Walking with head-mounted virtual and augmented reality devices: Effects on position control and gait biomechanics

Autoři: Zoe Y. S. Chan aff001;  Aislinn J. C. MacPhail aff001;  Ivan P. H. Au aff001;  Janet H. Zhang aff001;  Ben M. F. Lam aff001;  Reed Ferber aff002;  Roy T. H. Cheung aff001
Působiště autorů: Gait & Motion Analysis Lab, Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom Bay, Hong Kong S.A.R aff001;  Running Injury Clinic, University of Calgary, Calgary, Canada aff002;  Faculties of Kinesiology, Nursing, and Cumming School of Medicine, University of Calgary, Calgary, Canada aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0225972


What was once a science fiction fantasy, virtual reality (VR) technology has evolved and come a long way. Together with augmented reality (AR) technology, these simulations of an alternative environment have been incorporated into rehabilitation treatments. The introduction of head-mounted displays has made VR/AR devices more intuitive and compact, and no longer limited to upper-limb rehabilitation. However, there is still limited evidence supporting the use of VR and AR technology during locomotion, especially regarding the safety and efficacy relating to walking biomechanics. Therefore, the objective of this study is to explore the limitations of such technology through gait analysis. In this study, thirteen participants walked on a treadmill in normal, virtual and augmented versions of the laboratory environment. A series of spatiotemporal parameters and lower-limb joint angles were compared between conditions. The center of pressure (CoP) ellipse area (95% confidence ellipse) was significantly different between conditions (p = 0.002). Pairwise comparisons indicated a significantly greater CoP ellipse area for both the AR (p = 0.002) and VR (p = 0.005) conditions when compared to the normal laboratory condition. Furthermore, there was a significant difference in stride length (p<0.001) and cadence (p<0.001) between conditions. No statistically significant difference was found in the hip, knee and ankle joint kinematics between the three conditions (p>0.082), except for maximum ankle plantarflexion (p = 0.001). These differences in CoP ellipse area indicate that users of head-mounted VR/AR devices had difficulty maintaining a stable position on the treadmill. Also, differences in the gait parameters suggest that users walked with an unusual gait pattern which could potentially affect the effectiveness of gait rehabilitation treatments. Based on these results, position guidance in the form of feedback and the use of specialized treadmills should be considered when using head-mounted VR/AR devices.

Klíčová slova:

Ankles – Biomechanics – Ellipses – Gait analysis – Gait rehabilitation – Virtual reality – Walking – Retraining


1. Corbetta D, Imeri F, Gatti R. Rehabilitation that incorporates virtual reality is more effective than standard rehabilitation for improving walking speed, balance and mobility after stroke: a systematic review. J Physiother. 2015;61: 117–124. doi: 10.1016/j.jphys.2015.05.017 26093805

2. Chen Y, Fanchiang HD, Howard A. Effectiveness of Virtual Reality in Children With Cerebral Palsy: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Phys Ther. 2018;98: 63–77. doi: 10.1093/ptj/pzx107 29088476

3. Massetti T, Trevizan IL, Arab C, Favero FM, Ribeiro-Papa DC, de Mello Monteiro CB. Virtual reality in multiple sclerosis—A systematic review. Mult Scler Relat Disord. 2016;8: 107–112. doi: 10.1016/j.msard.2016.05.014 27456884

4. Levin MF, Weiss PL, Keshner EA. Emergence of Virtual Reality as a Tool for Upper Limb Rehabilitation: Incorporation of Motor Control and Motor Learning Principles. Phys Ther. 2015;95: 415–425. doi: 10.2522/ptj.20130579 25212522

5. Cho KH, Lee WH. Effect of treadmill training based real-world video recording on balance and gait in chronic stroke patients: A randomized controlled trial. Gait Posture. 2014;39: 523–528. doi: 10.1016/j.gaitpost.2013.09.003 24091250

6. Peruzzi A, Zarbo IR, Cereatti A, Della Croce U, Mirelman A. An innovative training program based on virtual reality and treadmill: effects on gait of persons with multiple sclerosis. Disabil Rehabil. 2017;39: 1557–1563. doi: 10.1080/09638288.2016.1224935 27808596

7. Borrego A, Latorre J, Llorens R, Alcañiz M, Noé E. Feasibility of a walking virtual reality system for rehabilitation: objective and subjective parameters. J Neuroeng Rehabil. 2016;13: 68. doi: 10.1186/s12984-016-0174-1 27503112

