(Georgia Institute of Technology, 2023-02-23)
Leestma, Jennifer K.; Golyski, Pawel R.; Smith, Courtney R.; Sawicki, Gregory S.; Young, Aaron
The purpose of this data set is to enable the investigation of human balance and recovery strategies during perturbed walking. We performed a study where participants walked while being exposed to ground translation perturbations. We varied the magnitude, direction, and onset time of these perturbations while collecting various biomechanical outcome metrics.
(Georgia Institute of Technology, 2020-01)
Golyski, Pawel R.; Vazquez, Esmeralda; Leestma, Jennifer K.; Sawicki, Gregory S.
Compromised balance is a major public health concern, both in the workplace and among older adults. In the US, falls account for 15% of the total injury cost among workers, and 25% of older adults fall each year. Wearable robots can address instability during walking, but despite walking being a cyclic task defined by the gait cycle, the critical period during the gait cycle when individuals are least robust to slips is unknown. We hypothesized that individuals would be most destabilized by a backwards slip when it is delivered between 15-20% of the gait cycle, which corresponds to the time when only one foot is on the ground and the center of mass is behind that supporting limb. Using a split-belt treadmill, we interrogated robustness to a brief slip delivered to one leg at 10, 15, 20, 30, 40, and 50% of the gait cycle. We slipped 10 individuals in each combination of leg and slip timing 10 times. We quantified stability using dynamic stability margin, step length, step width, and their variabilities from the step before to 4 steps after each slip. Dynamic stability margin, step width, step length, and step length variability indicated that slips from 20-30% of the gait cycle were significantly more destabilizing than slips delivered later in the gait cycle, while step width variability indicated slips delivered at 15% of the gait cycle were most destabilizing. We anticipate these findings will prompt wearable robotic solutions which improve slip robustness between 15-30% of the gait cycle.