177290. PMC: 5433697. DOI: 10.1371/journal.pone.0177290. View

12.

Musk E . An Integrated Brain-Machine Interface Platform With Thousands of Channels. J Med Internet Res. 2019; 21(10):e16194. PMC: 6914248. DOI: 10.2196/16194. View

13.

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

14.

Jang Y, Kim T, Lee B . Effects of Brain-Computer Interface-controlled Functional Electrical Stimulation Training on Shoulder Subluxation for Patients with Stroke: A Randomized Controlled Trial. Occup Ther Int. 2016; 23(2):175-85. DOI: 10.1002/oti.1422. View

15.

He S, Zhang R, Wang Q, Chen Y, Yang T, Feng Z . A P300-Based Threshold-Free Brain Switch and Its Application in Wheelchair Control. IEEE Trans Neural Syst Rehabil Eng. 2016; 25(6):715-725. DOI: 10.1109/TNSRE.2016.2591012. View

16.

Nojima I, Sugata H, Takeuchi H, Mima T . Brain-Computer Interface Training Based on Brain Activity Can Induce Motor Recovery in Patients With Stroke: A Meta-Analysis. Neurorehabil Neural Repair. 2021; 36(2):83-96. DOI: 10.1177/15459683211062895. View

17.

Nicoll R . A Brief History of Long-Term Potentiation. Neuron. 2017; 93(2):281-290. DOI: 10.1016/j.neuron.2016.12.015. View

18.

Mane R, Chouhan T, Guan C . BCI for stroke rehabilitation: motor and beyond. J Neural Eng. 2020; 17(4):041001. DOI: 10.1088/1741-2552/aba162. View

19.

Bundy D, Souders L, Baranyai K, Leonard L, Schalk G, Coker R . Contralesional Brain-Computer Interface Control of a Powered Exoskeleton for Motor Recovery in Chronic Stroke Survivors. Stroke. 2017; 48(7):1908-1915. PMC: 5482564. DOI: 10.1161/STROKEAHA.116.016304. View

20.

Chung E, Park S, Jang Y, Lee B . Effects of brain-computer interface-based functional electrical stimulation on balance and gait function in patients with stroke: preliminary results. J Phys Ther Sci. 2015; 27(2):513-6. PMC: 4339175. DOI: 10.1589/jpts.27.513. View