Lower Limb

Lower limb research encompasses the study of human and robotic leg mechanics, focusing on understanding and replicating natural locomotion and manipulation capabilities. Current research employs diverse approaches, including mathematical modeling of gait dynamics, machine learning for gait analysis and injury prediction (using algorithms like XGBoost), and the development of robotic legs with novel designs (e.g., overconstrained linkages and bio-inspired actuation) and control strategies (e.g., reinforcement learning for functional electrical stimulation). These advancements have significant implications for prosthetics design, rehabilitation therapies, and the creation of agile robots for various applications, from assistive technologies to industrial automation.