Korean Journal of Applied Biomechanics (한국운동역학회지)

Korean Society of Applied Biomechanics (한국운동역학회)
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Effects of Real-time Visual Feedback Gait Training on Gait Stability in Older Adults

실시간 시각적 피드백 보행 훈련이 노인들의 보행 안정성에 미치는 영향

  • Received : 2020.09.07
  • Accepted : 2020.10.06
  • Published : 2020.09.30
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Abstract

Objective: This study aimed to examine the effects of real-time visual feedback gait training on gait stability in older adults. Method: Twelve older adults participated in this study, being divided into 2 groups including a) visual feedback (VF) and b) non-visual feedback (NVF) groups. For 4 weeks, VF performed a treadmill walking training with real-time visual feedback about their postural information while NVF performed a normal treadmill walking training. For evaluations of gait stability, kinematic data of 15-minute treadmill walking were collected from depth-based motion capture system (30 Hz, exbody, Korea). Given that step lengths in both right and left sides were determined based on kinematic data, three variables including step difference, coefficient of variation, approximate entropy were calculated to evaluate gait symmetry, variability and complexity, respectively. Results: For research findings, VF exhibited significant improvements in gait stability after 4-week training in comparison to NVF, particularly in gait symmetry and complexity measures. However, greater improvement in gait variability was observed in NVF than VF. Conclusion: Given that visual feedback walking gives potential effectiveness on gait stability in older adults, gait training with visual feedback may be a robust therapeutic intervention in people with gait disturbances like instability or falls.

