Abstract
In a parallel development to traditional rigid rehabilitation robotic systems, cable-driven systems are becoming popular. The robowalk expander product uses passive elastic bands in the training of the lower limbs. However, a well-controlled assistance or resistance is desirable for effective walking relearning and muscle training. To achieve well-controlled force during locomotion training with the robowalk expander, we replaced the elastic bands with actuator-driven cables and implemented force control algorithms for regulation of cable tensions. The aim of this work was to develop an active cable-driven robotic system, and to evaluate force control strategies for walking rehabilitation using frequency-domain analysis. The system parameters were determined through experiment-assisted simulation. Then force-feedback lead controllers were developed for static force tracking, and velocity-feedforward lead compensators were implemented to reduce velocity-related disturbances during walking. The technical evaluation of the active cable-driven robotic system showed that force-feedback lead controllers produced satisfactory force tracking in the static tests with a mean error of 5.5%, but in the dynamic tests, a mean error of 13.2% was observed. Further implementation of the velocity-feedforward lead compensators reduced the force tracking error to 9% in dynamic tests. With the combined control algorithms, the active cable-driven robotic system produced constant force within the four cables during walking on the treadmill, with a mean force-tracking error of 10.3%. This study demonstrates that the force control algorithms are technically feasible. The active cable-driven, force-controlled robotic system has the potential to produce user-defined assistance or resistance in rehabilitation and fitness training.
Highlights
Diseases of or injuries to the cerebrovascular system often result in impaired sensorimotor function
To achieve well-controlled force during locomotion training with the robowalk expander, we replaced the elastic bands with actuator-driven cables and implemented novel force control algorithms for regulation of cable tensions
During evaluation of the force control algorithms, the simulated force output Fsim and the control signal Tmpsim are presented in figures using green lines, serving as a comparison for the experimental results, which are presented as red lines
Summary
Diseases of or injuries to the cerebrovascular system often result in impaired sensorimotor function. Most rehabilitation robotic systems use rigid mechanisms to assist training for the upper or lower limbs (Hesse et al, 2003; Hidler et al, 2005), including exoskeleton-based systems (e.g., Armeo Power and Lokomat from Hocoma, Switzerland) and end-effector based systems (e.g., MIT-MANUS from Interactive Motion Technologies Inc., Cambridge, Massachusetts, USA, and the G-EO system from Reha Technology, Switzerland). Along with these rigid rehabilitation robotic systems, cableaided rehabilitation therapy has emerged in recent years with advantages including low moment of inertia, high power output, and soft human-machine contact (Rosati et al, 2017). Cable-driven rehabilitation systems available on the market include Diego (Tyromotion GmbH, Austria) for upper limb rehabilitation (Aprile et al, 2019), and the robowalk expander system (h/p/cosmos Sports & Medical GmbH, Germany) for lower limb training (Schulze et al, 2019)
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