STUDY OF LEG EXOSKELETON FOR SIT TO STAND

Abstract

Leg exoskeletons assist the patients with lower limb impairments or elderly people to stand up and rehabilitate gait pattern. Lower limb exoskeletons can be classified as active exoskeletons and passive exoskeletons. Leg exoskeletons employ high-level control for general behavior, mid-level control for joint torque or position, and low-level control for executing actions. Several types of control strategies are applied in controlling leg exoskeleton including trajectory tracking, adaptive control, robust control, admittance shaping and intelligent control. The design of leg exoskeletons integrates biomechanical compatibility, advanced control strategies, and safety mechanisms, offering a versatile solution for individuals seeking enhanced mobility, rehabilitation support, or assistance in daily activities. Leg exoskeletons, designed with actuators like electric motors or series elastic actuators (SEA), enhance motion in the ankle, knee, and hip joints. Designs vary from single to multiple joints actuation classified into hip exoskeleton, knee exoskeleton, ankle exoskeleton, and multiple joint exoskeletons. Based on applications, leg exoskeletons classified into rehabilitation, assistive, and performance-enhancing types, which enhance mobility in patients with limb paralysis. Although lower limb exoskeletons provide benefit, they exhibit endangerments such as falls, skin damage, user errors, fractures, and long-term consequences. Regulatory standards and continuing research are indispensable to ensure safety measures. Bioelectric and mechanical sensing techniques, such as EEG, sEMG, IMU, torque sensors, and force sensors, enables the exact detection of human motion intentions for leg exoskeleton’s control and rehabilitation. Intelligent approaches, such as learning from demonstration and reinforcement learning, improve adaptability in robot-human interactions. The leg exoskeleton is modeled as a 2R robot and a 3R robot according to the actuated joints. Kinematic and dynamic analysis are also used to create the exoskeleton model. Forward kinematics and inverse kinematics are two kinds of kinematic analysis, and the Lagrangian equation is applied in dynamic analysis. This Lagrangian equation can be transformed into an equation including an inertia matrix, a Coriolis and centrifugal matrix, and a gravity matrix for the use of leg exoskeleton control. The fifth-order (quintic) trajectory generation is used in the control part of the leg exoskeleton. For effective control, close-loop PD and PID control schemes are designed by adjusting the proportional, integral, and derivative gains to make the error tend to zero.