The eff ect of gait imagery and its more demanding variant on muscle activity in stroke survivors

Česká verzia

Authors: Haltmar- H. ^{1 3}; Janura M. ¹; Haltmar- M. ^{2 4}; Elfmark M. ¹
Authors place of work: Katedra přírodních věd v kinantropologii, Fakulta tělesné kultury, Univerzita Palackého v Olomouci ¹; Ústav klinické rehabilitace, Fakulta zdravotnických věd, Univerzita Palackého v Olomouci ²; Oddělení rehabilitace, Fakultní nemocnice Olomouc ³; Neurologická klinika, Lékařská fakulta, Univerzita Palackého v Olomouci ⁴
Published in the journal: Rehabil. fyz. Lék., 31, 2024, No. 3, pp. 116-125.
Category: Original Papers
doi: https://doi.org/10.48095/ccrhfl 2024116

Summary

The gait imagery, or mental simulation of walking without actually performing it, appears to be the suitable adjunct to comprehensive rehabilitation for stroke survivors because it improves their subsequent gait performance and recovery. The aim of this study was to determine how muscle activity of selected paretic and non-paretic lower limb muscles changes in patients in the subacute phase after stroke when imagining normal gait and its more challenging variant, gait on the line. Surface electromyography (sEMG) of rectus femoris, biceps femoris, tibiais anterior and gastrocnemius medial head was recorded during three tasks (resting task, gait imagery before and after its actual execution) for normal gait and gait on the line in 40 stroke survivors. Muscle activity decreased significantly in most of the selected muscles of both lower limbs during each of the tasks of normal gait imagery and gait on the line imagery. We found lower sEMG activity in paretic gastrocnemius medial head and non-paretic rectus femoris and biceps femoris during the tasks of imagining more challenging situation. Muscle activity of paretic and non-paretic lower limbs did not differ during imagination before and after execution of both types of gait. The results of the study show that normal gait imagery and gait on a line imagery alters muscle activity in both paretic and non-paretic lower limbs. The findings may facilitate the application of imagining these movements as part of a comprehensive rehabilitation approach in subacute stroke survivors with gait limitations.

Keywords:

stroke – gait – motor imagery – lower limb muscle activity – surface electromyography – subacute

Zdroje

1. Murray CJ, Vos T, Lozano R et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380 (9859): 2197–2223. doi: 10.1016/S0140-6736 (12) 61689-4.

2. Mayo NE, Wood-Dauphinee S, Ahmed S et al. Disablement following stroke. Disabil Rehabil 1999; 21 (5–6): 258–268. doi: 10.1080/096382 899297684.

3. Jeannerod M. The representing brain: neural correlates of motor intention and imagery. Behav Brain Sci 1994; 17 (2): 187–202. doi: 10.1017/S0140525X00034026.

4. Zhao LJ, Jiang LH, Zhang H et al. Effects of motor imagery training for lower limb dysfunction in patients with stroke: a systematic review and meta-analysis of randomized controlled trials. Am J Phys Med Rehabil 2023; 102 (5): 409–418. doi: 10.1097/PHM.0000000000002107.

5. Bovonsunthonchai S, Aung N, Hiengkaew V et al. A randomized controlled trial of motor imagery combined with structured progressive circuit class therapy on gait in stroke survivors. Sci Rep 2020; 10 (1): 6945. doi: 10.1038/s41598-020-63914-8.

6. García Carrasco D, Aboitiz Cantalapiedra J. Effectiveness of motor imagery or mental practice in functional recovery after stroke: a systematic review. Neurologia 2016; 31 (1): 43–52. doi: 10.1016/j.nrl.2013.02.003.

7. Mehrholz J, Thomas S, Elsner B. Treadmill training and body weight support for walking after stroke. Cochrane Database Syst Rev 2017; 8 (8): CD002840. doi: 10.1002/14651858.CD002840.pub4.

8. Silva S, Borges LR, Santiago L et al. Motor imagery for gait rehabilitation after stroke. Cochrane Database Syst Rev 2020; 9 (9): CD13019. doi: 10.1002/14651858.CD013019.pub2.

