Visually fixating or tracking another person decreases balance control in young and older females walking in a real-world scenario

People with Long Covid and ME/CFS Exhibit Similarly Impaired Balance and Physical Capacity: A Case-Case-Control Study

PURPOSE

Postural sway and physical capacity had not previously been compared between people with long COVID and people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Therefore, this study determined postural sway and physical capacity in people with long COVID (∼16-month illness duration; n = 21) and ME/CFS (∼16-year illness duration; n = 20), vs age-matched healthy controls (n = 20).

METHODS

Postural sway was during a 30-s static stand test. Physical capacity was determined using the Timed Up and Go test and 5 Times Sit to Stand test. Throughout, participants wore isoinertial measurement units.

RESULTS

Postural sway was worse (ie, greater) in people with long COVID and ME/CFS than controls, but not different between long COVID and ME/CFS. Performance of the Timed Up and Go test and 5 Times Sit to Stand test were worse in long COVID and ME/CFS than controls, but not different between long COVID and ME/CFS. Of long COVID and ME/CFS participants, 87% and 13% exceeded the threshold for muscle weakness in the 5 Times Sit to Stand test and Timed Up and Go test, respectively.

CONCLUSIONS

These data suggest that both people with long COVID and people with ME/CFS have similarly impaired balance and physical capacity. Therefore, there is an urgent need for interventions to target postural sway and physical capacity in people with ME/CFS, and given the current pandemic, people with long COVID.

Keeping balance during head-free smooth pursuit: The role of aging

Standing balance is often more unstable when visually pursuing a moving target than when fixating on a stationary one. These effects are common in both young and older adults when the head is restrained during visual task performance. The present study focused on the role of head motion on standing balance during smooth pursuit as a function of age. Three predictions were tested: a) standing balance is compromised to a greater extent in older than young adults by gaze target pursuit compared to fixation, b) older adults pursue a moving target with greater and more variable head rotation than young adults, and c) greater and more variable head rotation during the smooth pursuit task is associated with greater Center of Pressure (CoP) sway. Twenty-two (22) older (age: 71.7 ± 8.1, 12 M / 10 F) and twenty-three (23) young adults (age: 23.6 ± 2.5, 12 M / 11 F) stood on a force plate while either fixating a stationary or smoothly pursuing a horizontally moving target (31.9° peak-to-peak visual angle). CoP (Bertec Balance Plate), head kinematics (Vicon Motion Analysis) and head-unconstrained gaze (Pupil Labs Invisible) were synchronously recorded. The root means square (RMS) of CoP velocity increased during smooth pursuit compared to fixation regardless of age (p < .05), while the interquartile CoP range increased only in older and not in young participants (p < .05). We also calculated the head rotation range (peak to peak cycle amplitude) of motion and variability (SD of range of motion) across the cycles of the smooth pursuit task. Older adults pursued the moving target employing more variable (p = .022) head yaw rotation than young participants although the mean range of head rotation was similar between groups (p =. 077). The amplitude and variability of head yaw rotation did not correlate with CoP sway measures. Results suggest that head-free pursuing of a moving target decreased balance to a greater extent in old than young individuals when compared to fixation. Nevertheless, postural sway during head-free smooth pursuit was not associated with the extent or variability of head rotation.

Visual oscillation effects on dynamic balance control in people with multiple sclerosis

Background

People with multiple sclerosis (PwMS) have balance deficits while ambulating through environments that contain moving objects or visual manipulations to perceived self-motion. However, their ability to parse object from self-movement has not been explored. The purpose of this research was to examine the effect of medial–lateral oscillations of the visual field and of objects within the scene on gait in PwMS and healthy age-matched controls using virtual reality (VR).

Methods

Fourteen PwMS (mean age 49 ± 11 years, functional gait assessment score of 27.8 ± 1.8, and Berg Balance scale score 54.7 ± 1.5) and eleven healthy controls (mean age: 53 ± 12 years) participated in this study. Dynamic balance control was assessed while participants walked on a treadmill at a self-selected speed while wearing a VR headset that projected an immersive forest scene. Visual conditions consisted of (1) no visual manipulations (speed-matched anterior/posterior optical flow), (2) 0.175 m mediolateral translational oscillations of the scene that consisted of low pairing (0.1 and 0.31 Hz) or (3) high pairing (0.15 and 0.465 Hz) frequencies, (4) 5 degree medial–lateral rotational oscillations of virtual trees at a low frequency pairing (0.1 and 0.31 Hz), and (5) a combination of the tree and scene movements in (3) and (4).

Results

We found that both PwMS and controls exhibited greater instability and visuomotor entrainment to simulated mediolateral translation of the visual field (scene) during treadmill walking. This was demonstrated by significant (p < 0.05) increases in mean step width and variability and center of mass sway. Visuomotor entrainment was demonstrated by high coherence between center of mass sway and visual motion (magnitude square coherence = ~ 0.5 to 0.8). Only PwMS exhibited significantly greater instability (higher step width variability and center of mass sway) when objects moved within the scene (i.e., swaying trees).

Conclusion

Results suggest the presence of visual motion processing errors in PwMS that reduced dynamic stability. Specifically, object motion (via tree sway) was not effectively parsed from the observer’s self-motion. Identifying this distinction between visual object motion and self-motion detection in MS provides insight regarding stability control in environments with excessive external movement, such as those encountered in daily life.