The Effect of Visual Stimuli on Stability and Complexity of Postural Control

Abstract

Visual input could benefit balance control or increase postural sway, and it is far from fully understanding the effect of visual stimuli on postural stability and its underlying mechanism. In this study, the effect of different visual inputs on stability and complexity of postural control was examined by analyzing the mean velocity (MV), SD, and fuzzy approximate entropy (fApEn) of the center of pressure (COP) signal during quiet upright standing. We designed five visual exposure conditions: eyes-closed, eyes-open (EO), and three virtual reality (VR) scenes (VR1–VR3). The VR scenes were a limited field view of an optokinetic drum rotating around yaw (VR1), pitch (VR2), and roll (VR3) axes, respectively. Sixteen healthy subjects were involved in the experiment, and their COP trajectories were assessed from the force plate data. MV, SD, and fApEn of the COP in anterior–posterior (AP), medial–lateral (ML) directions were calculated. Two-way analysis of variance with repeated measures was conducted to test the statistical significance. We found that all the three parameters obtained the lowest values in the EO condition, and highest in the VR3 condition. We also found that the active neuromuscular intervention, indicated by fApEn, in response to changing the visual exposure conditions were more adaptive in AP direction, and the stability, indicated by SD, in ML direction reflected the changes of visual scenes. MV was found to capture both instability and active neuromuscular control dynamics. It seemed that the three parameters provided compensatory information about the postural control in the immersive virtual environment.

Postural Control Disturbances Induced by Virtual Reality in Stroke Patients

“…In our study, challenging VE led to more pronounced postural perturbation in SP than in HA, which is consistent with their strong reliance on visual information [5]. Furthermore, in contrast to other studies evaluating the effect of VR on postural control [12,13,15], we proposed a multiple complex task with various optical flow induced by changing the density and avoidance space of avatars in a crowded environment. All in all, we suggest that immersive and various ecological virtual environment conditions can be used in SP virtual reality rehabilitation programs with progressive challenging situations.…”

“…Previous work indicates that static virtual environments (VE) do not appear to challenge postural control [12,13] whereas dynamic scenes induce postural perturbations in healthy young adults (HA) [12] and older adults [14]. However, D'Antonio et al [15] reported lesser postural perturbations in SP and older HA compared with young HA in semi-immersive environment.…”

Differences in the effect of sleep deprivation on the postural stability among men and women

“…Visual information may lead to both abnormal postural control of the body and its improvement [29]. In our study, the elimination of visual control resulted in higher COP path length values compared to the open eye study in the experimental and control group.…”

Triggering Postural Movements With Virtual Reality Technology in Healthy Young and Older Adults: A Cross-Sectional Validation Study for Early Dementia Screening

“…The result showed significant differences in the sway velocity between with and without VR environments and between open and closed VR sceneries. Similarly, HMD-based VR was used to generate visual stimuli and the effect of stimuli on postural control was evaluated under the conditions of eyes-open, eyes-closed, and three different VR designs; e.g., an optokinetic drum rotating around yaw, pitch, and roll axes, respectively ( 29 ). This research also reported differences between with and without VR environments in postural sway behavior of healthy YA.…”

“…We focused on analyzing velocity of postural sway because a meta-analysis found that significant differences were observed in sway velocity for an MCI group ( 13 ). In addition, a few studies developing a similar assessment system showed that sway speed was a sensitive dependent variable ( 28 , 29 ). We calculated the mean body sway velocity ( MV ) over 50 s after removing the initial 10 s of data to eliminate unusual movements caused by eye focus adjustment in the VR headset.…”