The effect of virtual visual scene inclination transitions on gait modulation in healthy older versus young adults - a virtual reality study.xlsx

The effect of virtual visual scene inclination transitions on gait modulation in healthy older versus young adults - a virtual reality study- study results.
abstract
Bipedal locomotion requires body adaptation to maintain stability after encountering a transition to incline walking. A major part of this adaptation is reflected by adjusting walking speed. When transitioning to uphill walking, people exert more energy to counteract gravitational forces pulling them backward, while when transitioning to downhill walking people break to avoid uncontrolled acceleration. These behaviors are affected by body-based (proprioception and vestibular) cues as well as by visual cues. Since older age adversely affects walking, it is unclear whether older adults rely on vision during locomotion in a similar manner to younger individuals.
In this study, we tested whether the influence of visual cues on these walking speed modulations in healthy older adults (60-75 years old, N=15) were comparable to those found in healthy young adults (20-40 years old, N=12). Using a fully immersive virtual-reality system embedded with a self-paced treadmill and projected visual scene, we manipulated the inclinations of both the treadmill and the visual scene in an independent manner, and measured participants walking speed. In addition, we also measured individual visual field dependency using the rod and frame test.
The protocol included nine walking conditions that the participant encountered in random order. Inclination of the treadmill (T) and/or visual scenes (V) transitioned to 10° uphill (U), remained leveled at 0° (L) or transitioned to -10° downhill (D).
Outcome measures
To assess the post-transition effects on gait speed, we examined (i) the magnitude of the peak/trough of gait speed relative to the SSV (%); and (ii) the time of this peak/trough after the transition (seconds).
Normalized walking speed
Additionally, we normalized gait speed for each participant in each experimental condition, the process consisted of three steps as follows: (i) gait speed was divided by the averaged SSV at every second, (ii) the ratio between gait speed and SSV was presented as a percentage, and (iii) the normalized trace was shifted so that the mean value of the SSV period would be zero. Following these steps, it was clear to distinguish between the responses of increased and decreased speed following the transition.
Standardized response to virtual inclination
To compute this index, we used data from the incongruent TLVU, TLVD, TDVU, TUVD walking conditions. The averaged absolute values from these four conditions of the peaks/troughs (%) relative to the SSV were calculated for each participant.
Visual field dependence index
In each trial of the rod and frame test, the degree of deviation of the rod from the true upright position was recorded as the position error. For each participant, the mean position error of the seven different frame angles was calculated. Data from all participants were grouped by the frame angle [20]. We defined the visual field dependence index as the average position error when the frame was projected at ±20 degrees (8 trials in total, 4 trials of +20° and 4 trials of -20°). This parameter allowed us to evaluate individual differences in visual field dependence.