Joint Kinematics as Predictors of Metabolic Response to Passive Exosuits

Exosuits and exoskeletons have emerged as promising technology for enhancing human locomotion by reducing metabolic costs. However, individual responses to exosuits vary significantly---while some users experience notable reductions in metabolic cost, others exhibit increases, limiting the widespread applicability of these devices. This variability highlights the need for a personalized approach to exosuit design and deployment. A key question remains: Are there biomechanical indicators in an unassisted walking condition that can predict whether an individual will benefit from exosuit assistance? If certain baseline movement characteristics can determine a person's response to assistance, this could pave the way for more targeted interventions and effective exosuit designs. This study explores whether baseline joint kinematics in an unassisted condition can serve as a predictor of metabolic cost outcomes across various passive biarticular exosuit configurations. We hypothesize that an individual's range of motion (RoM) during unassisted walking can classify them as either metabolic cost reducers or increasers, offering a simple, non-invasive predictive method for optimizing exosuit usage. Understanding these relationships could significantly enhance the design and implementation of exosuits, ensuring they provide effective and tailored assistance to each user.