Probability of lateral instability while walking on winding paths

Gait biomechanics is most often studied during straight-ahead walking. However, real-life walking imposes many turns and/or other such maneuvers that people must navigate.  Such maneuvers challenge people’s lateral balance. In older adults or others with impaired walking, such tasks can induce falls, which can increase risk of injuries in these populations.  Therefore, determining how people’s lateral balance is impacted during these more complex walking tasks, and how they adapt their steps, is critical.  Here, we asked 24 young healthy adult participants (12F/12M; Age 25.8±3.5yrs) to walk on both wide and narrow virtual paths that were either straight, slowly-winding, or quickly-winding. This data set comprises their lower body, pelvis, and head kinematics as they walked along those paths. A file of participant characteristics (.xlsx), including group demographics, participant anthropometrics, and assessment scores is also provided. In addition, a marker-set definition file (.xlsx) is also provided. These data include how people navigate paths of different width and curviness, which may lend themselves to several applications such as investigations of more real-world gait interventions to target adaptive strategies that could more effectively improve mobility.

Methods
This experiment included data from 24 healthy human adult participants (12F/12M; Age 25.8±3.5yrs).  Data regarding their baseline demographics, relevant participant anthropometrics, and relevant assessment scores are provided (*.xlsx file).

Participants walked on a motorized treadmill in a Motek M-Gait virtual reality system (https://www.motekmedical.com/). The walking paths they walked on are described in detail in the associated README file.  Each participant completed two experimental trials (4 min long each) walking on each of 6 different types of paths.

For each trial performed by each participant, motion capture data were recorded with a 10-camera Vicon system (https://www.vicon.com/).  These data were cleaned using Vicon Nexus software, and further processed in Matlab (https://www.mathworks.com/). All marker trajectories and path data (treadmill distance) are provided in this data set.