Computing the optimal trajectory of arm movement: the TOPS (Task Optimization in the Presence of Signal-Dependent Noise) model

A new framework is proposed for motor control: the Task Optimization in the Presence of Signal-dependent noise (TOPS) model. By using this model, we need not specify the position, velocity, and acceleration of the hand at the start and end of a movement. We can easily apply this model to any task setting as well as to simple point-to-point reaching movements. Estimation of the optimal trajectories using computer simulations showed that in the case of a moving target, the trajectories estimated by this model are very different from those estimated by the minimum jerk model.

[1]  P. Viviani,et al.  A developmental study of the relationship between geometry and kinematics in drawing movements. , 1991, Journal of experimental psychology. Human perception and performance.

[2]  D. Meyer,et al.  Attention and Performance XIV , 1973 .

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

[4]  T. Sejnowski,et al.  A Computational Model of Birdsong Learning by Auditory Experience and Auditory Feedback , 1998 .

[5]  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.

[6]  P. Viviani,et al.  The law relating the kinematic and figural aspects of drawing movements. , 1983, Acta psychologica.

[7]  M. A. Arbib,et al.  Models of Trajectory Formation and Temporal Interaction of Reach and Grasp. , 1993, Journal of motor behavior.

[8]  Yasuharu Koike,et al.  Estimation of dynamic joint torques and trajectory formation from surface electromyography signals using a neural network model , 1995, Biological Cybernetics.

[9]  M. Kawato,et al.  Formation and control of optimal trajectory in human multijoint arm movement , 1989, Biological Cybernetics.

[10]  E. Bizzi,et al.  Posture control and trajectory formation during arm movement , 1984, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[11]  J. Brugge,et al.  Central Auditory Processing and Neural Modeling , 2012, Springer US.

[12]  H.F. Durrant-Whyte,et al.  A new approach for filtering nonlinear systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[13]  Max Donath,et al.  American Control Conference , 1993 .

[14]  P. Fitts.  The information capacity of the human motor system in controlling the amplitude of movement. , 1954, Journal of experimental psychology.

[15]  M. Kawato.  Optimization and learning in neural networks for formation and control of coordinated movement , 1993 .

[16]  Yiannis Aloimonos,et al.  Vision and action , 1995, Image Vis. Comput..

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

[18]  Daniel M. Wolpert,et al.  Signal-dependent noise determines motor planning , 1998, Nature.

[19]  D Goodman,et al.  On the nature of human interlimb coordination. , 1979, Science.