Physical Therapy Rehabilitation Science

korean Academy of Physical Therapy Rehabilitation Science (물리치료재활과학회)
권호 표지
DOI QR코드

DOI QR Code

Effect of Robot-Assisted Wearable Exoskeleton on Gait Speed of Post-Stroke Patients: A Systematic Review and Meta-Analysis of a Randomized Controlled Trials

  • Chankyu Kim (Department of Physical Therapy, Gwangju Health University) ;
  • Hyun-Joong Kim (Department of Physical Therapy, Gwangju Health University)
  • Received : 2022.12.11
  • Accepted : 2022.12.20
  • Published : 2022.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Objective: The greatest motor impairment after stroke is a decreased ability to walk. Most stroke patients achieve independent gait, but approximately 70% do not reach normal speed, making it difficult to reach a standard of daily living. Therefore, a wearable exoskeleton is recommended for optimal independent gait because different residual disorders hinder motor function after stroke. This review synthesized the effect on gait speed in randomized controlled trials (RCTs) in which gait training using a wearable exoskeleton was performed on post-stroke patients for qualitative and quantitative analysis. Design: A systematic review and meta-analysis of a randomized controlled trials Methods: RCTs using wearable exoskeletons in robotic rehabilitation of post-stroke patients were extracted from an international electronic database. For quality assessment and quantitative analysis, RevMan 5.4 was used. Quantitative analysis was calculated as the standardized mean difference (SMD) and presented as a random effect model. Results: Five studies involving 197 post-stroke patients were included in this review. As a result of the analysis using a random effect model, gait training using a wearable exoskeleton in post-stroke patients showed a significant improvement in gait speed compared to the non-wearing exoskeleton (SMD=1.15, 95% confidence interval: 0.52 to 1.78). Conclusions: This study concluded that a wearable exoskeleton was more effective than conventional gait training in improving the gait speed in post-stroke patients.

Keywords

Acknowledgement

The Research has been conducted by the Research Grant of Gwangju Health University in 2022 (2022005).

