Design of RYSEN: An Intrinsically Safe and Low-Power Three-Dimensional Overground Body Weight Support

Body weight support (BWS) systems are widely used in gait research and rehabilitation. This letter introduces a new three-dimensional overground BWS system, called the RYSEN. The RYSEN is designed to be intrinsically safe and low power consuming, while still performing at least as well as existing BWS systems regarding human–robot interaction. These features are mainly achieved by decoupling degrees of freedom between motors: slow/high-torque motors for vertical motion and fast/low-torque motors for horizontal motion. This letter explains the design and evaluates its performance on power consumption and safety. Power consumption is expressed in terms of the sum of the positive mechanical output power of all motor axes. Safety is defined as the difference between the mechanical power available for horizontal and vertical movements and the mechanical power that is needed to perform its task. The results of the RYSEN are compared to the performance of three similar systems: a gantry, the FLOAT, and a classic cable robot. The results show that the RYSEN and a gantry consume approximately the same amount of power. The amount is approximately half the power consumed by the next-best system. For the safety, the gantry is taken as the benchmark, because of its perfect decoupling of directions. The RYSEN has a surplus of 268 W and 126 W for horizontal and vertical movements, respectively. This is significantly lower than the next-best system, which has a surplus of 1088 W and 1967 W, respectively.

[1]  Tobias Nef,et al.  ZeroG: overground gait and balance training system. , 2011, Journal of rehabilitation research and development.

[2]  P Cordo,et al.  Proprioceptive coordination of movement sequences: role of velocity and position information. , 1994, Journal of neurophysiology.

[3]  Joost Geeroms,et al.  Optimizing the power and energy consumption of powered prosthetic ankles with series and parallel elasticity , 2017 .

[4]  R. Riener,et al.  Towards more effective robotic gait training for stroke rehabilitation: a review , 2012, Journal of NeuroEngineering and Rehabilitation.

[5]  H. Thieme Enhanced Gait-Related Improvements After Therapist- versus Robotic-Assisted Locomotor Training in Subjects with Chronic Stroke: A Randomized Controlled Study , 2008 .

[6]  Larry K. Dungan,et al.  Active Response Gravity Offload System , 2011 .

[7]  S. Thorpe,et al.  Speed of processing in the human visual system , 1996, Nature.

[8]  J. Hidler,et al.  Multicenter Randomized Clinical Trial Evaluating the Effectiveness of the Lokomat in Subacute Stroke , 2009, Neurorehabilitation and neural repair.

[9]  Matthew M. Williamson,et al.  Series elastic actuators , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[10]  Paolo Gallina,et al.  Variable Radius Drum Mechanisms , 2016 .

[11]  Robert Riener,et al.  Effects of added inertia and body weight support on lateral balance control during walking , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[12]  Marc Bolliger,et al.  Multidirectional transparent support for overground gait training , 2013, 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR).