RUPERT closed loop control design

Robot-assisted rehabilitation is an active area of research in the field of stroke rehabilitation. RUPERT is a wearable robotic exoskeleton powered by pneumatic muscle actuators. In this study, we described the structure of the controllers for the five degrees of freedom currently used by RUPERT. We applied the RUPERT on 6 stroke patients to provide robot-assisted rehabilitation therapy in a clinical study. Statistical χ2 test on the proportion of successfully reaching targets showed that 3 out of the 6 patients demonstrated significant improvement in reaching targets successfully, and the remaining 3 did not show performance improvement or deterioration. We plan to implement the RUPERT in the patient's house for easier access and more frequent use. More significant performance results are expected.

[1]  V. Dietz,et al.  Driven gait orthosis for improvement of locomotor training in paraplegic patients , 2001, Spinal Cord.

[2]  Sivakumar Balasubramanian,et al.  RUPERT closed loop control design , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[4]  N. Hogan,et al.  Robot-aided neurorehabilitation. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[5]  N. Hogan,et al.  Robot-aided sensorimotor training in stroke rehabilitation. , 2003, Advances in neurology.

[6]  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.

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

[8]  C. Burgar,et al.  Quantification of force abnormalities during passive and active-assisted upper-limb reaching movements in post-stroke hemiparesis , 1999, IEEE Transactions on Biomedical Engineering.

[9]  N. Hogan,et al.  Robot training enhanced motor outcome in patients with stroke maintained over 3 years , 1999, Neurology.

[10]  A.G. Alleyne,et al.  A survey of iterative learning control , 2006, IEEE Control Systems.

[11]  Nilanjan Sarkar,et al.  Adaptable force control in robotic rehabilitation , 2005, ROMAN 2005. IEEE International Workshop on Robot and Human Interactive Communication, 2005..

[12]  P. Culmer,et al.  An Admittance Control Scheme for a Robotic Upper- Limb Stroke Rehabilitation System , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[13]  Hermano Igo Krebs,et al.  Rehabilitation Robotics: Performance-Based Progressive Robot-Assisted Therapy , 2003, Auton. Robots.

[14]  David J. Reinkensmeyer,et al.  Design of robot assistance for arm movement therapy following stroke , 2001, Adv. Robotics.

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

[16]  Robert Riener,et al.  A novel paradigm for patient-cooperative control of upper-limb rehabilitation robots , 2007, Adv. Robotics.

[17]  D. Reinkensmeyer,et al.  Emerging Technologies for Improving Access to Movement Therapy following Neurologic Injury , 2002 .