Assisting Gait Stability in Walking Aid Users Exploiting Biomechanical Variables Correlation

Abstract

Walking aids for individuals with musculoskeletal frailty or motor disabilities must ensure adequate physical support and assistance to their users. To this end, sensor-enabled human state monitoring and estimation are crucial. This letter proposes an innovative approach to assessing users' stability while walking with WANDER, a novel gait assistive device, by exploiting the correlation between the eXtrapolated Center of Mass ($XCoM$) and the Base of Support ($BoS$) edges. First, the soundness of this metric in monitoring gait stability is proven. Experiments on 25 healthy individuals show that the median value of Pearson's correlation coefficient (p-value $< $ 0.05) remained high during the forward walk for all subjects. Next, a correlation-based variable admittance (CVA) controller is implemented, whose parameters are tuned to physically support users when a gait perturbation is detected (i.e. low values of Pearson's correlation coefficient). To validate this approach, 13 healthy subjects were asked to compare our controller with a force threshold-based (FVA) one. The CVA controller's performance in discriminating stable and perturbed gait conditions showed a high sensitivity value, comparable to FVA, and improved performance in terms of specificity. The number of false and missed detections of gait perturbation was considerably reduced, independently of walking speed, exhibiting a higher level of safety and smoothness compared to the FVA controller. Overall, the outcome of this study gives promising evidence of the proposed metric capability in identifying user stability and triggering WANDER's assistance.