Feigin VL, Forouzanfar MH, Krishnamurthi R, Mensah GA, Connor M, Bennett DA, Moran AE, Sacco RL, Anderson L, Truelsen T, et al. Global and regional burden of stroke during 1990-2010: findings from the global burden of disease study 2010. Lancet. 2014;383(9913):245–54.
Article
PubMed
PubMed Central
Google Scholar
Mackay-Lyons MJ, Makrides L. Longitudinal changes in exercise capacity after stroke. Arch Phys Med Rehabil. 2004;85(10):1608–12.
Article
PubMed
Google Scholar
Kim T, Kim S, Lee B. Effects of action observational training plus brain-computer Interface-based functional electrical stimulation on paretic arm motor recovery in patient with stroke: a randomized controlled trial. Occup Ther Int. 2016;23(1):39–47.
Article
PubMed
Google Scholar
Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain-computer interfaces for communication and control. Clin Neurophysiol. 2002;113(6):767–91.
Article
PubMed
Google Scholar
Guger C, Allison B, Lebedev M. Brain-computer interface research : a state-of-the-art summary 6. In: Springer Briefs in electrical and computer engineering. Cham, Switzerland: Springer; 2017. 1 online resource.
Google Scholar
Dickstein R, Deutsch JE: Motor imagery in physical therapist practice. Phys Ther. 2007;87(7):942–53. https://doi.org/10.2522/ptj.20060331. Epub 2007 May 1.
Decety J. The neurophysiological basis of motor imagery. Behav Brain Res. 1996;77(1–2):45–52.
Article
CAS
PubMed
Google Scholar
Solodkin A, Hlustik P, Chen EE, Small SL. Fine modulation in network activation during motor execution and motor imagery. Cereb Cortex. 2004;14(11):1246–55.
Article
PubMed
Google Scholar
Braun S, Kleynen M, van Heel T, Kruithof N, Wade D, Beurskens A. The effect of mental practice in neurlogical rehabilitation: a systematic review and meta-analysis. Front Hum Neurosci. 2013;7:390.
Article
PubMed
PubMed Central
Google Scholar
Guerra ZF, Lucchetti ALG, Lucchetti G. Motor imagery training after stroke: a systematic review and meta-analysis of randomized controlled trials. J Neurol Phys Ther. 2017;41(4):205–14.
Article
PubMed
Google Scholar
Monge-Pereira E, Molina-Rueda F, Rivas-Montero FM, Ibanez J, Serrano JI, Alguacil-Diego IM, Miangolarra-Page JC. Electroencephalography as a post-stroke assessment method: an updated review. Neurologia. 2017;32(1):40–9.
Article
CAS
PubMed
Google Scholar
Carvalho R, Dias N, Cerqueira JJ. Brain-machine interface of upper limb recovery in stroke patients rehabilitation: a systematic review. Physiother Res Int. 2019;24(2):e1764.
Article
PubMed
Google Scholar
Cervera MA, Soekadar SR, Ushiba J, Millan JDR, Liu M, Birbaumer N, Garipelli G. Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis. Ann Clin Transl Neurol. 2018;5(5):651–63.
Article
PubMed
PubMed Central
Google Scholar
Ang KK, Chua KS, Phua KS, Wang C, Chin ZY, Kuah CW, Low W, Guan C. A randomized controlled trial of EEG-based motor imagery brain-computer interface robotic rehabilitation for stroke. Clin EEG Neurosci. 2015;46(4):310–20.
Article
PubMed
Google Scholar
Ang KK, Guan C. EEG-based strategies to detect motor imagery for control and rehabilitation. IEEE Trans Neural Syst Rehabil Eng. 2017;25(4):392–401.
Article
PubMed
Google Scholar
Ang KK, Guan C, Chua KS, Ang BT, Kuah C, Wang C, Phua KS, Chin ZY, Zhang H. Clinical study of neurorehabilitation in stroke using EEG-based motor imagery brain-computer interface with robotic feedback. Conf Proc IEEE Eng Med Biol Soc. 2010;2010:5549–52.