9. Mulder T. Motor imagery and action observation: cognitive tools for rehabilitation. J Neural Transm 2007; 114 (10): 1265–1278. doi: 10.1007/s00702-007-0763-z.

10. Case LK, Pineda J, Ramachandran VS. Common coding and dynamic interactions between observed, imagined, and experienced motor and somatosensory activity. Neuropsychologia 2015; 79 (Pt B): 233–245. doi: 10.1016/j.neuropsychologia.2015.04.005.

11. Dickstein R, Deutsch JE. Motor imagery in physical therapist practice. Phys Ther 2007; 87 (7): 942–953. doi: 10.2522/ptj.20060331.

12. Barclay-Goddard RE, Stevenson TJ, Poluha W et al. Mental practice for treating upper extremity deficits in individuals with hemiparesis after stroke. Cochrane Database Syst Rev 2011; 5: CD005950. doi: 10.1002/14651858.CD005950.pub4.

13. Hatem SM, Saussez G, Della Faille M et al. Rehabilitation of motor function after stroke: a multiple systematic review focused on techniques to stimulate upper extremity recovery. Front Hum Neurosci 2016; 10: 442. doi: 10.3389/fnhum.2016.00442.

14. Oh DS, Choi JD. Effects of motor imagery training on balance and gait in older adults: a randomized controlled pilot study. Int J Environ Res Public Health 2021; 18 (2): 650. doi: 10.3390/ijerph18020650.

15. Ridderinkhof KR, Brass M. How Kinesthetic Motor Imagery works: a predictive-processing theory of visualization in sports and motor expertise. J Physiol Paris 2015; 109 (1–3): 53–63. doi: 10.1016/j.jphysparis.2015.02.003.

16. Lotze M, Halsband U. Motor imagery. J Physiol Paris 2006; 99 (4–6): 386–395. doi: 10.1016/j.jphysparis.2006.03.012.

17. Hardwick RM, Caspers S, Eickhoff SB et al. Neural correlates of action: comparing meta-analyses of imagery, observation, and execution. Neurosci Biobehav Rev 2018; 94: 31–44. doi: 10.1016/j.neubiorev.2018.08.003.

18. Hétu S, Grégoire M, Saimpont A et al. The neural network of motor imagery: an ALE meta-analysis. Neurosci Biobehav Rev 2013; 37 (5): 930–949. doi: 10.1016/j.neubiorev.2013. 03.017.

19. Loporto M, McAllister C, Williams J et al. Investigating central mechanisms underlying the effects of action observation and imagery through transcranial magnetic stimulation. J Mot Behav 2011; 43 (5): 361–373. doi: 10.1080/00222895.2011.604655.

20. Cengiz B, Boran HE. The role of the cerebellum in motor imagery. Neurosci Lett 2016; 617: 156–159. doi: 10.1016/j.neulet.2016.01.045.

21. Decety J. The neurophysiological basis of motor imagery. Behav Brain Res 1996; 77 (1–2): 45–52. doi: 10.1016/0166-4328 (95) 00225-1.

22. Di Rienzo F, Guillot A, Daligault S et al. Motor inhibition during motor imagery: a MEG study with a quadriplegic patient. Neurocase 2014; 20 (5): 524–539. doi: 10.1080/13554794. 2013.826685.

23. Solodkin A, Hlustik P, Chen EE et al. Fine modulation in network activation during motor execution and motor imagery. Cereb Cortex 2004; 14 (11): 1246–1255. doi: 10.1093/cercor/ bhh086.

24. Haltmar H, Kolářová B, Haltmar M et al. Představa pohybu – neurální podstata a mož-nosti jejího využití ve fyzioterapii. Rehabil Fyz Lék 2022; 29 (3): 130–135. doi: 10.48095/ccrhfl 2022130.

25. Guillot A, Lebon F, Rouffet D et al. Muscular responses during motor imagery as a function of muscle contraction types. Int J Psychophysiol 2007; 66 (1): 18–27. doi: 10.1016/ j.ijpsycho.2007.05.009.

26. Guillot A, Collet C. Contribution from neurophysiological and psychological methods to the study of motor imagery. Brain Res Rev 2005; 50 (2): 387–397. doi: 10.1016/ j.brainresrev.2005.09.004.

