국제물리치료학회지 (Journal of International Academy of Physical Therapy Research)

  • 제11권2호
  • /
  • Pages.2021-2027
  • /
  • 2020
  • /
  • 2092-8475(pISSN)
  • /
  • 2714-0148(eISSN)
국제물리치료연구학회 (International Academy of Physical Therapy Research)
권호 표지
DOI QR코드

DOI QR Code

Effects of Robot-Mediated Gait Training Combined with Virtual Reality System on Muscle Activity: A Case Series Research

  • Heo, Seoyoon (Department of Occupational Therapy, School of Medical and Health Care, Kyungbok University) ;
  • Kim, Mooki (Department of Occupational Therapy, Pohang University) ;
  • Choi, Wansuk (Department of Physical Therapy, International University of Korea)
  • 투고 : 2020.05.21
  • 심사 : 2020.06.05
  • 발행 : 2020.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Background: Previous robot-mediated gait training has been proven several limitations such as pointless repeated motion training, decreased presence, etc. In this research, adult stroke patients were participated in robot-mediated gait training accompanied with or without virtual reality program. Objectives: Exploring whether the results indicated virtual reality system has contribution to muscle strength and balance ability. Design: A case series research, cross-over trial. Methods: Eleven participants (male 4, female 7) with adults diagnosed as stroke from medical doctor ware engaged. The participants received 2 treatment sessions of identical duration, robot-assisted gait training with virtual reality and robot-assisted gait training with screen-off randomly crossed over include 1-day for each person of wash-out period. The parameter was muscle activity, the researchers assessed sEMG (surface electromyography). Results: The result showed less muscle activities during training in robot-assisted gait training with virtual reality circumstances, and these indicated muscles were gluteus medius muscle, vastus medialis muscle, vastus intermedius and vastus lateralis muscle, semimembranosus muscle, gastrocnemius-lateral head, and soleus muscle (P<.05). Conclusion: In this study, we analyzed the outcome of muscle activity for clinical inference of robot-assisted gait training with virtual reality (VR). Less muscle activity was measured in the treatment accompanied by VR, therefore, a more systematic, in-depth and well-founded level of follow-up research is needed.

