Citation

Gerin-Lajoie M, Ciombor DM, Warren WH, Aaron RK. Gait Posture 2010; 31(4): 533-536.

Affiliation

Virtual Environment Navigation Laboratory (VENLAB), Department of Cognitive & Linguistic Sciences, Brown University, Providence, RI, USA.

Copyright

(Copyright © 2010, Elsevier Publishing)

DOI

10.1016/j.gaitpost.2010.01.017

PMID

20171105

PMCID

PMC2854238

Abstract

This study aimed to demonstrate the sensitivity of virtual reality (VR)/motion tracking to detect global functional gait impairment resulting from an emulated knee disability as a prelude to describing mobility changes following lower limb injury/treatment. Participants walked in a figure-8 around two virtual posts placed 6m apart while viewing the computer-generated environment in a helmet-mounted display. Three-dimensional position and orientation of the participant's head were tracked and used to update the virtual scenes, measure walking path and speed, and control task parameters with real-time feedback. Participants walked with/without an emulated lower extremity disability (splint preventing normal knee flexion). Participants performed the task at self-selected Natural (NAT) speed providing a baseline measure of their turning speed and area. Turning speed and area were then in turn maintained fixed (controlled speed, CS; controlled path, CP) while the other variable was measured as a gait impairment indicator. Different adaptive strategies were used to cope with the emulated deficit during the NAT scenario: maintaining turning speed while altering path geometry; decreasing turning speed while maintaining path geometry; and combining the previous two strategies. This resulted, on average, in decreased turning speeds and increased turning areas. The CS and CP manipulations respectively generated even greater turning areas and more consistent speed decreases. The three subtests acted as intertwined filters enabling the detection of functional gait impairment in all subjects regardless of their adaptive strategies. This proof-of-concept study demonstrated how VR/motion tracking technology can be used to detect and quantitatively characterize global functional mobility impairment.

Language: en