Assist-as-Needed Control of an Intrinsically Compliant Robotic Gait Training Orthosis

Abstract

Abstract-It is a common hypothesis in the field of robot assisted gait rehabilitation that the active involvement and voluntary participation of neurologically impaired subjects in the robotic gait training process may enhance the outcomes of such therapy. An adaptive seamless assist-as-needed (AAN) control scheme was developed for the robotic gait training. The AAN control scheme learns in real time the disability level of human subjects based on the trajectory tracking errors and adapts the robotic assistance accordingly. The overall AAN control architecture works on the basis of a robust adaptive control approach. The performance of seamless AAN control scheme was evaluated during treadmill training with a compliant robotic orthosis having 6-degrees of freedom (DOF). Two experiments, namely trajectory following experiment and the AAN experiment were carried out to evaluate the performance of seamless adaptive AAN control scheme. It was found that the robotic orthosis is capable of guiding the subjects' limbs on reference trajectories during the trajectory following experiment. Also, a variation in robotic assistance was recorded during the AAN experiment based on the voluntary participation of human subjects. This work is an advance on the current state of the art in the compliant actuation of robotic gait rehabilitation orthoses in the context of seamless AAN gait training.

Assist-as-Needed Control of a Robotic Orthosis Actuated by Pneumatic Artificial Muscle for Gait Rehabilitation

“…This control performance is in accordance with the result achieved in [19][20][21][22] in which the 6-DOFs gait rehabilitation orthosis powered by PAMs is used, i.e., MTE < 15 • . However, the walking speed of the proposed system, i.e., 2.2 km/h, is lower than of its 6-DOF robot orthosis system counter part, i.e., 2.5 km/h.…”

“…However, the walking speed of the proposed system, i.e., 2.2 km/h, is lower than of its 6-DOF robot orthosis system counter part, i.e., 2.5 km/h. The trajectory tracking control strategy of 6-DOF system based on the boundary layer augmented sliding control (BASMC) law [19,20] and the chattering free robust variable structure controller (CRVC) [21,22], whereas the proposed system employed the modified computed torque control scheme with one more fractional order derivative for tracking purposed. Although, the nominal pressure is also used for AAN, the proposed strategy required less force sensors, i.e., 2 bar-shaped load cells attached at COM of thigh and shank part, in comparison with 4 load cells connected in series with each PAM in the 6-DOF robot system.…”

“…Thus, the applications of PAM in rehabilitation robotics field are growing despite the inherent drawbacks such as hysteresis, compressibility and time variance which yield extreme difficulties in constructing an accurate mathematical model. Various prototype systems have been developed in research centers [11][12][13][14][15][16][17][18][19][20][21][22]. To handle the nonlinear behavior of the PAM, a three-element model [23] based on the sliding mode control (SMC) has been considered as a good choice for tracking control of both single PAM [24] and robots powered by PAMs [14,15,[18][19][20].…”

“…To handle the nonlinear behavior of the PAM, a three-element model [23] based on the sliding mode control (SMC) has been considered as a good choice for tracking control of both single PAM [24] and robots powered by PAMs [14,15,[18][19][20]. Besides, AAN strategy which provides interactive human-robot gait training is also indispensable in these systems [20][21][22]. The AAN strategy can be achieved by compliance control in which the nominal pressure of the PAM is adjusted [17,[19][20][21][22].…”

“…Besides, AAN strategy which provides interactive human-robot gait training is also indispensable in these systems [20][21][22]. The AAN strategy can be achieved by compliance control in which the nominal pressure of the PAM is adjusted [17,[19][20][21][22].…”