Patient cooperative adaptive controller for lower limb Robotic Rehabilitation Device

Publication Type:
Conference Proceeding
Citation:
Souvenir of the 2014 IEEE International Advance Computing Conference, IACC 2014, 2014, pp. 1469 - 1474
Issue Date:
2014-01-01
Full metadata record
This is evident that training duration is a key factor for a successful therapy. Robot supported therapy can improve the rehabilitation allowing more intensive training. This paper presents the kinematic, the control architecture and benchmark criteria to evaluate the performance of Robotic Rehabilitation Devices (RRD). Equipped with position, force and impedance controller, the proposed RRD can deliver the patient cooperative lower limb therapy taking into account the patient activity and supporting him/her only as much as needed[1]. One of the main objectives of a successful lower limb robotic rehabilitation device is to obtain a smooth human machine interaction in different phase of gait cycle at the interaction point (haptic behavior). The input (interaction force, Joint angle, rate of change of interaction force) and output (impedance, Δτ) relationship of the control system is nonlinear. This paper proposes a fuzzy rule based controller to be used to control the interaction force at the patient exoskeleton interaction point. In achieving the objective, impedance, driver torque and angular velocity have been modulated in a way such that there is a reduction of interaction force. Minimum interaction force at the interaction point and tracking the defined gait trajectory with minimum error are set as the benchmark to evaluate the performance in many tasks. In this paper there is an evaluation of what degree of impedance is ideal for what type of interaction force and joint angle to maintain a trajectory tunnel. This paper describes the control architecture of one Degree of freedom lower limb exoskeleton that has been specifically designed in order to ensure a proper trajectory control for guiding patient's limb along an adaptive reference gait pattern[2]. The proposed methodology satisfies all the desired criteria to be an ideal robotic rehabilitation device. © 2014 IEEE.
Please use this identifier to cite or link to this item: