Is there a correlation between muscle and brain electrical activity after training with upper limb and trunk constraint-induced therapy in subjects with stroke?
DOI:
https://doi.org/10.11606/issn.2317-0190.v29i4a168691Keywords:
Stroke, Electromyography, Electroencephalography, Physical Therapy Modalities, RehabilitationAbstract
Objective: Establish the correlation between central and peripheral excitability after training with the modified upper limb constraint-induced movement therapy (CIMT) associated with trunk constraint for patients with stroke. Methods: This study is a randomized clinical trial. Twenty-two volunteers were included and randomized into the Control (CG) and Experimental Groups (EG). They were assessed with electroencephalography (EEG) and surface electromyography (EMG). The EEG channels analyzed were antero-frontal (AF3/AF4), frontal-medial (F7/F8), frontal-lateral (F3/F4), frontal-central (FC5/FC6), temporal (T7/T8), and occipital (O1/O2). The muscles evaluated with EMG were biceps brachii, wrist flexors, and wrist extensors. The evaluations were performed simultaneously with a functional assessment for ten minutes. The EG received the modified CIMT training one hour per day for two consecutive weeks. Results: After the intervention, the CG showed a moderate negative correlation of the Fa channel with the wrist extensor (r= -0.69; p= 0.02), whereas the EG had a moderate negative correlation of the FA channel (r= -0.68; p= 0.02) and FC (r= - 0.71; p= 0.01) with wrist flexor. In the post-intervention, a positive correlation of the FA channel was found with the wrist extensor (r= 0.61; p= 0.04). Conclusion: The modified CIMT associated with the trunk constraint for the paretic upper limb showed a positive correlation between the Fa channel and the wrist extensor muscle, and the control group showed a negative correlation between the Fa channel and the wrist extensor.
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References
Li S. Spasticity, motor recovery, and neural plasticity after stroke. Front Neurol. 2017;8:120. Doi: https://doi.org/10.3389/fneur.2017.00120
Go AS, Mozaffarian D, Roger VL, Bejamin EJ, Berry JD, Blaha MJ, et al. Heart disease and stroke statistics – 2014 update: a report from the American Heart Association. Circulation 2014;129(3):e28-e292. Doi: https://doi.org/10.1161/01.cir.0000441139.02102.80
Jones TA. Motor compensation and its effects on neural reorganization after stroke. Nat Rev Neurosci. 2017;18(5):267-80. Doi: https://doi.org/10.1038/nrn.2017.26
Taub E, Uswatte G, Mark VW. The functional significance of cortical reorganization and the parallel development of CI therapy. Front Hum Neurosci. 2014;8:396. Doi: https://doi:10.3389/fnhum.2014.00396
Cramer SC. Treatments to promote neural repair after stroke. J Stroke 2018;20(1):57-70. Doi: https://doi.org/10.5853/jos.2017.02796
Kwakkel G, Veerbeek JM, van Wegen EE, Wolf SL. Constraint-induced movement therapy after stroke. Lancet Neurol. 2015;14(2):224-34. Doi: https://doi.org/10.1016/S1474-4422(14)70160-7
Greisberger A, Aviv H, Garbade SF, Diermayr G. Clinical relevance of the effects of reach-to-grasp training using trunk restraint in individuals with hemiparesis poststroke: A systematic review. J Rehabil Med. 2016;48(5):405-16. Doi: https://doi.org/10.2340/16501977-2077
Bang DH, Shin WS, Choi HS. Effects of modified constraint-induced movement therapy combined with trunk restraint in chronic stroke: a double-blinded randomized controlled pilot trial. NeuroRehabilitation. 2015;37(1):131-7. Doi: https://doi.org/10.3233/NRE-151245