Google Scholar
Ang KK, Guan C, Phua KS, Wang C, Teh I, Chen CW, Chew E. Transcranial direct current stimulation and EEG-based motor imagery BCI for upper limb stroke rehabilitation. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:4128–31.
Google Scholar
Ang KK, Guan C, Phua KS, Wang C, Zhou L, Tang KY, Ephraim Joseph GJ, Kuah CW, Chua KS. 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.
Article
PubMed
PubMed Central
Google Scholar
Biasiucci A, Leeb R, Iturrate I, Perdikis S, Al-Khodairy A, Corbet T, Schnider A, Schmidlin T, Zhang H, Bassolino M, et al. Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke. Nat Commun. 2018;9(1):2421.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chung E, Kim JH, Park DS, Lee BH. Effects of brain-computer interface-based functional electrical stimulation on brain activation in stroke patients: a pilot randomized controlled trial. J Phys Ther Sci. 2015;27(3):559–62.
Article
PubMed
PubMed Central
Google Scholar
Chung E, Park SI, Jang YY, Lee BH. 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.
Article
PubMed
PubMed Central
Google Scholar
Curado MR, Cossio EG, Broetz D, Agostini M, Cho W, Brasil FL, Yilmaz O, Liberati G, Lepski G, Birbaumer N, et al. Residual upper arm motor function primes innervation of paretic forearm muscles in chronic stroke after brain-machine Interface (BMI) training. PLoS One. 2015;10(10):e0140161.
Article
PubMed
PubMed Central
CAS
Google Scholar
Frolov AA, Mokienko O, Lyukmanov R, Biryukova E, Kotov S, Turbina L, Nadareyshvily G, Bushkova Y. Post-stroke rehabilitation training with a motor-imagery-based brain-computer Interface (BCI)-controlled hand exoskeleton: a randomized controlled multicenter trial. Front Neurosci. 2017;11:400.
Article
PubMed
PubMed Central
Google Scholar
Jang YY, Kim TH, Lee BH. 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.
Article
PubMed
Google Scholar
Mrachacz-Kersting N, Jiang N, Stevenson AJ, Niazi IK, Kostic V, Pavlovic A, Radovanovic S, Djuric-Jovicic M, Agosta F, Dremstrup K, et al. Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface. J Neurophysiol. 2016;115(3):1410–21.
Article
PubMed
Google Scholar
Pichiorri F, Morone G, Petti M, Toppi J, Pisotta I, Molinari M, Paolucci S, Inghilleri M, Astolfi L, Cincotti F, et al. Brain-computer interface boosts motor imagery practice during stroke recovery. Ann Neurol. 2015;77(5):851–65.
Article
PubMed
Google Scholar
Ramos-Murguialday A, Broetz D, Rea M, Laer L, Yilmaz O, Brasil FL, Liberati G, Curado MR, Garcia-Cossio E, Vyziotis A, et al. Brain-machine interface in chronic stroke rehabilitation: a controlled study. Ann Neurol. 2013;74(1):100–8.
Article
PubMed
PubMed Central
Google Scholar
Varkuti B, Guan C, Pan Y, Phua KS, Ang KK, Kuah CW, Chua K, Ang BT, Birbaumer N, Sitaram R. Resting state changes in functional connectivity correlate with movement recovery for BCI and robot-assisted upper-extremity training after stroke. Neurorehabil Neural Repair. 2013;27(1):53–62.
Article
PubMed
Google Scholar
Monge-Pereira E, Ibanez-Pereda J, Alguacil-Diego IM, Serrano JI, Spottorno-Rubio MP, Molina-Rueda F. Use of electroencephalography brain-computer interface systems as a rehabilitative approach for upper limb function after a stroke: a systematic review. PM R. 2017;9(9):918–32.
Article
PubMed
Google Scholar
Orrison WW, Lewine J, Sanders J, Hartshorne MF. Functional brain imaging. St. Louis: Elsevier health sciences; 1995.
