Individual-specific gait pattern planning and locomotion control strategy for robotic gait rehabilitation

• Main Author: Luu, Trieu Phat
• Other Authors: Qu Xingda
• Format: Theses and Dissertations
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Bioengineering; DRNTU::Engineering::Mechanical engineering::Control engineering; DRNTU::Engineering::Mechanical engineering::Robots
• Online Access: https://hdl.handle.net/10356/58912
• Institution: Nanyang Technological University

Spinal cord injury (SCI) and stroke are the leading cause of permanent disability around the world. Majority of these patients has to go through gait rehabilitation to regain their walking ability. The objectives of this research work are to introduce an individual-specific gait pattern prediction model and to design a subject-cooperative control strategy for robotic gait rehabilitation to improve the therapeutic outcomes. Robotics is gaining its popularity in gait rehabilitation. Gait pattern planning is important to ensure that the gait patterns induced by robotic systems are tailored to each individual and varying walking speed. Most research groups planned gait patterns for their robotic systems based on Clinical Gait Analysis (CGA). The major problem with CGA data is that it cannot accommodate inter-subject differences and it is limited to only one walking speed as per the published data. In this work, an individual-specific gait pattern planning model was developed to generate walking gait patterns based on gait parameters (stride length, cadence) and anthropometric data of targeted subjects. The results showed that the proposed model was able to generate gait pattern better than CGA approach in term of resembling the actual gait pattern of the targeted subject. Reviews on locomotor control in robotic gait rehabilitation showed that passive training strategy does not provide an ideal training for patients who have capability of some voluntary motor control. If patients are trained with totally passive training strategy, they tend to train with reduced activity of muscles and metabolism. This work introduces a gait pattern adaptation model for subject-cooperative control strategy in robotic rehabilitation. Based on the human-machine interaction, the walking speed is updated and gait pattern is modified during the training process. This model allows the subject to interact with the machine and increase their effort in the training session. This thesis presents a new robotic assisted gait rehabilitation methodology. The methodology is accompanied with the human gait locomotion study, development of a control module hardware for an over-ground gait trainer, motion planning for natural gait-like implemented on robotic assisted systems and design of subject-cooperative locomotion control strategy.