Loubinoux I, Brihmat N, Castel-Lacanal E, Marque P. Cerebral imaging of post-stroke plasticity and tissue repair. Revue Neurologique. 2017;173(9):577-583. Doi: https://doi.org/10.1016/j.neurol.2017.09.007
Nuwer M. Assessment of digital EEG, quantitative EEG, and EEG brain mapping: report of the American Academy of Neurology and the American Clinical Neurophysiology Society. Neurology. 1997;49(1):277-92. Doi: https://doi.org/10.1212/wnl.49.1.277
Bastos VH, Cunha M, Veiga H, McDowell K, Pompeu F, Cagy M, et al. Análise da distribuição de potência cortical em função do aprendizado de datilografia. Rev Bras Med Esporte. 2004;10(6):494-9. Doi: https://doi.org/10.1590/S1517-86922004000600006
Kiefer AW, Gualberto Cremades J, Myer GD. Train the brain: novel electroencephalography data indicate links between motor learning and brain adaptations. J Nov Physiother. 2014;4(2):198. Doi: https://doi.org/10.4172/2165-7025.1000198
Medved V. Cifrek M. Kinesiological electromyography. In: Klika V. Biomechanics in applications. London: IntechOpen; 2011. Doi: https://doi.org/10.5772/21282
Kouzi I, Trachani E, Anagnostou E, Rapidi CA, Ellul J, Sakellaropoulos GC, et al. Motor unit number estimation and quantitative needle electromyography in stroke patients. J Electromyogr Kinesiol. 2014;24(6):910-6. Doi: https://doi.org/10.1016/j.jelekin.2014.09.006
Hu XL, Tong KY, Wei XJ, Rong W, Susanto EA, Ho SK. The effects of post-stroke upper-limb training with an electromyography (EMG)-driven hand robot. J Electromyogr Kinesiol. 2013;23(5):1065-74. Doi: https://doi.org/10.1016/j.jelekin.2013.07.007
Folstein MF, Folstein SE, Mchugh PR. Mini Mental State. A practical method for grading the cognitive state of patients for the clinician. J Psychiat Res. 1975;12:189-98. Doi: https://doi.org/10.1016/0022-3956(75)90026-6
Fugl-Meyer AR, Jääskö L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scand J Rehabil Med. 1975;7(1):13-31.
Biering-Sorense F, Nielsen J B, Klinge K. Spasticity-assessment: a review. Spinal Cord. 2006;44(12):708-22. Doi: https://doi.org/10.1038/sj.sc.3101928
Kasner SE. Clinical interpretation and use of stroke scales. Lancet Neurol. 2006;5(7):603-12. Doi: https://doi.org/10.1016/S1474-4422(06)70495-1
European Recommendations for Surface Electromyography [text on the Internet]. Enschede: SENIAM [cited 2018 Jan 26]. Available from: http://www.seniam.org/
Duvinage M, Castermans T, Petieau M, Hoellinger T, Cheron G, Dutoit T. Performance of the Emotiv Epoc headset for P300-based applications. Biomed Eng Online. 2013;12:56. Doi: https://doi.org/10.1186/1475-925X-12-56
Badcock NA, Mousikou P, Mahajan Y, Lissa P, Thie J, McArthur G. Validation of the Emotiv EPOC(®) EEG gaming system for measuring research quality auditory ERPs. PeerJ. 2013;1:e38. Doi: https://doi.org/10.7717/peerj.38
Pacheco TBF, Oliveira Rego IA, Campos TF, Cavalcanti FADC. Brain activity during a lower limb functional task in a real and virtual environment: A comparative study. NeuroRehabilitation. 2017;40(3):391-400. Doi: https://doi.org/10.3233/NRE-161426
Koessler L, Maillard L, Benhadid A, Vignal JP, Felblinger J, Vespignani H, Braun M. Automated cortical projection of EEG sensors: anatomical correlation via the international 10-10 system. Neuroimage. 2009;46(1):64-72. Doi: https://doi.org/10.1016/j.neuroimage.2009.02.006
Jensen O, Mazaheri A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front Hum Neurosci. 2010;4:186. Doi: https://doi.org/10.3389/fnhum.2010.00186