27. Hanakawa T. Organizing motor imageries. Neurosci Res 2016; 104: 56–63. doi: 10.1016/ j.neures.2015.11.003.

28. Ruffino C, Papaxanthis C, Lebon F. Neural plasticity during motor learning with motor imagery practice: review and perspectives. Neuroscience 2017; 341: 61–78. doi: 10.1016/j.neuroscience.2016.11.023.

29. Harris JE, Hebert A. Utilization of motor imagery in upper limb rehabilitation: a systematic scoping review. Clin Rehabil 2015; 29 (11): 1092–1107. doi: 10.1177/02692155145 66248.

30. Zimmermann-Schlatter A, Schuster C, Puhan MA et al. Efficacy of motor imagery in post-stroke rehabilitation: a systematic review. J Neuroeng Rehabil 2008; 5: 8. doi: 10.1186/1743- 0003-5-8.

31. Beyaert C, Vasa R, Frykberg GE. Gait post-stroke: pathophysiology and rehabilitation strategies. Neurophysiol Clin 2015; 45 (4–5): 335–355. doi: 10.1016/j.neucli.2015.09.005.

32. Riccio I, Iolascon G, Barillari MR et al. Mental practice is effective in upper limb recovery after stroke: a randomized single-blind cross-over study. Eur J Phys Rehabil Med 2010; 46 (1): 19–25.

33. Page SJ, Levine P, Leonard AC. Effects of mental practice on affected limb use and function in chronic stroke. Arch Phys Med Rehabil 2005; 86 (3): 399–402. doi: 10.1016/ j.apmr.2004.10.002.

34. Gregg M, Hall C, Butler A. The MIQ-RS: a suitable option for examining movement imagery ability. Evid Based Complement Alternat Med 2010; 7 (2): 249–257. doi: 10.1093/ecam/ nem170.

35. Sharma N, Pomeroy VM, Baron JC. Motor imagery: a backdoor to the motor system after stroke? Stroke 2006; 37 (7): 1941–1952. doi: 10.1161/01.STR.0000226902.43357.fc.

36. Hall CR, Martin KA. Measuring movement imagery abilities: a revision of the Movement Imagery Questionnaire. J Ment Imagery 1997; 21 (1–2): 143–154.

37. Butler AJ, Cazeaux J, Fidler A et al. The Movement Imagery Questionnaire-Revised, Second Edition (MIQ-RS) is a reliable and valid tool for evaluating motor imagery in stroke populations. Evid Based Complement Alternat Med 2012; 497289. doi: 10.1155/2012/497289.

38. Haltmar H, Janura M, Elfmark M. Validizace české verze dotazníku představy pohybu Movement Imagery Questionnaire-Revised Second Version u pacientů po cévní mozkové příhodě. Rehabil Fyz Lék 2023; 30 (4): 172–182. doi: 10.48095/ccrhfl 2023172.

39. Mehrholz J, Wagner K, Rutte K et al. Predictive validity and responsiveness of the functional ambulation category in hemiparetic patients after stroke. Arch Phys Med Rehabil 2007; 88 (10): 1314–1319. doi: 10.1016/ j.apmr.2007.06.764.

40. Stegeman DF, Hermens HJ. Standards for surface electromyography: the European project (SENIAM). In: Hermens HJ, Rau G, Disselhorst-Klug C et al. Surface ElectroMyoGraphy application areas and parameters. Proceedings of the 3rd general SENIAM workshop, Aachen, Germany 1998; 108–112.

41. Cotter KN. Mental control in musical imagery: a dual component model. Front Psychol 2019; 10: 1904. doi: 10.3389/fpsyg.2019. 01904.

42. Ghislieri M, Gastaldi L, Pastorelli S et al. Wearable inertial sensors to assess standing balance: a systematic review. Sensors (Basel) 2019; 19 (19): 4075. doi: 10.3390/s19194075.

43. Solomon JP, Kraeutner SN, Bardouille T et al. Probing the temporal dynamics of movement inhibition in motor imagery. Brain Res 2019; 1720: 146310. doi: 10.1016/j.brainres.2019. 146310.

44. Brunner R, Rutz E. Biomechanics and muscle function during gait. J Child Orthop 2013; 7 (5): 367–371. doi: 10.1007/s11832-013-0508-5.