References

  1. Kwakkel G, Kollen BJ, Wagenaar RC. Therapy impact on functional recovery in stroke rehabilitation: a critical review of the literature. Physiotherapy. 1999;85:377-91.  https://doi.org/10.1016/S0031-9406(05)67198-2
  2. Schmidt H, Werner C, Bernhardt R, Hesse S, Kruger J. Gait rehabilitation machines based on programmable footplates. J Neuroeng Rehabil. 2007;4:1-7.  https://doi.org/10.1186/1743-0003-4-1
  3. Evers SM, Struijs JN, Ament AJ, van Genugten ML, Jager JC, van den Bos GA. International comparison of stroke cost studies. Stroke. 2004;35:1209-15.  https://doi.org/10.1161/01.STR.0000125860.48180.48
  4. Flansbjer U-B, Holmback AM, Downham D, Patten C, Lexell J. Reliability of gait performance tests in men and women with hemiparesis after stroke. J Rehabil Med. 2005;37:75-82.  https://doi.org/10.1080/16501970410017215
  5. Hesse S, Mehrholz J, Werner C. Robot-assisted upper and lower limb rehabilitation after stroke: walking and arm/hand function. Dtsch Arztebl Int. 2008;105:330. 
  6. Wall A, Borg J, Palmcrantz S. Clinical application of the Hybrid Assistive Limb (HAL) for gait training-a systematic review. Front Syst Neurosci. 2015;9:48. 
  7. Louie DR, Eng JJ. Powered robotic exoskeletons in post-stroke rehabilitation of gait: a scoping review. J Neuroeng Rehabil. 2016;13:1-10.  https://doi.org/10.1186/s12984-015-0109-2
  8. Chen G, Chan CK, Guo Z, Yu H. A review of lower extremity assistive robotic exoskeletons in rehabilitation therapy. Crit Rev Biomed Eng. 2013;41. 
  9. Carpino G, Pezzola A, Urbano M, Guglielmelli E. Assessing effectiveness and costs in robot-mediated lower limbs rehabilitation: a meta-analysis and state of the art. J Healthc Eng. 2018;2018. 
  10. Bruni MF, Melegari C, De Cola MC, Bramanti A, Bramanti P, Calabro RS. What does best evidence tell us about robotic gait rehabilitation in stroke patients: a systematic review and meta-analysis. J Clin Neurosci. 2018;48:11-7.  https://doi.org/10.1016/j.jocn.2017.10.048
  11. Rossi S, Colazza A, Petrarca M, Castelli E, Cappa P, Krebs HI. Feasibility study of a wearable exoskeleton for children: is the gait altered by adding masses on lower limbs? PloS one. 2013;8:e73139. 
  12. Saglia JA, Tsagarakis NG, Dai JS, Caldwell DG. A high-performance redundantly actuated parallel mechanism for ankle rehabilitation. Int J Rob Res. 2009;28:1216-27.  https://doi.org/10.1177/0278364909104221
  13. Meng W, Liu Q, Zhou Z, Ai Q, Sheng B, Xie SS. Recent development of mechanisms and control strategies for robot-assisted lower limb rehabilitation. Mechatronics. 2015;31:132-45.  https://doi.org/10.1016/j.mechatronics.2015.04.005
  14. Oh W, Park C, Oh S, You SJH. Stage 2: Who Are the Best Candidates for Robotic Gait Training Rehabilitation in Hemiparetic Stroke? J Clin Med. 2021;10:5715. 
  15. Akdogn E, Adli MA. The design and control of a therapeutic exercise robot for lower limb rehabilitation: Physiotherabot. Mechatronics. 2011;21:509-22.  https://doi.org/10.1016/j.mechatronics.2011.01.005
  16. Kim H, Jung J, Park S, Joo Y, Lee S, Lee S. Effects of Repetitive Transcranial Magnetic Stimulation on the Primary Motor Cortex of Individuals with Fibromyalgia: A Systematic Review and Meta-Analysis. Brain Sci. 2022;12:570. 
  17. Buesing C, Fisch G, O'Donnell M, Shahidi I, Thomas L, Mummidisetty CK, et al. Effects of a wearable exoskeleton stride management assist system (SMA®) on spatiotemporal gait characteristics in individuals after stroke: a randomized controlled trial. J Neuroeng Rehabil. 2015;12:1-14.  https://doi.org/10.1186/1743-0003-12-1
  18. Jayaraman A, O'brien MK, Madhavan S, Mummidisetty CK, Roth HR, Hohl K, et al. Stride management assist exoskeleton vs functional gait training in stroke: a randomized trial. Neurology. 2019;92:e263-e73.  https://doi.org/10.1212/WNL.0000000000006782
  19. Lee H-J, Lee S-H, Seo K, Lee M, Chang WH, Choi B-O, et al. Training for walking efficiency with a wearable hip-assist robot in patients with stroke: a pilot randomized controlled trial. Stroke. 2019;50:3545-52.  https://doi.org/10.1161/STROKEAHA.119.025950
  20. Watanabe H, Goto R, Tanaka N, Matsumura A, Yanagi H. Effects of gait training using the Hybrid Assistive Limb® in recovery-phase stroke patients: a 2-month follow-up, randomized, controlled study. NeuroRehabilitation. 2017;40:363-7.  https://doi.org/10.3233/NRE-161424
  21. Yeung L-F, Lau CC, Lai CW, Soo YO, Chan M-L, Tong RK. Effects of wearable ankle robotics for stair and over-ground training on sub-acute stroke: a randomized controlled trial. J Neuroeng Rehabil. 2021;18:1-10.  https://doi.org/10.1186/s12984-020-00774-3
  22. Babic A, Pijuk A, Brazdilova L, Georgieva Y, Raposo Pereira MA, Poklepovic Pericic T, et al. The judgement of biases included in the category "other bias" in Cochrane systematic reviews of interventions: a systematic survey. BMC Med Res Methodol. 2019;19:1-10.  https://doi.org/10.1186/s12874-018-0650-3
  23. Page MJ, Higgins JP, Sterne JA. Assessing risk of bias due to missing results in a synthesis. Cochrane Database Syst Rev. 2019:349-74. 
  24. Mehrholz J, Thomas S, Kugler J, Pohl M, Elsner B. Electromechanical-ssisted training for walking after stroke. Cochrane Database Syst Rev. 2020. 
  25. Schwartz I, Meiner Z. Robotic-assisted gait training in neurological patients: who may benefit? Ann Biomed Eng. 2015;43:1260-9.  https://doi.org/10.1007/s10439-015-1283-x
  26. Lamontagne A, Fung J. Faster is better: implications for speed-intensive gait training after stroke. Stroke. 2004;35:2543-8.  https://doi.org/10.1161/01.STR.0000144685.88760.d7
  27. Patterson KK, Gage WH, Brooks D, Black SE, McIlroy WE. Changes in gait symmetry and velocity after stroke: a cross-sectional study from weeks to years after stroke. Neurorehabil Neural Repair. 2010;24:783-90.  https://doi.org/10.1177/1545968310372091
  28. Guzik A, Druzbicki M, Przysada G, Kwolek A, Brzozowska-Magon A, Sobolewski M. Relationships between walking velocity and distance and the symmetry of temporospatial parameters in chronic post-stroke subjects. Acta Bioeng Biomech. 2017;19. 
  29. Lee S-H, Lee H-J, Shim Y, Chang WH, Choi B-O, Ryu G-H, et al. Wearable hip-assist robot modulates cortical activation during gait in stroke patients: a functional near-infrared spectroscopy study. J Neuroeng Rehabil. 2020;17:1-8. https://doi.org/10.1186/s12984-019-0634-5