Exploring the effects of degraded vision on sensorimotor performance

Abstract

Purpose: Many people experience unilateral degraded vision, usually owing to a developmental or age-related disorder. There are unresolved questions regarding the extent to which such unilateral visual deficits impact on sensorimotor performance; an important issue as sensorimotor limitations can constrain quality of life by restricting 'activities of daily living'. Examination of the relationship between visual deficit and sensorimotor performance is essential for determining the functional implications of ophthalmic conditions. This study attempts to explore the effect of unilaterally degraded vision on sensorimotor performance.

Methods: In Experiment 1 we simulated visual deficits in 30 participants using unilateral and bilateral Bangerter filters to explore whether motor performance was affected in water pouring, peg placing, and aiming tasks. Experiment 2 (n = 74) tested the hypothesis that kinematic measures are associated with visuomotor deficits by measuring the impact of small visual sensitivity decrements created by monocular viewing on sensorimotor interactions with targets presented on a planar surface in aiming, tracking and steering tasks.

Results: In Experiment 1, the filters caused decreased task performance-confirming that unilateral (and bilateral) visual loss has functional implications. In Experiment 2, kinematic measures were affected by monocular viewing in two of three tasks requiring rapid online visual feedback (aiming and steering).

Conclusions: Unilateral visual loss has a measurable impact on sensorimotor performance. The benefits of binocular vision may be particularly important for some groups (e.g. older adults) where an inability to complete sensorimotor tasks may necessitate assisted living. There is an urgent need to develop rigorous kinematic approaches to the quantification of the functional impact of unilaterally degraded vision and of the benefits associated with treatments for unilateral ophthalmic conditions to enable informed decisions around treatment.

Fig 1

Illustration of the three motor control tasks: a) tracking, b) aiming and c) steering. a) Left panel shows the No Guide (NG) tracking condition, the dotted line indicates the trajectory of the moving dot. The right panel demonstrates the With Guide (WG) tracking condition, the solid line is the spatial guideline. b) Shows the aiming task. The red dot is the target, the arrows signal the movements that participants would make with the stylus between target locations and the numbers indicate the sequence in which the targets appeared. c) The left panel shows the primary path steering condition and the right panel shows the alternative path (mirror image) condition. The light grey line is the ‘ink trail’ showing the path taken. Participants follow the shape with their stylus and they are instructed to stay within the box shown, the box moves every 5 seconds. (Image adapted with permission from Flatters et al [47]). Note, only the aiming task (panel b) is completed during Experiment 1, whereas all three tasks (panel a-c) are completed in Experiment 2 and, therefore, are included here for future reference.

Fig 2. Experimental procedure flowchart.

The order of visual condition completed (unilateral, bilateral and no impairment) was counter-balanced, so condition one refers to no impairment for some participants, unilateral impairment for others and so on.

Fig 3

A) Visual Acuity (VA; mean logMAR score); B) Contrast sensitivity (CS; mean score in log units); C) Stereoacuity (mean score in arcsecs) across all visual conditions (no impairment, unilateral impairment, bilateral impairment). Significant effects are represented as: p < 0.05 (*), p < .01 (**), p < .001 (***).

Fig 4

Water-pouring measures: A) Time taken (s) to complete the water-pouring task across all visual conditions. B) Water-pouring absolute accuracy (ml). Mean volume of water either above or below the 40ml marker across all visual conditions. C) Water-pouring composite measure of time and accuracy across all visual conditions. Error bars represent the standard error of the mean. Significant effects are represented as: p < 0.05 (*), p < .01 (**), p < .001 (***).

Fig 5. Purdue pegboard scores.

The mean number of correctly placed pegs within 30 seconds across all visual conditions (no impairment, unilateral impairment, bilateral impairment). Error bars represent the standard error of the mean. Significant effects are represented as: p < 0.05 (*), p < .01 (**), p < .001 (***).

Fig 6. Aiming.

Mean movement time (MT) in seconds across all visual conditions (no impairment, unilateral impairment, bilateral impairment). Error bars represent the standard error of the mean. Significant effects are represented as: p < 0.05 (*), p < .01 (**), p < .001 (***).

Fig 7. Tracking a moving target in a ‘figure-of-8’ trajectory with No Guide (NG) or With Guide (WG).

Performance was measured using the mean root mean square error (RMSE) for all three speeds (Slow = circles, Medium = squares, Fast = diamonds) across all visual conditions (worse eye, better eye, both eyes). Note that the WG conditions were completed second so worse (and more variable) performance may reflect participant mental fatigue/boredom. Error bars represent the standard error of the mean. Where no error bars appear they are smaller than the size of the symbol.

Fig 8. Aiming performance was measured using mean movement time (MT) in seconds across all visual conditions (worse eye, better eye, both eyes).

Error bars represent the standard error of the mean. Significant effects are represented as: p < 0.05 (*), p < .01 (**), p < .001 (***).

Fig 9. Steering performance was measured using mean penalised path accuracy (pPA) for both paths (circles = path A, triangles = path B) across all visual conditions (worse eye, better eye, both eyes).

Error bars represent the standard error of the mean.