Avoiding Virtual Obstacles During Treadmill Gait in Parkinson's Disease

Abstract

Falls often occur due to spontaneous loss of balance, but tripping over an obstacle during gait is also a frequent cause of falls (Sheldon, 1960; Stolze et al., 2004). Obstacle avoidance requires that appropriate modifications of the ongoing cyclical movement be initiated and completed in time. We evaluated the available response time to avoid a virtual obstacle in 26 Parkinson's disease (PD) patients (in the off-medication state) and 26 controls (18 elderly and 8 young), using a virtual obstacle avoidance task during visually cued treadmill walking. To maintain a stable baseline of stride length and visual attention, participants stepped on virtual "stepping stones" projected onto a treadmill belt. Treadmill speed and stepping stone spacing were matched to overground walking (speed and stride length) for each individual. Unpredictably, a stepping stone changed color, indicating that it was an obstacle. Participants were instructed to try to step short to avoid the obstacle. By using an obstacle that appeared at a precise instant, this task probed the time interval required for processing new information and implementing gait cycle modifications. Probability of successful avoidance of an obstacle was strongly associated with the time of obstacle appearance, with earlier-appearing obstacles being more easily avoided. Age was positively correlated (p < 0.001) with the time required to successfully avoid obstacles. Nonetheless, the PD group required significantly more time than controls (p = 0.001) to achieve equivalent obstacle-avoidance success rates after accounting for the effect of age. Slowing of gait adaptability could contribute to high fall risk in elderly and PD. Possible mechanisms may include disturbances in motor planning, movement execution, or disordered response inhibition.

Keywords: Parkinson’s disease; adaptive gait; obstacle avoidance; postural control; treadmill.

FIGURE 1

(A) Dimensions of virtual obstacles and stepping stones; (B) The distribution of timing of obstacle appearance relative to previous ipsilateral toe-off (in all participants); (C) Illustration for calculation of available time to respond; (D) Logistic regression of success/failure on available time to respond (bottom x-axis) and obstacle latency (top x-axis) in one representative participant; (E) density plot of obstacle latency (left)/available time to respond (right) for total number of obstacles presented to all participants separated by group.

FIGURE 2

(A) The available time to respond (ttr₅₀) of the two groups (the three asterisks shows significant difference between the groups with p < 0.001); (B) The overall success rates for obstacle avoidance task of the two groups.

FIGURE 3

(A) Relationship between ttr₅₀ and age for both groups, for regression lines, dashed trace represents Parkinson’s disease (PD) and solid trace Control, while light gray circle and dark gray circle represents PD and Control, respectively (age covariate, p < 0.001); (B) Relationship between ttr₅₀ and MDS-UPDRS total motor scores for the PD group (two participant excluded due to missing items in MDS-UPDRS motor, dashed trace represents the regression line, p = 0.16); (C) Relationship between ttr₅₀ and MDS-UPDRS motor axial subscores for the PD group, dashed trace represents the regression line (one participant excluded due to missing axial item, p = 0.02); (D) Relationship between ttr₅₀ and disease duration for the PD group, dashed trace represents the regression line (p = 0.77).