8. Kang H-K, Kim Y, Chung Y, Hwang S. Effects of treadmill training with optic flow on balance and gait in individuals following stroke: randomized controlled trials. Clin Rehabil. 2012;26: 246–255. doi: 10.1177/0269215511419383 21971754

9. Jaffe DL, Brown DA, Pierson-Carey CD, Buckley EL, Lew HL. Stepping over obstacles to improve walking in individuals with poststroke hemiplegia. J Rehabil Res Dev. 2004;41: 283–292. doi: 10.1682/jrrd.2004.03.0283 15543446

10. Cheung RTH, Ho KKW, Au IPH, An WW, Zhang HW, Chan ZYS, et al. Immediate and short-term effects of gait retraining on the knee joint moments and symptoms in patients with early tibiofemoral joint osteoarthritis: a randomized controlled trial. Osteoarthr Cartil. 2018. doi: 10.1016/j.joca.2018.07.011 30081075

11. Crowell HP, Davis IS. Gait retraining to reduce lower extremity loading in runners. Clin Biomech. 2011;26: 78–83. doi: 10.1016/j.clinbiomech.2010.09.003 20888675

12. Davis IS, Futrell E. Gait Retraining: Altering the Fingerprint of Gait. Phys Med Rehabil Clin N Am. 2016;27: 339–355. doi: 10.1016/j.pmr.2015.09.002 26616188

13. Keshner EA, Fung J. The quest to apply VR technology to rehabilitation: tribulations and treasures. J Vestib Res. 2017;27: 1–5. doi: 10.3233/VES-170610 28387695

14. Beek PJ, Roerdink M. Evolving insights into motor learning and their implications for neurorehabilitation. 2nd ed. In: Selzer M, Clarke S, Cohen LG, Kwakkel G, Miller R, editors. Textbook of Neural Repair and Rehabilitation. 2nd ed. Cambridge: Cambridge University Press; 2014. pp. 95–104. doi: 10.1017/CBO9780511995590.012

15. Malone LA, Bastian AJ. Thinking About Walking: Effects of Conscious Correction Versus Distraction on Locomotor Adaptation. J Neurophysiol. 2010;103: 1954–1962. doi: 10.1152/jn.00832.2009 20147417

16. Braun DA, Aertsen A, Wolpert DM, Mehring C. Motor task variation induces structural learning. Curr Biol. 2009;19: 352–357. doi: 10.1016/j.cub.2009.01.036 19217296

17. Shea JB, Morgan RL. Contextual interference effects on the acquisition, retention, and transfer of a motor skill. J Exp Psychol Hum Learn. 1979;5: 179–187. doi: 10.1037/0278-7393.5.2.179

18. Proffitt R, Lange B. Considerations in the efficacy and effectiveness of virtual reality interventions for stroke rehabilitation: moving the field forward. Phys Ther. 2015;95: 441–448. doi: 10.2522/ptj.20130571 25343960

19. Brunner I, Skouen JS, Hofstad H, Aßmuss J, Becker F, Pallesen H, et al. Is upper limb virtual reality training more intensive than conventional training for patients in the subacute phase after stroke? An analysis of treatment intensity and content. BMC Neurol. 2016;16: 219. doi: 10.1186/s12883-016-0740-y 27835977

20. Luque-Moreno C, Ferragut-Garcías A, Rodríguez-Blanco C, Heredia-Rizo AM, Oliva-Pascual-Vaca J, Kiper P, et al. A Decade of Progress Using Virtual Reality for Poststroke Lower Extremity Rehabilitation: Systematic Review of the Intervention Methods. BioMed Res Int. 2015;2015: 1–7. doi: 10.1155/2015/342529 26539480

21. Kim A, Darakjian N, Finley JM. Walking in fully immersive virtual environments: an evaluation of potential adverse effects in older adults and individuals with Parkinson’s disease. J Neuroeng Rehabil. 2017;14: 16. doi: 10.1186/s12984-017-0225-2 28222783

22. Moreira MC, de Amorim Lima AM, Ferraz KM, Benedetti Rodrigues MA. Use of virtual reality in gait recovery among post stroke patients–a systematic literature review. Disabil Rehabil Assist Technol. 2013;8: 357–362. doi: 10.3109/17483107.2012.749428 23614694