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References

  1. Amboni, M., Barone, P. & Hausdorff, J. M. (2013). Cognitive contributions to gait and falls: evidence and implications. Movement Disorders, 28(11), 1520-1533. https://doi.org/10.1002/mds.25674
  2. Aoi, S., Ohashi, T., Bamba, R., Fujiki, S., Tamura, D., Funato, T. ... & Tsuchiya, K. (2019). Neuromusculoskeletal model that walks and runs across a speed range with a few motor control parameter changes based on the muscle synergy hypothesis. Scientific Reports, 9(1), 1-13. https://doi.org/10.1038/s41598-018-37186-2
  3. Ashoori, A., Eagleman, D. M. & Jankovic, J. (2015). Effects of auditory rhythm and music on gait disturbances in Parkinson's disease. Frontiers in Neurology, 6, 234.
  4. Barton, G. J., De Asha, A. R., van Loon, E. C., Geijtenbeek, T. & Robinson, M. A. (2014). Manipulation of visual biofeedback during gait with a time delayed adaptive Virtual Mirror Box. Journal of Neuroengineering and Rehabilitation, 11(1), 101. https://doi.org/10.1186/1743-0003-11-101
  5. Bisi, M. C., Riva, F. & Stagni, R. (2014). Measures of gait stability: performance on adults and toddlers at the beginning of independent walking. Journal of Neuroengineering and Rehabilitation, 11(1), 1-9. https://doi.org/10.1186/1743-0003-11-1
  6. Calabro, R. S., Naro, A., Russo, M., Leo, A., De Luca, R., Balletta, T. ... & Bramanti, P. (2017). The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial. Journal of Neuroengineering and Rehabilitation, 14(1), 53. https://doi.org/10.1186/s12984-017-0268-4
  7. Decker, L. M., Cignetti, F. & Stergiou, N. (2010). Complexity and human gait. Revista Andaluza de Medicina del Deporte, 3(1), 2-12.
  8. Della Croce, U., Riley, P. O., Lelas, J. L. & Kerrigan, D. C. (2001). A refined view of the determinants of gait. Gait & Posture, 14(2), 79-84. https://doi.org/10.1016/S0966-6362(01)00128-X
  9. De Paz, R. H., Serrano-Munoz, D., Perez-Nombela, S., Bravo-Esteban, E., Avendano-Coy, J. & Gomez-Soriano, J. (2019). Combining transcranial direct-current stimulation with gait training in patients with neurological disorders: a systematic review. Journal of Neuroengineering and Rehabilitation, 16(1), 114. https://doi.org/10.1186/s12984-019-0591-z
  10. Floyer-Lea, A. & Matthews, P. M. (2004). Changing brain networks for visuomotor control with increased movement automaticity. Journal of Neurophysiology, 92(4), 2405-2412. https://doi.org/10.1152/jn.01092.2003
  11. Hamacher, D., Hamacher, D., Herold, F. & Schega, L. (2016). Effect of dual tasks on gait variability in walking to auditory cues in older and young individuals. Experimental Brain Research, 234(12), 3555-3563. https://doi.org/10.1007/s00221-016-4754-x
  12. Hamacher, D., Liebl, D., Hodl, C., Hessler, V., Kniewasser, C. K., Thonnessen, T. & Zech, A. (2019). Gait stability and its influencing factors in older adults. Frontiers in Physiology, 9, 1955. https://doi.org/10.3389/fphys.2018.01955
  13. IJmker, T. & Lamoth, C. J. (2012). Gait and cognition: the relationship between gait stability and variability with executive function in persons with and without dementia. Gait & Posture, 35(1), 126-130. https://doi.org/10.1016/j.gaitpost.2011.08.022
  14. Kaipust, J. P., Huisinga, J. M., Filipi, M. & Stergiou, N. (2012). Gait variability measures reveal differences between multiple sclerosis patients and healthy controls. Motor Control, 16(2), 229-244. https://doi.org/10.1123/mcj.16.2.229
  15. Karmakar, C. K., Khandoker, A. H., Begg, R. K., Palaniswami, M. & Taylor, S. (2007). Understanding ageing effects by approximate entropy analysis of gait variability. In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 1965-1968). IEEE.
  16. Kikkert, L. H., De Groot, M. H., van Campen, J. P., Beijnen, J. H., Hortobagyi, T., Vuillerme, N. & Lamoth, C. C. (2017). Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic. PloS One, 12(6), e0178615. https://doi.org/10.1371/journal.pone.0178615
  17. Kim, M. & Won, C. W. (2019). Sarcopenia is associated with cognitive impairment mainly due to slow gait speed: Results from the Korean Frailty and Aging Cohort Study (KFACS). International Journal of Environmental Research and Public Health, 16(9), 1491. https://doi.org/10.3390/ijerph16091491
  18. Kuo, A. D. & Donelan, J. M. (2010). Dynamic principles of gait and their clinical implications. Physical Therapy, 90(2), 157-174. https://doi.org/10.2522/ptj.20090125
  19. LaRoche, D. P., Cook, S. B. & Mackala, K. (2012). Strength asymmetry increases gait asymmetry and variability in older women. Medicine and Science in Sports and Exercise, 44(11), 2172. https://doi.org/10.1249/MSS.0b013e31825e1d31
  20. Ohsugi, H., Ohgi, S., Shigemori, K. & Schneider, E. B. (2013). Differences in dual-task performance and prefrontal cortex activation between younger and older adults. BMC Neuroscience, 14(1), 10. https://doi.org/10.1186/1471-2202-14-10
  21. Perez-Sousa, M. A., Venegas-Sanabria, L. C., Chavarro-Carvajal, D. A., Cano-Gutierrez, C. A., Izquierdo, M., Correa-Bautista, J. E. & Ramirez-Velez, R. (2019). Gait speed as a mediator of the effect of sarcopenia on dependency in activities of daily living. Journal of Cachexia, Sarcopenia and Muscle, 10(5), 1009-1015. https://doi.org/10.1002/jcsm.12444
  22. Preatoni, E., Ferrario, M., Dona, G., Hamill, J. & Rodano, R. (2010). Motor variability in sports: a non-linear analysis of race walking. Journal of Sports Sciences, 28(12), 1327-1336. https://doi.org/10.1080/02640414.2010.507250
  23. Rispens, S. M., Van Dieen, J. H., Van Schooten, K. S., Lizama, L. E. C., Daffertshofer, A., Beek, P. J. & Pijnappels, M. (2016). Fallrelated gait characteristics on the treadmill and in daily life. Journal of Neuroengineering and Rehabilitation, 13(1), 12. https://doi.org/10.1186/s12984-016-0118-9
  24. Stergiou, N. & Decker, L. M. (2011). Human movement variability, nonlinear dynamics, and pathology: Is there a connection? Human Movement Science, 30, 869-888. https://doi.org/10.1016/j.humov.2011.06.002
  25. Tate, J. C. & Milner, C. E. (2010). Real-time kinematic, temporospatial, and kinetic biofeedback during gait retraining in patients: a systematic review. Physical Therapy, 90, 1123-1134. https://doi.org/10.2522/ptj.20080281
  26. Terroso, M., Rosa, N., Marques, A. T. & Simoes, R. (2014). Physical consequences of falls in the elderly: a literature review from 1995 to 2010. European Review of Aging and Physical Activity, 11(1), 51-59. https://doi.org/10.1007/s11556-013-0134-8
  27. Washabaugh, E. P., Augenstein, T. E. & Krishnan, C. (2020). Functional resistance training during walking: Mode of application differentially affects gait biomechanics and muscle activation patterns. Gait & Posture, 75, 129-136. https://doi.org/10.1016/j.gaitpost.2019.10.024
  28. Winter, D. A. (1991). Biomechanics and Motor control of Human Movement. 2nd edition. Wiley-Interscienc Publication, New York: John Wiley & Sons, Inc.
  29. Yentes, J. M., Hunt, N., Schmid, K. K., Kaipust, J. P., McGrath, D. & Stergiou, N. (2013). The appropriate use of approximate entropy and sample entropy with short data sets. Annals of Biomedical Engineering, 41(2), 349-365. https://doi.org/10.1007/s10439-012-0668-3