This is a repository copy of Recent development of mechanisms and control strategies for robot-assisted lower limb rehabilitation.

Landsat satellite image (LE70390372003084EDC00) showing location of surface slip triggered along faults in the greater Salton Trough area. Red bars show the generalized location of 2010 surface slip along faults in the central Salton Trough and many additional faults in the southwestern section of the Salton Trough. Surface slip in the central Salton Trough shown only where verified in the field; slip in the southwestern section of the Salton Trough shown where verified in the field or inferred from UAVSAR images.

No abstract

Abstract-Robot-assisted rehabilitation offers benefits such as repetitive, intensive and task specific training as compared to traditional manual manipulation performed by physiotherapists. In this paper, a robust iterative feedback tuning (IFT) technique for repetitive training control of a compliant parallel ankle rehabilitation robot is presented. The robot employs four parallel intrinsically compliant pneumatic muscle actuators that mimic skeletal muscles for ankle's motion training. A multiple degreesof-freedom normalised IFT technique is proposed to increase the controller robustness by obtaining an optimal value for the weighting factor and offering a method with learning capacity to achieve an optimum of the controller parameters. Experiments with human participants were conducted to investigate the robustness as well as to validate the performance of the proposed IFT technique. Results show that the normalised IFT scheme will achieve a better and better tracking performance during the robot repetitive control and provides more robustness to the system by adapting to various situations in robotic rehabilitation.