Barbas H, Mesulam MM. Organization of afferent input to subdivisions of area 8 in the rhesus monkey. J Comp Neurol. 1981;200(3):407-31. Doi: https://doi.org/10.1002/cne.902000309
Oliveira SMS, Medeiros CSP, Pacheco TBF, Bessa NPOS, Silva FGM, Tavares NSA, et al. Electroencephalographic changes using virtual reality program: technical note. Neurol Res. 2018;40(3):160-5. Doi: https://doi.org/10.1080/01616412.2017.1420584
Fang Y, Daly JJ, Sun J, Hvorat K, Fredrickson E, Pundik S, et al. Functional corticomuscular connection during reaching is weakened following stroke. Clinical Neurophysiology; 2009;120(5):994-1002. Doi: https://doi.org/10.1016/j.clinph.2009.02.173
Flament D, Shapiro MB, Kempf T, Corcos DM. Time course and temporal order of changes in movement kinematics during learning of fast and accurate elbow flexions. Exp Brain Res. 1999;129(3):441-50. Doi: https://doi.org/10.1007/s002210050911
Thibaut A, Simis M, Battistella LR, Fanciullacci C, Bertolucci F, Huerta-Gutierrez R, et al. Using brain oscillations and corticospinal excitability to understand and predict post-stroke motor function. Front Neurol. 2017;8:187. Doi: https://doi.org/10.3389/fneur.2017.00187
Demandt E, Mehring C, Vogt K, Schulze-Bonhage A, Aertsen A, Ball T. Reaching movement onset- and end-related characteristics of EEG spectral power modulations. Front Neurosci. 2012;6:65. https://doi.org/10.3389/fnins.2012.00065
Gao Y, Ren L, Li R, Zhang Y. Electroencephalogram-Electromyography Coupling Analysis in Stroke Based on Symbolic Transfer Entropy. Front Neurol. 2018;8:716. Doi: https://doi.org/10.3389/fneur.2017.00716
Luft AR, Smith GV, Larry F, Jill W, Macko RF, Hauser T, et al. Comparing brain activation associated with isolated upper and lower limb movement across corresponding joints. Human brain mapping 2002;17:131-40. Doi: https://doi.org/10.1002/hbm.10058
Hu XL, Tong KY, Song R, Zheng XJ, Lui KH, Leung WW, et al. Quantitative evaluation of motor functional recovery process in chronic stroke patients during robot-assisted wrist training. J Electromyogr Kinesiol. 2009;19(4):639-50. https://doi.org/10.1016/j.jelekin.2008.04.002
Nam C, Rong W, Li W, Xie Y, Hu X, Zheng Y. The Effects of Upper-Limb Training Assisted with an Electromyography-Driven Neuromuscular Electrical Stimulation Robotic Hand on Chronic Stroke. Front Neurol. 2017;8:679. https://doi.org/10.3389/fneur.2017.00679
Ivanhoe CB, Reistetter TA. Spasticity: the misunderstood part of the upper motor neuron syndrome. Am J Phys Med Rehabil. 2004;83(10 Suppl):S3-9. https://doi.org/10.1097/01.phm.0000141125.28611.3e
Cauraugh J, Light K, Kim S, Thigpen M, Behrman A. Chronic motor dysfunction after stroke: recovering wrist and finger extension by electromyography-triggered neuromuscular stimulation. Stroke. 2000;31(6):1360-4. https://doi.org/10.1161/01.str.31.6.1360
Pellicciari MC, Bonnì S, Ponzo V, Cinnera AM, Mancini M, Casula EP, et al. Dynamic reorganization of TMS-evoked activity in subcortical stroke patients. Neuroimage. 2018;175:365-78. https://doi.org/10.1016/j.neuroimage.2018.04.011
Brinkman L, Stolk A, Dijkerman HC, Lange FP, Toni I. Distinct roles for alpha- and beta-band oscillations during mental simulation of goal-directed actions. J Neurosci. 2014;34(44):14783-92. https://doi.org/10.1523/JNEUROSCI.2039-14.2014
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Fundação de Amparo à Pesquisa do Estado de Minas Gerais
Grant numbers APQ-02976- 17
