Evaluation of a Noninvasive Command Scheme for Upper-Limb Prostheses in a Virtual Reality Reach and Grasp Task

C5/C6 tetraplegic patients and transhumeral amputees may be able to use voluntary shoulder motion as command signals for a functional electrical stimulation system or transhumeral prosthesis. Stereotyped relationships, termed “postural synergies,” among the shoulder, forearm, and wrist joints emerge during goal-oriented reaching and transport movements as performed by able-bodied subjects. Thus, the posture of the shoulder can potentially be used to infer the desired posture of the elbow and forearm joints during reaching and transporting movements. We investigated how well able-bodied subjects could learn to use a noninvasive command scheme based on inferences from these postural synergies to control a simulated transhumeral prosthesis in a virtual reality task. We compared the performance of subjects using the inferential command scheme (ICS) with subjects operating the simulated prosthesis in virtual reality according to complete motion tracking of their actual arm and hand movements. Initially, subjects performed poorly with the ICS but improved rapidly with modest amounts of practice, eventually achieving performance only slightly less than subjects using complete motion tracking. Thus, inferring the desired movement of distal joints from voluntary shoulder movements appears to be an intuitive and noninvasive approach for obtaining command signals for prostheses to restore reaching and grasping functions.

[1]  E. Fetz,et al.  Direct control of paralyzed muscles by cortical neurons , 2008, Nature.

[2]  Stephan A Brandt,et al.  Spatial reorganization of cortical motor output maps of stump muscles in human upper-limb amputees , 2002, Neuroscience Letters.

[3]  S. Bandinelli,et al.  Motor reorganization after upper limb amputation in man. A study with focal magnetic stimulation. , 1991, Brain : a journal of neurology.

[4]  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.

[5]  B U Meyer,et al.  Long-term reorganization of motor cortex outputs after arm amputation , 1999, Neurology.

[6]  T. Elbert,et al.  Cortical reorganization and phantom phenomena in congenital and traumatic upper-extremity amputees , 1998, Experimental Brain Research.

[7]  Robert D. Lipschutz,et al.  Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. , 2009, JAMA.

[8]  Rahman Davoodi,et al.  Model-Based Development of Neural Prostheses for Movement , 2007, IEEE Transactions on Biomedical Engineering.

[9]  P. Morasso Three dimensional arm trajectories , 1983, Biological Cybernetics.

[10]  E Marquardt,et al.  The angulation osteotomy of above-elbow stumps. , 1974, Clinical orthopaedics and related research.

[11]  E. Bizzi,et al.  Human arm trajectory formation. , 1982, Brain : a journal of neurology.

[12]  Robert D. Lipschutz,et al.  The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a bilateral shoulder disarticulation amputee , 2004, Prosthetics and orthotics international.

[13]  Martin E. Schwab,et al.  Plasticity of motor systems after incomplete spinal cord injury , 2001, Nature Reviews Neuroscience.

[14]  Miguel A. L. Nicolelis,et al.  Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex , 1999, Nature Neuroscience.

[15]  J. F. Soechting,et al.  Moving effortlessly in three dimensions: does Donders' law apply to arm movement? , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[16]  G.S. Dhillon,et al.  Direct neural sensory feedback and control of a prosthetic arm , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[17]  K. Horch,et al.  Residual function in peripheral nerve stumps of amputees: implications for neural control of artificial limbs. , 2004, The Journal of hand surgery.

[18]  E. Biddiss,et al.  Upper-Limb Prosthetics: Critical Factors in Device Abandonment , 2007, American journal of physical medicine & rehabilitation.

[19]  M. Swiontkowski Targeted Muscle Reinnervation for Real-time Myoelectric Control of Multifunction Artificial Arms , 2010 .

[20]  Veronica J. Santos,et al.  Biomimetic Tactile Sensor Array , 2008, Adv. Robotics.

[21]  J. Lackner,et al.  Rapid adaptation to Coriolis force perturbations of arm trajectory. , 1994, Journal of neurophysiology.

[22]  F. Lacquaniti,et al.  Some factors pertinent to the organization and control of arm movements , 1982, Brain Research.

[23]  Rahman Davoodi,et al.  Prediction of Elbow Trajectory from Shoulder Angles Using Neural Networks , 2008, Int. J. Comput. Intell. Appl..

[24]  A Curt,et al.  How does the human brain deal with a spinal cord injury? , 1998, The European journal of neuroscience.

[25]  P. Morasso Spatial control of arm movements , 2004, Experimental Brain Research.

[26]  C. I. Hovland Human learning and retention , 1951 .

[27]  M. Hauschild,et al.  A Virtual Reality Environment for Designing and Fitting Neural Prosthetic Limbs , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[28]  M Desmurget,et al.  Postural and synergic control for three-dimensional movements of reaching and grasping. , 1995, Journal of neurophysiology.

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

[30]  D A Hong,et al.  Task dependent patterns of muscle activation at the shoulder and elbow for unconstrained arm movements. , 1994, Journal of neurophysiology.

[31]  Rahman Davoodi,et al.  Prediction of Distal Arm Posture in 3-D Space From Shoulder Movements for Control of Upper Limb Prostheses , 2008, Proceedings of the IEEE.

[32]  J. F. Soechting,et al.  Invariant characteristics of a pointing movement in man , 1981, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[33]  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.