The Electromyographic Activity of Lower Limb Muscles in the Elderly during Walking on the Treadmill: An Emphasis on the Effect of Virtual Reality

Document Type : Original Articles

Authors

1 Assistant Professor, Department of Motor Behavior, School of Physical Education and Sports Sciences, University of Tabriz, Tabriz, Iran

2 MSc Student, Department of Motor Behavior, School of Physical Education and Sports Sciences, University of Tabriz, Tabriz, Iran

3 MSc Student, Department of Sport Psychology, School of Physical Education and Sports Sciences, University of Tabriz, Tabriz, Iran

4 Assistant Professor, Department of Health in the Sport, School of Physical Education and Sports Sciences, University of Agri Ibrahim chechen, Agri, Turkey

10.22122/jrrs.v16i0.3567

Abstract

Introduction: The aim of this study was to assess the effects of virtual reality (VR) on the electromyographic (EMG) activity of the lower limb muscles during gait on the treadmill in the elderly.Materials and Methods: 12 elderly male subjects participated in this study voluntarily. Using an EMG-USB2+ multichannel system (Bioelettronica, Italy) (sampling frequency of 1000 Hz) and bipolar surface electrodes, the electrical activity of tibialis anterior (TA), rectus femoris (RF), and biceps femoris (BF) muscles were recorded bilaterally during walking with the preferred speed with and without VR environment on the treadmill. The maximal voluntary isometric contraction (MVIC) method was used for the normalization of signals. The gathered signals were processed using OT BioLab software with a bandpass filter of 10-350 Hz and a notch filter of 50 Hz. The data were processed using repeated measures analysis of variance (ANOVA) and paired sample t-test in SPSS software at a significance level of 0.050.Results: The findings showed that during walking in VR environment, the EMG activity of bilateral RF muscles and right TA muscle of the elderly subjects were significantly higher than normal walking with about 1.97 (P ≤ 0.005), 1.91 (P ≤ 0.003), and 2.03 (P ≤ 0.002) times, respectively. But the differences between EMG activity of right (P ≤ 0.280) and left (P ≤ 0.990) BF and left TA (P ≤ 0.080) muscles were not significant during walking with and without VR. Overall, VR had the main effect on the muscle activity of the elderly subjects (P ≤ 0.007). Moreover, there was a significant interaction between VR and muscle factors (P ≤ 0.036).Conclusion: The results indicated that VR increases the EMG activity of lower extremity muscles among the elderly, thus it can be recommended strongly in the rehabilitation of lower extremity muscles in the elderly.