23. Yang Y-R, Tsai M-P, Chuang T-Y, Sung W-H, Wang R-Y. Virtual reality-based training improves community ambulation in individuals with stroke: A randomized controlled trial. Gait Posture. 2008;28: 201–206. doi: 10.1016/j.gaitpost.2007.11.007 18358724

24. Menegoni F, Albani G, Bigoni M, Priano L, Trotti C, Galli M, et al. Walking in an immersive virtual reality. Stud Health Technol Inform. 2009;144: 72–76. doi: 10.3233/978-1-60750-017-9-72 19592734

25. Hollman JH, Brey RH, Robb RA, Bang TJ, Kaufman KR. Spatiotemporal gait deviations in a virtual reality environment. Gait Posture. 2006;23: 441–444. doi: 10.1016/j.gaitpost.2005.05.005 16095905

26. Ardestani MM, Ferrigno C, Moazen M, Wimmer MA. From normal to fast walking: Impact of cadence and stride length on lower extremity joint moments. Gait Posture. 2016;46: 118–125. doi: 10.1016/j.gaitpost.2016.02.005 27131188

27. Hondori HM, Khademi M, Dodakian L, Cramer SC, Lopes CV. A Spatial Augmented Reality Rehab System for Post-Stroke Hand Rehabilitation. Stud Health Technol Inform. 2013;184: 279–285. doi: 10.3233/978-1-61499-209-7-279 23400171

28. Hollands KL, Pelton TA, Wimperis A, Whitham D, Tan W, Jowett S, et al. Feasibility and Preliminary Efficacy of Visual Cue Training to Improve Adaptability of Walking after Stroke: Multi-Centre, Single-Blind Randomised Control Pilot Trial. Quinn TJ, editor. PLoS One. 2015;10: e0139261. doi: 10.1371/journal.pone.0139261 26445137

29. van Ooijen MW, Roerdink M, Trekop M, Janssen TWJ, Beek PJ. The efficacy of treadmill training with and without projected visual context for improving walking ability and reducing fall incidence and fear of falling in older adults with fall-related hip fracture: a randomized controlled trial. BMC Geriatr. 2016;16: 215. doi: 10.1186/s12877-016-0388-x 28031021

30. Silva WHS, Lopes GLB, Yano KM, Tavares NSA, Rego IAO, Cavalcanti FA da C. Effect of a rehabilitation program using virtual reality for balance and functionality of chronic stroke patients. Motriz. 2015;21: 237–243. doi: 10.1590/S1980-65742015000300003

31. Peruzzi A, Cereatti A, Della Croce U, Mirelman A. Effects of a virtual reality and treadmill training on gait of subjects with multiple sclerosis: a pilot study. Mult Scler Relat Disord. 2016;5: 91–96. doi: 10.1016/j.msard.2015.11.002 26856951

32. Hollman JH, Brey RH, Bang TJ, Kaufman KR. Does walking in a virtual environment induce unstable gait? Gait Posture. 2007;26: 289–294. doi: 10.1016/j.gaitpost.2006.09.075 17056258

33. Wall JC, Charteris J. A kinematic study of long-term habituation to treadmill walking. Ergonomics. 1981;24: 531–542. doi: 10.1080/00140138108924874 7333270

34. Full body modeling with Plug-in Gait—Nexus 2.6 Documentation—Vicon Documentation. [cited 26 Jun 2019]. Available: https://docs.vicon.com/display/Nexus26/Full+body+modeling+with+Plug-in+Gait#FullbodymodelingwithPlug-inGait-MarkersetsforPlug-inGaitfullbodymodeling

35. Kadaba MP, Ramakrishnan HK, Wootten ME. Measurement of lower extremity kinematics during level walking. J Orthop Res. 1990;8: 383–392. doi: 10.1002/jor.1100080310 2324857

36. Winter DA. Biomechanics and motor control of human movement. 4th ed. Hoboken, N.J: Wiley; 2009.

37. Ogdon DC. Hololens and Vive Pro: Virtual Reality Headsets. J Med Libr Assoc. 2019;107: 118–121. doi: 10.5195/jmla.2019.602

38. Desai PR, Desai PN, Ajmera KD, Mehta K. A Review Paper on Oculus Rift-A Virtual Reality Headset. IJETT. 2014;13: 175–179. doi: 10.14445/22315381/IJETT-V13P237

