Control strategies modeling for robotic exoskeletons facilitating sit-to-stand transitions in geriatric and lower limb impaired

Abstract

With the growing global aging population, there's been an amplified societal emphasis on preserving the health of the elderly and enhancing their quality of life. In this scenario, robotic exoskeletons have emerged as a cutting-edge solution to assist the elderly and those with lower limb muscle deficiencies in Sit-to-Stand (STS) exercises. These exoskeletons adopt two main approaches: full assistance for those with entirely weakened lower limbs and partial assistance for those with some remaining muscle strength. This article introduces two modeling methods and concepts for these control strategies, aligning with the full and partial assistance directions, respectively. Both approaches hinge on the Lagrange equation as their foundational structure, integrating distinct kinematic designs to form their individual dynamic models. Based on this, the models are further adapted to address the specific risks associated with STS activities as per each strategy. Research outcomes highlight that by assessing the wearer's EMG signal, the partial assistance strategy considerably mitigates the lower limb muscle strength required for STS under conditions such as low-speed, medium-speed, sitback-like, and step-like. This not only improves balance but also augments the likelihood of successful STS execution, consequently diminishing fall incidents.