Analyses of Gait Parameters of Younger and Older Adults During (Non-)Isometric Virtual Walking.

Abstract

Understanding real walking in virtual environments (VEs) is important for immersive experiences, allowing users to move through VEs in the most natural way. Previous studies have shown that basic implementations of real walking in virtual spaces, in which head-tracked movements are mapped isometrically to a VE, are not estimated as entirely natural. Instead, users estimate a virtual walking velocity as more natural when it is slightly increased compared to the user's physical locomotion. However, these findings have been reported in most cases only for young persons, e.g., students, whereas older adults are clearly underrepresented in such studies. Recently, virtual reality (VR) has received significant public and media attention. Therefore, it appears reasonable to assume that people at different ages will have access to VR, and might use this technology more and more in application scenarios such as rehabilitation or training. To better understand how people at different ages walk and perceive locomotion in VR, we have performed a study to investigate the effects of (non-)isometric mappings between physical movements and virtual motions in the VE on the walking biomechanics across generations, i.e., younger and older adults. Three primary domains (pace, base of support and phase) of spatio-temporal parameters were identified to evaluate gait performance. The results show that the older adults walked very similar in the real and VE in the pace and phasic domains, which differs from results found in younger adults. In contrast, the results indicate differences in terms of base of support domain parameters for both groups while walking within a VE and the real world. For non-isometric mappings, we found in both younger and older adults an increased divergence of gait parameters in all domains correlating with the up- or down-scaled velocity of visual self-motion feedback. The results provide important insights into the design of future VR applications for older adults in domains ranging from medicine and psychology to rehabilitation.