키워드

참고문헌

  1. Timmermans AA, Spooren AI, Kingma H, Seelen HA. Influence of task-oriented training content on skilled arm-hand performance in stroke: a systematic review. Neurorehabil Neural Repair. 2010;24(9):858-870. https://doi.org/10.1177/1545968310368963
  2. Francesco T, Antonino C, Maria FP, et al. A Case Report on Intensive, Robot-Assisted Rehabilitation Program for Brainstem Radionecrosis. Medicine (Baltimore). 2020;99(10):e19517. https://doi.org/10.1097/MD.0000000000019517
  3. Zhao Y, Liang C, Gu Z, Zheng Y, Wu Q. A New Design Scheme for Intelligent Upper Limb Rehabilitation Training Robot. Int J Environ Res Public Health. 2020;17(8):2948. https://doi.org/10.3390/ijerph17082948
  4. Keramas JG. Robot Technology Fundamentals. Delmar Learning; 1998:398.
  5. Munari D, Fonte C, Varalta V, et al. Effects of robot-assisted gait training combined with virtual reality on motor and cognitive functions in patients with multiple sclerosis: A pilot, single-blind, randomized controlled trial. Restor Neurol Neurosci. 2020;38(2):151-164. https://doi.org/10.3233/rnn-190974
  6. Shahab M, Raisi M, Hejrati M, Taheri AR, Meghdari A. Virtual Reality Robot for Rehabilitation of Children with Cerebral Palsy (CP). In: IEEE conference on Robotics and Mechatronics (ICRoM), 2019.
  7. Patel J. Virtual Reality and Robotic Based Training for the Upper Limb in the Acute and Early Sub-acute Periods Post-stroke [PhD thesis]. New Jersey, USA: Rutgers The State University of New Jersey, Rutgers School of Health Professions; 2020.
  8. Sorrento GU, Archambault PS, Fung J. The Effects of a Virtual Environment and Robot Generated Haptic Forces on the Coordination of the Lower Limb During Gait in Chronic Stroke Using Planar and 3D Phase Diagrams. In: IEEE conference on Virtual Rehabilitation (ICVR), 2019.
  9. Zhang M, Davies TC, Xie S. Effectiveness of robot-assisted therapy on ankle rehabilitation - a systematic review. J Neuroeng Rehabil. 2013;10:30. https://doi.org/10.1186/1743-0003-10-30
  10. Kwakkel G, Kollen BJ, Krebs HI. Effects of Robot-Assisted Therapy on Upper Limb Recovery After Stroke: A Systematic Review. Neurorehabil Neural Repair. 2008;22(2):111-121. https://doi.org/10.1177/1545968307305457
  11. Heo SY, Lee HJ, Ham AJ, Kim YN, Jeong SN, Kim KM. The Effects of Virtual Reality Therapy on Executive Function and Balance for Stroke Patients: A Randomized Controlled Clinical Trial. J Korean Soc Occup Ther. 2016;24(4):1-14. https://doi.org/10.14519/jksot.2016.24.4.01
  12. Lemmens RJ, Timmermans AA, Janssen-Potten YJ, Smeets RJ, Seelen HA. Valid and reliable instruments for arm-hand assessment at ICF activity level in persons with hemiplegia: a systematic review. BMC Neurol. 2012;12(1):21. https://doi.org/10.1186/1471-2377-12-21
  13. Ali M, Atula S, Bath PM, et al. Stroke outcome in clinical trial patients deriving from different countries. Stroke. 2009;40(1):35-40. https://doi.org/10.1161/STROKEAHA.108.518035
  14. Van Delden AEQ, Peper CE, Beek PJ, Kwakkel G. Unilateral versus bilateral upper limb exercise therapy after stroke: a systematic review. J Rehabil Med. 2012;44(2):106-117. https://doi.org/10.2340/16501977-0928
  15. Williams JR. The Declaration of Helsinki and public health. Bull World Health Organ. 2008;86:650-652. https://doi.org/10.2471/BLT.08.050955
  16. Cram JR. Cram's Introduction to Surface Electromyography. 2nd ed. Burlington: Jones & Bartlett Learning; 2010.
  17. Nishimura RA, Trusty JM, Hayes DL, et al. Dual-Chamber Pacing for Hypertrophic Cardiomyopathy: A Randomized, Double-Blind, Crossover Trial. J Am Coll Cardiol. 1997;29(2):435-441. https://doi.org/10.1016/S0735-1097(96)00473-1
  18. Kempen TGH, Bertilsson M, Lindner K-J, et al. Medication Reviews Bridging Healthcare (MedBridge): Study protocol for a pragmatic cluster-randomised crossover trial. Contemp Clin Trials. 2017;61:126-132. https://doi.org/10.1016/j.cct.2017.07.019
  19. Tim Joda, Urs Bragger. Patient-centered outcomes comparing digital and conventional implant impression procedures: a randomized crossover trial. Clin Oral Implants Res. 2016;27(12):e185-e189. https://doi.org/10.1111/clr.12600
  20. Friede T, Posch M, Zohar S, et al. Recent advances in methodology for clinical trials in small populations: the InSPiRe project. OrphanetJ Rare Dis. 2018;13(1):186. https://doi.org/10.1186/s13023-018-0919-y
  21. Kashi S, Feingold-Polak R, Lerner B, Rokach L, Levy-Tzedek S. A machine-learning model for automatic detection of movement compensations in stroke patients. In: IEEE Transactions on Emerging Topics in Computing, 2020.
  22. Tepe Victoria, Charles M. Peterson. Full stride: advancing the state of the art in lower extremity Gait systems. NY: Springer; 2017.
  23. Stergiou N. Biomechanics and Gait Analysis. Academic Press; 2020.
  24. Baker RW. Measuring Walking: A Handbook of Clinical Gait Analysis. London: Mac Keith Press; 2013.
  25. Hoeger WWK, Hopkins DR, Barette SL, Hale DF. Relationship between Repetitions and Selected percentages of One Repetition Maximum: A Comparison between Untrained and Trained Males and Females. J Strength Cond Res. 1990;4(2):47-54. https://doi.org/10.1519/1533-4287(1990)004<0047:RBRASP>2.3.CO;2
  26. Heller J, Peric T, Dlouha R, Kohlikova E, Melichna J, Novakova H. Physiological profiles of male and female taekwon-do (ITF) black belts. J Sports Sci. 1998;16(3):243-249. https://doi.org/10.1080/026404198366768
  27. Schick EE, Coburn JW, Brown LE, et al. A Comparison of Muscle Activation Between a Smith Machine and Free Weight Bench Press. J Strength Cond Res. 2010;24(3):779-784. https://doi.org/10.1519/JSC.0b013e3181cc2237
  28. Yoo JH, Hwang D, Moon KY, Mark SN. Automated Human Recognition by Gait using Neural Network. In: IEEE conference on Robotics and Mechatronics (ICRoM), 2019.
  29. American College of Sports Medicine. American College of Sports Medicine position stand. Progression models in resistance training for healthy adults. Med Sci Sports Exerc. 2009;41(3):687-708. https://doi.org/10.1249/MSS.0b013e3181915670
  30. Ancillao A. Modern Functional Evaluation Methods for Muscle Strength and Gait Analysis. Springer; 2018.
  31. Adams JM, Cerny K. Observational Gait Analysis. Slack Incorporated; 2018
  32. Williams J. The Declaration of Helsinki and public health. Bull World Health Organ. 2008;86(8):650-651. https://doi.org/10.2471/BLT.08.050955
  33. Criswell E, Cram JR, eds. Cram's Introduction to Surface Electromyography. 2nd ed. Jones and Bartlett; 2011.
  34. Nishimura RA, Trusty JM, Hayes DL, et al. Dual-Chamber Pacing for Hypertrophic Cardiomyopathy: A Randomized, Double-Blind, Crossover Trial. J Am Coll Cardiol. 1997;29(2):435-441. https://doi.org/10.1016/S0735-1097(96)00473-1
  35. Green AJ, Gelfand JM, Cree BA, et al. Clemastine fumarate as a remyelinating therapy for multiple sclerosis (ReBUILD): a randomised, controlled, double-blind, crossover trial. The Lancet. 2017;390(10111):2481-2489. https://doi.org/10.1016/S0140-6736(17)32346-2