Keywords

  1. Azim Zadeh E, Faghihi V, Ghasemi A. The effect of dual-task training on balance of elderly women: with the motor and cognitive approach. Research in Sport Management and Motor Behavior 2018; 8(15): 103-10. [In Persian].
  2. Barak Y, Wagenaar RC, Holt KG. Gait characteristics of elderly people with a history of falls: A dynamic approach. Phys Ther 2006; 86(11): 1501-10.
  3. Lockhart TE, Woldstad JC, Smith JL. Effects of age-related gait changes on the biomechanics of slips and falls. Ergonomics 2003; 46(12): 1136-60.
  4. Voermans NC, Snijders AH, Schoon Y, Bloem BR. Why old people fall (and how to stop them). Pract Neurol 2007; 7(3): 158-71.
  5. Lamoth CJ, van Deudekom FJ, van Campen JP, Appels BA, de Vries OJ, Pijnappels M. Gait stability and variability measures show effects of impaired cognition and dual tasking in frail people. J Neuroeng Rehabil 2011; 8: 2.
  6. Priest AW, Salamon KB, Hollman JH. Age-related differences in dual task walking: A cross sectional study. J Neuroeng Rehabil 2008; 5: 29.
  7. Callisaya ML, Blizzard L, Schmidt MD, Martin KL, McGinley JL, Sanders LM, et al. Gait, gait variability and the risk of multiple incident falls in older people: A population-based study. Age Ageing 2011; 40(4): 481-7.
  8. Annetta LA. Video Games in Education: Why they should be used and how they are being used. Theory Pract 2008; 47(3): 229-39.
  9. Laver KE, George S, Thomas S, Deutsch JE, Crotty M. Virtual reality for stroke rehabilitation. Cochrane Database Syst Rev 2011; (9): CD008349.
  10. Saposnik G, Teasell R, Mamdani M, Hall J, McIlroy W, Cheung D, et al. Effectiveness of virtual reality using Wii gaming technology in stroke rehabilitation: A pilot randomized clinical trial and proof of principle. Stroke 2010; 41(7): 1477-84.
  11. Keshner EA. Virtual reality and physical rehabilitation: A new toy or a new research and rehabilitation tool? J Neuroeng Rehabil 2004; 1(1): 8.
  12. Martin O, Julian B, Boissieux L, Gascuel JD, Prablanc C. Evaluating online control of goal-directed arm movement while standing in virtual visual environment. Comput Animat Virtual Worlds 2003; 14(5): 253-60.
  13. Hoffman HG, Garcia-Palacios A, Kapa V, Beecher J, Sharar SR. Immersive virtual reality for reducing experimental ischemic pain. Int J Human Computer Interact 2003; 15(3): 469-86.
  14. Forkan R, Pumper B, Smyth N, Wirkkala H, Ciol MA, Shumway-Cook A. Exercise adherence following physical therapy intervention in older adults with impaired balance. Phys Ther 2006; 86(3): 401-10.
  15. Mirelman A, Patritti BL, Bonato P, Deutsch JE. Effects of virtual reality training on gait biomechanics of individuals post-stroke. Gait Posture 2010; 31(4): 433-7.
  16. Powell WA, Stevens B. The influence of virtual reality systems on walking behaviour: A toolset to support application design. Proceedings of 2013 International Conference on Virtual Rehabilitation (ICVR); 2013 Aug 26-29; Philadelphia, PA, USA. p. 270-6.
  17. Deutsch JE, Myslinski MJ, Kafri M, Ranky R, Sivak M, Mavroidis C, et al. Feasibility of virtual reality augmented cycling for health promotion of people poststroke. J Neurol Phys Ther 2013; 37(3): 118-24.
  18. Bahram ME, Akasheh G, Shabanzadeh Fini M. The effect of 10 weeks of pilates exercises on static and dynamic balance and psychological factors in elderly men. J Fasa Univ Med Sci 2017; 7(3): 416-27. [In Persian].
  19. Farajzadeh MM, Ghanei GR, Sayehmiri K. Health related quality of life in iranian elderly citizens: A systematic review and meta-analysis. Int J Community Based Nurs Midwifery 2017; 5(2): 100-11.
  20. Jeste DV, Blazer DG, First M. Aging-related diagnostic variations: need for diagnostic criteria appropriate for elderly psychiatric patients. Biol Psychiatry 2005; 58(4): 265-71.
  21. Browne JP, O'Boyle CA, McGee HM, Joyce CR, McDonald NJ, O'Malley K, et al. Individual quality of life in the healthy elderly. Qual Life Res 1994; 3(4): 235-44.
  22. Simoes EC, Moraes AC, Okano AH, Altimari LR. Behavior of EMG activation of rectus femoris, vastus lateralis and vastus medialis muscles during maximum contraction before and after a series of repeated efforts. Electromyogr Clin Neurophysiol 2008; 48(8): 377-84.
  23. Contreras B, Vigotsky AD, Schoenfeld BJ, Beardsley C, Cronin J. A comparison of gluteus maximus, biceps femoris, and vastus lateralis electromyography amplitude in the parallel, full, and front squat variations in resistance-trained females. J Appl Biomech 2016; 32(1): 16-22.
  24. Merletti R, Rainoldi A, Farina D. Surface electromyography for noninvasive characterization of muscle. Exerc Sport Sci Rev 2001; 29(1): 20-5.
  25. Hollman JH, Childs KB, McNeil ML, Mueller AC, Quilter CM, Youdas JW. Number of strides required for reliable measurements of pace, rhythm and variability parameters of gait during normal and dual task walking in older individuals. Gait Posture 2010; 32(1): 23-8.
  26. Ghanavati T, Salavati M, Karimi N, Negahban H, Ebrahimi Takamjani I, Mehravar M, et al. Intra-limb coordination while walking is affected by cognitive load and walking speed. J Biomech 2014; 47(10): 2300-5.
  27. Hollman JH, Kovash FM, Kubik JJ, Linbo RA. Age-related differences in spatiotemporal markers of gait stability during dual task walking. Gait Posture 2007; 26(1): 113-9.
  28. Lin HT, Hsu AT, Chang JH, Chien CS, Chang GL. Comparison of EMG activity between maximal manual muscle testing and cybex maximal isometric testing of the quadriceps femoris. J Formos Med Assoc 2008; 107(2): 175-80.
  29. Tabard-Fougere A, Rose-Dulcina K, Pittet V, Dayer R, Vuillerme N, Armand S. EMG normalization method based on grade 3 of manual muscle testing: Within- and between-day reliability of normalization tasks and application to gait analysis. Gait Posture 2018; 60: 6-12.
  30. Park J, Lee D, Lee S. Effect of virtual reality exercise using the nintendo wii fit on muscle activities of the trunk and lower extremities of normal adults. J Phys Ther Sci 2014; 26(2): 271-3.
  31. Sharifmoradi K, Farahpour N. Assessment of range of motion and lower limb muscle activity in Parkinson patients and normal elderly subject (A case study). J Sport Biomech 2017; 3(1): 25-36. [In Persian].
  32. Elhami M, Yazdani S. Electromyographic activity of lower extremity and trunk muscles in patients with cerebral palsy during normal walking and walking with visual, motor and cognitive dual task [MSc Thesis]. Tabriz, Iran: University of Tabriz; 2019. [In Persian].
  33. Azadian E, Taheri H R, Saberi Kakhki A, Farahpour N. Effects of dual-tasks on spatial-temporal parameters of gait in older adults with impaired balance. Salmand Iran J Ageing 2016; 11(1): 100-9. [In Persian].
  34. Walker ML, Ringleb SI, Maihafer GC, Walker R, Crouch JR, Van Lunen B, et al. Virtual reality-enhanced partial body weight-supported treadmill training poststroke: Feasibility and effectiveness in 6 subjects. Arch Phys Med Rehabil 2010; 91(1): 115-22.
  35. Dunning K, Levine P, Schmitt L, Israel S, Fulk G. An ankle to computer virtual reality system for improving gait and function in a person 9 months poststroke. Top Stroke Rehabil 2008; 15(6): 602-10.
  36. Quaney BM, He J, Timberlake G, Dodd K, Carr C. Visuomotor training improves stroke-related ipsilesional upper extremity impairments. Neurorehabil Neural Repair 2010; 24(1): 52-61.
  • Receive Date: 19 June 2020
  • Revise Date: 02 June 2022
  • Accept Date: 22 May 2022