Convex Computation of the Basin of Stability to Measure the Likelihood of Falling: A Case Study on the Sit-to-Stand Task
This work addresses the need for a quantitative stability metric in locomoting systems, such as for safety in human movement analysis, but it is incremental as it applies existing dynamical systems theory to a specific task.
The paper tackled the problem of quantifying stability in locomotion by developing a personalized, automated framework to compute the basin of stability, which measures the set of perturbations from which a system can avoid failure, and verified it on a Sit-to-Stand task with 15 individuals, showing it could differentiate between less and more stable strategies.
Locomotion in the real world involves unexpected perturbations, and therefore requires strategies to maintain stability to successfully execute desired behaviours. Ensuring the safety of locomoting systems therefore necessitates a quantitative metric for stability. Due to the difficulty of determining the set of perturbations that induce failure, researchers have used a variety of features as a proxy to describe stability. This paper utilises recent advances in dynamical systems theory to develop a personalised, automated framework to compute the set of perturbations from which a system can avoid failure, which is known as the basin of stability. The approach tracks human motion to synthesise a control input that is analysed to measure the basin of stability. The utility of this analysis is verified on a Sit-to-Stand task performed by 15 individuals. The experiment illustrates that the computed basin of stability for each individual can successfully differentiate between less and more stable Sit-to-Stand strategies.