39. Zeni JA, Richards JG, Higginson JS. Two simple methods for determining gait events during treadmill and overground walking using kinematic data. Gait Posture. 2008;27: 710–714. doi: 10.1016/j.gaitpost.2007.07.007 17723303

40. Santos-Concejero J, Oliván J, Maté-Muñoz JL, Muniesa C, Montil M, Tucker R, et al. Gait-Cycle Characteristics and Running Economy in Elite Eritrean and European Runners. Int J Sports Physiol Perform. 2015;10: 381–387. doi: 10.1123/ijspp.2014-0179 25310728

41. Schubert P, Kirchner M. Ellipse area calculations and their applicability in posturography. Gait Posture. 2014;39: 518–522. doi: 10.1016/j.gaitpost.2013.09.001 24091249

42. Sinclair J. The influence of minimalist, maximalist and conventional footwear on impact shock attenuation during running. Mov Sport Sci/Sci Mot. 2017; 59–64. doi: 10.1051/sm/2016010

43. Saunders JA. Reliability and relative weighting of visual and nonvisual information for perceiving direction of self-motion during walking. J Vis. 2014;14: 24–24. doi: 10.1167/14.3.24 24648194

44. Warren WH, Kay BA, Zosh WD, Duchon AP, Sahuc S. Optic flow is used to control human walking. Nat Neurosci. 2001;4: 213–216. doi: 10.1038/84054 11175884

45. Siegel ZD, Kelly JW. Walking through a virtual environment improves perceived size within and beyond the walked space. Atten Percept Psychophys. 2017;79: 39–44. doi: 10.3758/s13414-016-1243-z 27914094

46. Ng AKT, Chan LKY, Lau HYK. Depth Perception in Virtual Environment: The Effects of Immersive System and Freedom of Movement. In: Lackey S, Shumaker R, editors. Virtual, Augmented and Mixed Reality. Cham: Springer International Publishing; 2016. pp. 173–183. doi: 10.1007/978-3-319-39907-2_17

47. Maki BE. Gait changes in older adults: predictors of falls or indicators of fear. J Am Geriatr Soc. 1997;45: 313–320. doi: 10.1111/j.1532-5415.1997.tb00946.x 9063277

48. Hallemans A, Ortibus E, Meire F, Aerts P. Low vision affects dynamic stability of gait. Gait Posture. 2010;32: 547–551. doi: 10.1016/j.gaitpost.2010.07.018 20801658

49. Liu MQ, Anderson FC, Pandy MG, Delp SL. Muscles that support the body also modulate forward progression during walking. J Biomech. 2006;39: 2623–2630. doi: 10.1016/j.jbiomech.2005.08.017 16216251

50. McGowan CP, Neptune RR, Kram R. Independent effects of weight and mass on plantar flexor activity during walking: implications for their contributions to body support and forward propulsion. J Appl Physiol. 2008;105: 486–494. doi: 10.1152/japplphysiol.90448.2008 18556431

51. Lee J, Ahn SC, Hwang J-I. A Walking-in-Place Method for Virtual Reality Using Position and Orientation Tracking. Sensors. 2018;18: 2832. doi: 10.3390/s18092832 30150586

52. Jung J, Yu J, Kang H. Effects of Virtual Reality Treadmill Training on Balance and Balance Self-efficacy in Stroke Patients with a History of Falling. J Phys Ther Sci. 2012;24: 1133–1136. doi: 10.1589/jpts.24.1133

53. Munafo J, Diedrick M, Stoffregen TA. The virtual reality head-mounted display Oculus Rift induces motion sickness and is sexist in its effects. Exp Brain Res. 2017;235: 889–901. doi: 10.1007/s00221-016-4846-7 27915367

54. Ohyama S, Nishiike S, Watanabe H, Matsuoka K, Akizuki H, Takeda N, et al. Autonomic responses during motion sickness induced by virtual reality. Auris Nasus Larynx. 2007;34: 303–306. doi: 10.1016/j.anl.2007.01.002 17336009

55. Fukuchi CA, Fukuchi RK, Duarte M. Effects of walking speed on gait biomechanics in healthy participants: a systematic review and meta-analysis. Syst Rev. 2019;8: 153. doi: 10.1186/s13643-019-1063-z 31248456

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2019 Číslo 12