Control of a Pneumatic Orthosis for Upper Extremity Stroke Rehabilitation

A key challenge in rehabilitation robotics is the development of a lightweight, large force, high degrees-of-freedom device that can assist in functional rehabilitation of the arm. Pneumatic actuators can potentially help meet this challenge because of their high power-to-weight ratio. They are currently not widely used for rehabilitation robotics because they are difficult to control. This paper describes the control development of a pneumatically actuated, upper extremity orthosis for rehabilitation after stroke. To provide the sensing needed for good pneumatic control, position and velocity of the robot are estimated by a unique implementation of a Kalman filter using MEMS accelerometers. To compensate for the nonlinear behavior of the pneumatic servovalves, force control is achieved using a new method for air flow mapping using experimentally measured data in a least-squares regression. To help patients move with an inherently compliant robot, a high level controller that assists only as needed in reaching exercises is developed. This high level controller differs from traditional trajectory-based, position controllers, allowing free voluntary movements toward a target while resisting movements away from the target. When the target cannot be reached voluntarily, the controller slowly builds up force, pushing the arm toward the target. As each target position is reached, the controller builds an internal model of the subject's capability, learning the forces necessary to complete movements. Preliminary testing performed on a non-disabled subject demonstrated the ability of the orthosis to complete reaching movements with graded assistance and to adapt to the effort level of the subject. Thus, the orthosis is a promising tool for upper extremity rehabilitation after stroke

[1]  J.J. Palazzolo,et al.  Rehabilitation robotics: adapting robot behavior to suit patient needs and abilities , 2004, Proceedings of the 2004 American Control Conference.

[2]  E.J. Barth,et al.  Energy saving control for pneumatic servo systems , 2003, Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003).

[3]  James E. Bobrow,et al.  Modeling, Identification, and Control of a Pneumatically Actuated, Force Controllable Robot , 1996 .

[4]  C. Burgar,et al.  Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. , 2002, Archives of physical medicine and rehabilitation.

[5]  Tariq Rahman,et al.  16 Design and Testing of WREX , 2004 .

[6]  N. Hogan,et al.  Interactive robots for neuro-rehabilitation. , 2004, Restorative neurology and neuroscience.

[7]  Steven C Cramer,et al.  Robotics, motor learning, and neurologic recovery. , 2004, Annual review of biomedical engineering.

[8]  J. Leavitt,et al.  Bandwidth tilt measurement using low cost sensors , 2004 .

[9]  D.J. Reinkensmeyer,et al.  Robotic movement training as an optimization problem: designing a controller that assists only as needed , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[10]  R. Seliktar,et al.  Design and testing of WREX , 2004 .

[11]  Jan Wikander,et al.  Block-oriented approximate feedback linearization for control of pneumatic actuator system , 2004 .

[12]  J. Liu,et al.  Monitoring functional arm movement for home-based therapy after stroke , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[13]  D.J. Reinkensmeyer,et al.  A pneumatic robot for re-training arm movement after stroke: rationale and mechanical design , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[14]  Robert Riener,et al.  Robot-aided neurorehabilitation of the upper extremities , 2005, Medical and Biological Engineering and Computing.

[15]  Grzegorz Granosik,et al.  Minimizing air consumption of pneumatic actuators in mobile robots , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[16]  Yildirim Hurmuzlu,et al.  A High Performance Pneumatic Force Actuator System: Part I—Nonlinear Mathematical Model , 2000 .