45. Sozzi S, Honeine J-L, Do M-C et al. Leg muscle activity during tandem stance and the control of body balance in the frontal plane. Clin Neurophysiol 2013; 124 (6): 1175–1186. doi: 10.1016/j.clinph.2012.12.001.

46. Bunno Y. Motor imagery for neurorehabilitation: the F-wave study. In: Suzuki T (ed). Somatosensory and motor research. Japan: IntechOpen 2020. doi: 10.5772/intechopen.91834.

47. Brach JS, Van Swearingen JM, Perera S et al. Motor learning versus standard walking exercise in older adults with subclinical gait dysfunction: a randomized clinical trial. J Am Geriatr Soc 2013; 61 (11): 1879–1886. doi: 10.1111/ jgs.12506.

48. Shadmehr R, Mussa-Ivaldi FA. Adaptive representation of dynamics during learning of a motor task. J Neurosci 1994; 14 (5 Pt 2): 3208–3224. doi: 10.1523/JNEUROSCI.14-05-03208. 1994.

49. Grosprêtre S, Lebon F, Papaxanthis C et al. Spinal plasticity with motor imagery practice. J Physiol 2019; 597 (3): 921–934. doi: 10.1113/JP276694.

50. Wieland B, Behringer M, Zentgraf K. Effects of motor imagery training on skeletal muscle contractile properties in sports science students. PeerJ 2022; 10: e14412. doi: 10.7717/peerj.14412.

51. Goodworth AD, Peterka RJ. Influence of stance width on frontal plane postural dynamics and coordination in human balance control. J Neurophysiol 2010; 104 (2): 1103–1118. doi: 10.1152/jn.00916.2009.

52. Houdijk H, Fickert R, van Velzen J et al. The energy cost for balance control during upright standing. Gait Posture 2009; 30 (2): 150–154. doi: 10.1016/j.gaitpost.2009.05.009.

53. Heshmatollah A, Darweesh SKL, Dommershuijsen LJ et al. Quantitative gait impairments in patients with stroke or transient ischemic attack: a population-based approach. Stroke 2020; 51 (8): 2464–2471. doi: 10.1161/STROKEAHA.120.029829.

54. Steele KM, Papazian C, Feldner HA. Muscle activity after stroke: perspectives on deploying surface electromyography in acute care. Front Neurol 2020; 11: 576757. doi: 10.3389/fneur.2020.576757.

55. Chae J, Yang G, Park BK, et al. Muscle weakness and cocontraction in upper limb hemiparesis: relationship to motor impairment and physical disability. Neurorehabil Neural Repair 2002; 16 (3): 241–248. doi: 10.1177/1545968 30201600303.

56. Johnson SH, Sprehn G, Saykin AJ. Intact motor imagery in chronic upper limb hemiplegics: evidence for activity-independent action representations. J Cogn Neurosci 2002; 14 (6): 841–852. doi: 10.1162/0898929027601 91072.

57. Malouin F, Richards CL, Durand A et al. Clinical assessment of motor imagery after stroke. Neurorehabil Neural Repair 2008; 22 (4): 330–340. doi: 10.1177/15459683073 13499.

58. Yao WX, Ranganathan VK, Allexandre D et al. Kinesthetic imagery training of forceful muscle contractions increases brain signal and muscle strength. Front Hum Neurosci 2013; 7: 561. doi: 10.3389/fnhum.2013.00561.

59. Holmes PS, Collins DJ. The PETTLEP approach to motor imagery: a functional equivalence model for sport psychologists. J Appl Sport Psychol 2001; 13 (1): 60–83. doi: 10.1080/10413 200109339004.

Poděkování

Autoři článku by rádi poděkovali všem pacientům za jejich ochotu participovat na studii.

Doručeno/Submitted: 23. 4. 2024

Přijato/Accepted: 20. 6. 2024

Korespondenční autor:

Mgr. Hana Haltmar

Katedra přírodních věd v kinantropologii Fakulta tělesné kultury

Univerzita Palackého v Olomouci

třída Míru 117

771 11 Olomouc

e-mail: hana.haltmar@upol.cz