3DOM: A 3 Degree of Freedom Manipulandum to Investigate Redundant Motor Control

This paper presents a novel robotic interface to investigate the neuromechanical control of redundant planar arm movements. A unique aspect of this device is the third axis by which the wrist, and hence the pose of the arm can be fully constrained. The topology is based on a 5R, closed loop pantograph, with a decoupled wrist flexion/extension cable actuated mechanism. The design and characterization (in terms of range of motion, impedance, friction and dynamics) are described in this paper. This device is lightweight, safe and has high force capabilities and low impedance. Simple experiments illustrate the advantages of this device for the investigation of redundant motor control in humans.

[1]  Vincent Hayward,et al.  International Conference on Intelligent Robots and Systems The Pantograph Mk-II : A Haptic Instrument * , 2005 .

[2]  Byoung Gook Loh,et al.  Kinematic analysis of 7 degrees of freedom upper-limb exoskeleton robot with tilted shoulder abduction , 2013 .

[3]  Mitsuo Kawato,et al.  Human arm stiffness and equilibrium-point trajectory during multi-joint movement , 1997, Biological Cybernetics.

[4]  D.J. Reinkensmeyer,et al.  Biomimetic orthosis for the neurorehabilitation of the elbow and shoulder (BONES) , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[5]  P. Neilson.  Speed of response or bandwidth of voluntary system controlling elbow position in intact man , 1972, Medical and biological engineering.

[6]  Simon C Gandevia,et al.  Postural control at the human wrist , 2008, The Journal of physiology.

[7]  W. Rymer,et al.  Understanding and treating arm movement impairment after chronic brain injury: progress with the ARM guide. , 2014, Journal of rehabilitation research and development.

[8]  E. Bizzi,et al.  Neural, mechanical, and geometric factors subserving arm posture in humans , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[9]  Etienne Burdet,et al.  A Robust and Sensitive Metric for Quantifying Movement Smoothness , 2012, IEEE Transactions on Biomedical Engineering.

[10]  N. A. Bernshteĭn.  The co-ordination and regulation of movements , 1967 .

[11]  Etienne Burdet,et al.  Hi5: A versatile dual-wrist device to study human-human interaction and bimanual control , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  B. Brewer,et al.  Poststroke Upper Extremity Rehabilitation: A Review of Robotic Systems and Clinical Results , 2007, Topics in stroke rehabilitation.

[13]  Rieko Osu,et al.  CNS Learns Stable, Accurate, and Efficient Movements Using a Simple Algorithm , 2008, The Journal of Neuroscience.

[14]  F. Mussa-Ivaldi,et al.  The motor system does not learn the dynamics of the arm by rote memorization of past experience. , 1997, Journal of neurophysiology.

[15]  Sheng Quan Xie,et al.  Exoskeleton robots for upper-limb rehabilitation: state of the art and future prospects. , 2012, Medical engineering & physics.

[16]  T. Milner,et al.  Compensation for mechanically unstable loading in voluntary wrist movement , 2004, Experimental Brain Research.

[17]  Daniel M. Wolpert,et al.  A modular planar robotic manipulandum with end-point torque control , 2009, Journal of Neuroscience Methods.

[18]  F A Mussa-Ivaldi,et al.  Adaptive representation of dynamics during learning of a motor task , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[19]  Rieko Osu,et al.  The central nervous system stabilizes unstable dynamics by learning optimal impedance , 2001, Nature.

[20]  Roger Weber,et al.  Tools for understanding and optimizing robotic gait training. , 2006, Journal of rehabilitation research and development.

[21]  Hermano Igo Krebs,et al.  MIT-MANUS: a workstation for manual therapy and training. I , 1992, [1992] Proceedings IEEE International Workshop on Robot and Human Communication.

[22]  Etienne Burdet,et al.  Evaluation of parametric and nonparametric nonlinear adaptive controllers , 1998, Robotica.

[23]  E. Burdet,et al.  Robot-assisted rehabilitation of hand function. , 2010, Current opinion in neurology.

[24]  J. Klein,et al.  Breaking It Down Is Better: Haptic Decomposition of Complex Movements Aids in Robot-Assisted Motor Learning , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[25]  P. Morasso,et al.  Braccio di Ferro: a new haptic workstation for neuromotor rehabilitation. , 2006, Technology and health care : official journal of the European Society for Engineering and Medicine.

[26]  Hermano I Krebs,et al.  Rehabilitation robotics: pilot trial of a spatial extension for MIT-Manus , 2004, Journal of NeuroEngineering and Rehabilitation.

[27]  John M. Hollerbach,et al.  Dynamic interactions between limb segments during planar arm movement , 1982, Biological Cybernetics.

[28]  Stephen H. Scott,et al.  Apparatus for measuring and perturbing shoulder and elbow joint positions and torques during reaching , 1999, Journal of Neuroscience Methods.

[29]  Jean-Pierre Merlet,et al.  Jacobian, Manipulability, Condition Number and Accuracy of Parallel Robots , 2005, ISRR.