Optimizing Compliant, Model-Based Robotic Assistance to Promote Neurorehabilitation Export

@article{citeulike:3360539, abstract = {Based on evidence from recent experiments in motor learning and neurorehabilitation, we hypothesize that three desirable features for a controller for robot-aided movement training following stroke are high mechanical compliance, the ability to assist patients in completing desired movements, and the ability to provide only the minimum assistance necessary. This paper presents a novel controller that successfully exhibits these characteristics. The controller uses a standard model-based, adaptive control approach in order to learn the patient's abilities and assist in completing movements while remaining compliant. Assistance-as-needed is achieved by adding a novel force reducing term to the adaptive control law, which decays the force output from the robot when errors in task execution are small. Several tests are presented using the upper extremity robotic therapy device named Pneu-WREX to evaluate the performance of the adaptive, ldquoassist-as-neededrdquo controller with people who have suffered a stroke. The results of these experiments illustrate the ldquoslackingrdquo behavior of human motor control: given the opportunity, the human patient will reduce his or her output, letting the robotic device do the work for it. The experiments also demonstrate how including the ldquoassist-as-neededrdquo modification in the controller increases participation from the motor system.}, author = {Wolbrecht, E. T. and Chan, V. and Reinkensmeyer, D. J. and Bobrow, J. E.}, booktitle = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on}, citeulike-article-id = {3360539}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/TNSRE.2008.918389}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4451797}, doi = {10.1109/TNSRE.2008.918389}, journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on}, keywords = {cooperative\_control, rehabilitation\_robotics, stroke\_movement}, number = {3}, pages = {286--297}, posted-at = {2009-02-02 12:06:44}, priority = {5}, title = {Optimizing Compliant, Model-Based Robotic Assistance to Promote Neurorehabilitation}, url = {http://dx.doi.org/10.1109/TNSRE.2008.918389}, volume = {16}, year = {2008} }

TY - JOUR ID - citeulike:3360539 L3 - citeulike-article-id:3360539 N2 - Based on evidence from recent experiments in motor learning and neurorehabilitation, we hypothesize that three desirable features for a controller for robot-aided movement training following stroke are high mechanical compliance, the ability to assist patients in completing desired movements, and the ability to provide only the minimum assistance necessary. This paper presents a novel controller that successfully exhibits these characteristics. The controller uses a standard model-based, adaptive control approach in order to learn the patient's abilities and assist in completing movements while remaining compliant. Assistance-as-needed is achieved by adding a novel force reducing term to the adaptive control law, which decays the force output from the robot when errors in task execution are small. Several tests are presented using the upper extremity robotic therapy device named Pneu-WREX to evaluate the performance of the adaptive, ldquoassist-as-neededrdquo controller with people who have suffered a stroke. The results of these experiments illustrate the ldquoslackingrdquo behavior of human motor control: given the opportunity, the human patient will reduce his or her output, letting the robotic device do the work for it. The experiments also demonstrate how including the ldquoassist-as-neededrdquo modification in the controller increases participation from the motor system. IS - 3 JF - Neural Systems and Rehabilitation Engineering, IEEE Transactions on EP - 297 TI - Optimizing Compliant, Model-Based Robotic Assistance to Promote Neurorehabilitation VL - 16 T2 - Neural Systems and Rehabilitation Engineering, IEEE Transactions on SP - 286 KW - cooperative_control KW - rehabilitation_robotics KW - stroke_movement AU - Wolbrecht, ET AU - Chan, V AU - Reinkensmeyer, DJ AU - Bobrow, JE PY - 2008/// UR - http://dx.doi.org/10.1109/TNSRE.2008.918389 ER -