"Based on over three years of intensive R&D, the RHEO KNEE is the first in a new generation of microprocessor-controlled, swing & stance knee systems that incorporate artificial intelligence, giving the system the ability to learn how the user walks and eventually pre-empt each step," explains Ms. Claire Staniforth, Research Analyst with Frost & Sullivan. "This breakthrough in technology will lead the way for the next generation of prosthetics, focused on precisely copying the bio-mechanical motion of human joints and limbs."
The angle of and load borne through the artificial knee joint are monitored at a rate of 1,000 times per second using electronic sensors. Changes in value are accompanied by related alterations in the viscosity of the magnetorheological (MR) fluid within the knee. A computer chip creates and regulates the intensity of the magnetic field, causing changes in MR fluid viscosity about the joint that facilitates optimal motion control.
A dynamic learning matrix algorithm (DLMA) enables the RHEO KNEE in rapidly adjusting the swing and stance resistance as it effectively learns the movements of the user. The DLMA optimises levels of resistance during the swing phase allowing the user to walk comfortably and safely at a range of speeds.
The crucial drawback with traditional hydraulic knee control joints has been the build up of drag within the system. However, the MR fluid used in the RHEO KNEE significantly reduces this drag thereby conserving the energy levels of the amputee enabling longer periods of joint
Contact: Beverly Millson