Rondina JM, Filippone M, Girolami M, Ward NS. Decoding post-stroke motor function from structural brain imaging. NeuroImage Clin. 2016;12:372–80.
Article
PubMed
PubMed Central
Google Scholar
Schulz R, Braass H, Liuzzi G, Hoerniss V, Lechner P, Gerloff C, Hummel FC. White matter integrity of premotor-motor connections is associated with motor output in chronic stroke patients. NeuroImage Clin. 2015;7:82–6.
Article
PubMed
Google Scholar
Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA, Group P-P. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. 2015;350:g7647.
Article
PubMed
Google Scholar
Moher D, Liberati A, Tetzlaff J, Altman DG, The PG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.
Article
PubMed
PubMed Central
Google Scholar
Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–74.
Article
CAS
PubMed
Google Scholar
Higgins JP, Altman DG, Gotzsche PC, Juni P, Moher D, Oxman AD, Savovic J, Schulz KF, Weeks L, Sterne JA. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.
Article
PubMed
PubMed Central
Google Scholar
How to GRADE [Internet].figshare; 2018 [cited 2020Apr1] [https://figshare.com/articles/How_to_GRADE/6818894/1].
Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58.
Article
PubMed
Google Scholar
Borenstein M. Introduction to meta-analysis. Chichester: John Wiley & Sons; 2009.
Book
Google Scholar
Higgins JPT, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration; 2011. Available from www.handbook.cochrane.org.
Xin X, Chang J, Gao Y, Shi Y. Correlation between the revised brain symmetry index, an EEG feature index, and short-term prognosis in acute ischemic stroke. J Clin Neurophysiol. 2017;34(2):162–7.
Article
PubMed
Google Scholar
Agius Anastasi A, Falzon O, Camilleri K, Vella M, Muscat R. Brain symmetry index in healthy and stroke patients for assessment and prognosis. Stroke Res Treat. 2017;2017:8276136.
PubMed
PubMed Central
Google Scholar
Malouin F, Richards CL, Desrosiers J, Doyon J. Bilateral slowing of mentally simulated actions after stroke. NeuroReport. 2004;15(8):1349–53.
Article
PubMed
Google Scholar
Malouin F, Richards CL, Durand A. Normal aging and motor imagery vividness: implications for mental practice training in rehabilitation. Arch Phys Med Rehabil. 2010;91(7):1122–7.
Article
PubMed
Google Scholar
Schuster C, Lussi A, Wirth B, Ettlin T. Two assessments to evaluate imagery ability: translation, test-retest reliability and concurrent validity of the German KVIQ and Imaprax. BMC Med Res Methodol. 2012;12:127.
Article
PubMed
PubMed Central
Google Scholar
Malouin F, Richards CL, Jackson PL, Lafleur MF, Durand A, Doyon J. The kinesthetic and visual imagery questionnaire (KVIQ) for assessing motor imagery in persons with physical disabilities: a reliability and construct validity study. J Neurol Phys Ther. 2007;31(1):20–9.
Article
PubMed
Google Scholar
Schuster C, Hilfiker R, Amft O, Scheidhauer A, Andrews B, Butler J, Kischka U, Ettlin T. Best practice for motor imagery: a systematic literature review on motor imagery training elements in five different disciplines. BMC Med. 2011;9:75.
Article
PubMed
PubMed Central
Google Scholar
Wondrusch C, Schuster-Amft C. A standardized motor imagery introduction program (MIIP) for neuro-rehabilitation: development and evaluation. Front Hum Neurosci. 2013;7:477.
Article
CAS
PubMed
PubMed Central
Google Scholar
Carelli L, Solca F, Faini A, Meriggi P, Sangalli D, Cipresso P, Riva G, Ticozzi N, Ciammola A, Silani V, et al. Brain-computer Interface for clinical purposes: cognitive assessment and rehabilitation. Biomed Res Int. 2017;2017:1695290.
Article
PubMed
PubMed Central
Google Scholar