Abstract
In this paper, we present a corticospinal network for control voluntary movements within constraints from neurophysiology. Neural controller is proposed to follow desired joint trajectories of a single link controlled by an agonist-ant agonist pair of actuator with muscle-like properties. This research work involves the design and implementation of an efficient biomechanical model of the animal muscular actuation system. In this biomechanical system the implementation of a mathematical model for whole skeletal muscle force generation on DC motors is carried out. Through experimental results, we showed that neural controller exhibits key kinematic properties of human movements, dynamics compensation and including asymmetric bell-shaped velocity profiles. Neural controller suggests how the brain may set automatic and volitional gating mechanisms to vary the balance of static and dynamic feedback information to guide the movement command and to compensate for external forces.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
García-Córdova, F., Guerrero, A., Pedreño, J.L, López-Coronado, J. (2001). “Emulation of the animal muscular actuation system in an experimental platform”. Proceedings of the IEEE Conference on Systems, Man, and Cybernetics, October 7–10, Tucson, AZ.
Kettner, R.E., Schwartz, A.B., and Georgopoulos, A.P., “Primate motor cortex and free arm move-ments to visual targets in three-dimensional space. III. Positional gradients and population coding of movement direction from various movements origin,” The journal of Neuroscience, 8(8):2938–2947, 1988.
Riehle, A., Mackay, W.A., and Renqui, J., “Are extent and force independent movement parameter? Preparation and movement-related neuronal activity in the monkey cortex”, Experimental Brain research, 99(1), 56–74, 1994.
Bizzi, E., Accornero, N., Chapple, W., and Hogan, N., “Posture control and trajectory formation during arm movement,” The Journal of Neuro-science, 4(11):2738–2744, 1984.
Bullock, D., Cisek, P., and Grossberg, S., “Cortical networks for control of voluntary arm movements under variable force conditions,” Cere-bral Cortex, 8, 48–62, 1998.
Kalaska, J.F., and Crammond, D.J., “Cerebral cortical mechanics of reaching movements,” Science, 255:1517–1527, 1992.
García-Córdova, F., Guerrero, A., Pedreño, J.L, López-Coronado, J., (2001). “A cortical network for vcontrol of voluntary movements in robotics sytems”. Proceedings of the IEEE Conference on Systems, Man, and Cybernetics, October 7–10, Tucson, AZ.
García-Cordova, F., Coronado, J.L., Guerrero, A., “A Neural Controller for an artificial finger built with SMA actuators”, Symposium on Intelligent Robotic Systems (SIRS99). July 1999. Coimbra (Portugal).
García-Cordova, F., Coronado, J.L., Guerrero, A., “Design of an anthropomorphic finger using shape memory alloy springs”, Proceedings of the IEEE on System, Man and Cybernetic (SMC99). September 1999. Tokyo (Japan).
Bullock, D. and Grossberg, S., “The VITE model: A neural command circuit for generating arm and articulatory trajectories,” In J.A.S. Kelso, A.J. Mandell, and M.F. Shlesinger (Eds), Dynamic patters in complex systems. Singapore: World Scientific Publishers, 1988.
Hannaford, Blake and Winters, Jack, “Actuator properties and movement control: Biological and technological models”, Multiple Muscle systems: Biomechanics and Movement Organization, J.M. Winters and S.L-Y. Woo (eds.), pp 101–120, 1990 Springer-Verlag.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
García-Córdova, F., Molina-Vilaplana, J., López-Coronado, J. (2002). A Corticospinal Network for Control of Voluntary Movements of a Physiologically Based Experimental Platform. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_36
Download citation
DOI: https://doi.org/10.1007/3-540-46084-5_36
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44074-1
Online ISBN: 978-3-540-46084-8
eBook Packages: Springer Book Archive