Robot assisted knee joint rehabilitation system

Abstract

Global demand for rehabilitation services is increasing because of growing non-communicable diseases like stroke and heart attacks, which raises greater demand of robot assisted rehabilitation systems. As the research on rehabilitation robot is quite new and most of the rehabilitation systems used in various rehabilitation and medical centers are imported, this research aims to design and develop a robot assisted rehabilitation system focusing on knee joint Range of Motion (RoM) exercise. Currently, most of the robot assisted rehabilitation systems require trained medical personnel and the systems are too expensive for the adoption of mass consumers. This research will provide key findings to support the adoption of rehabilitation systems as a part of personal service robots for therapeutic exercise. Knee joint rehabilitation basically refers to a kind of treatment or care which is provided to a patient having impaired lower limbs, or dysfunction in certain abilities to move knee joint due to the results of trauma or other medical conditions. Exercise sessions consist of a series of repeated and assistive physical motions. During exercise, reflex action of limbs causes inappropriate balance of load which may damage muscle or tendon tissues. Establishing correlation between impedance data and limb motions is important to solve this problem which is not considered in most of the available rehabilitation systems. Considering these points, a 1-DoF rehabilitation system-prototype with 3-DoF control mechanisms is designed and implemented in this research to maintain position, velocity, and force of knee joint through establishing correlation of impedance responses with limb motions during rehabilitation. The research develops a mathematical model of human leg dynamics for estimating leg (or knee joint) impedances that leads to design the force compensator to control system torque in real time. The system prototype was experimented with ten healthy subjects whose ages were between 23 to 35 years, heights were 150 cm to 174 cm, and weights were 55 kg to 80 kg. Experimental results were also validated with two recent researches. Validation results present that the designed prototype shows good performances with low position and velocity tracking errors, �0.02� & 0.04 rad.sec^(-1) during hold phase; and �0.14� & 0.17 rad.sec^(-1) during swing phase respectively. Though, main limitation of the designed prototype is its current range of motion which is limited to 25�, the system shows potential for application on real patients. Sensor with wide range of torque responses will not only improve the RoM functionality of the system but also facilitate a wide range of opportunities in terms of clinical and engineering research on rehabilitation. Among the three categories of robots, this rehabilitation system could be used as professional service robot in medical centers as well as personal service robot for rehabilitation exercise.