Gait patterns and control strategies for a lower limb rehabilitation exoskeleton

Abstract

This thesis involves the study of movement while walking donning a lower limb exoskeleton and using crutches for stability in a rehabilitation scenario. A kinematic coherence system is proposed and consists of an algorithm to guarantee that all joints have a specific position setpoint during the exoskeleton operation. Additionally, an array of PID position controllers with a variable torque threshold algorithm modifies the position setpoint in order to maintain the torque under a predefined threshold. The variable torque algorithm modifies the position control setpoints such that the joint movement does not stop abruptly. The variable torque algorithm consists of a set of first order filters, one per each controller. They are heuristically tuned and react when the interaction torque surpasses the torque threshold. In this work only one degree of freedom for hip and ankle joints is used to simplify and mimic the pace when walking straight forward. A method is presented to acquire ankle trajectories from subjects and produce and reproduce human-like ankle trajectories that could be scaled and calculated on-line, could be altered to adjust to different gait environments, could be used to generate reference trajectories for high level gait controllers. In addition, it could be used as an accurate and salient benchmark to test the human likeness of gait trajectories of current exoskeletal devices. Literature review suggests analyzing gait in phases. A preliminary data analysis, suggests that there exist six key events of the gait cycle, events that can adequately characterize gait for the purposes required of robotic rehabilitation including gait analysis and reference trajectory generation. Defining the ankle as an end effector and the hip as the origin of the coordinate frame and basing the linear regression calculations only on the six key events, i.e. Heel Strike, Toe Off, Pre-Swing, Initial Swing, Mid-Swing and Terminal Swing, it is possible to generate a new calculated ankle trajectory with an arbitrary step length. The Leave-One-Out Cross Validation algorithm was used to estimate the fitting error of the calculated trajectory versus the characteristic captured trajectory per subject, showing a fidelity average value of 95.2%, 96.1% and 97.2% respectively for each step-length trial including all subjects. The thesis also includes a partial automation of the lower limb exoskeleton for position control and torque limiting of the three main joints: hip, knee and ankle and their respective movements over the sagittal plane. To obtain information of the angular position in which each limb is placed, the exoskeleton uses linear potentiometers. The proper torque threshold level is selected according to the user’s range-of move- ment. The user’s range-of-movement for each joint was obtained measuring the flexion-extension movements with a goniometer. Before implementation, the proposed control algorithm is tested in a control system software and its effectiveness is verified thorough simulation. The experimental protocol consists in capturing kinematic data while subjects walk, with a donned lower-limb exoskeleton, across three experimental conditions: walking with three different pre-determined step lengths marked on a lane. The captured ankle trajectories in the sagittal plane were found by normalizing all trials of each test from one heel strike to the next heel strike independent of the specific gait features of each subject. To generate a walking pattern for the exoskeleton, the adjustable trajectory generator was developed. It includes the method to acquire and saliently analyze subject-specific gait data while the subject dons a passive lower-limb exoskeleton. A human-user study with ten healthy subjects provides the experimental setup to validate the proposed method. Preliminary results show a good performance of the proposed gait patterns and control strategies for potential applications in physical rehabilitation.