(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, 2023)
Scherpereel, Keaton; Molinaro, Dean; Inan, Omer; Shepherd, Maxwell; Young, Aaron
Tasks of daily living are often sporadic, highly variable, and asymmetric. Analyzing these real-world non-cyclic activities is integral for expanding the applicability of exoskeletons, protheses, wearable sensing, and activity classification to real life, and could provide new insights into human biomechanics. Yet, currently available biomechanics datasets focus on either highly consistent, continuous, and symmetric activities, such as walking and running, or only a single specific non-cyclic task. To capture a more holistic picture of lower limb movements in everyday life, we collected data from 12 participants performing 20 non-cyclic activities (e.g. sit-to-stand, jumping, squatting, lunging, cutting) as well as 11 cyclic activities (e.g. walking, running) while kinematics (motion capture and IMUs), kinetics (force plates), and EMG were collected. This dataset provides normative biomechanics for a highly diverse range of activities and common tasks from a consistent set of participants and sensors.