Analysis of the Interaction Torque on the Arm Based on Via-Point Movement

Takashi Oyama, Teruaki Ito


To produce a desired movement, the human motor control system must regular the interaction torque generated owing to the multi-joint structure of the body. In this study, the trajectories of human movements were evaluated considering the interaction torque generated through the elbow and shoulder joints. Measurement experiments were conducted, in which the participants performed movements corresponding to a three-point task, and the results indicated that the interaction torque is correlated with certain characteristics of the trajectories of the arm movements. Moreover, the contribution of the interaction torque in realizing the task differs in the cases of dominant and non-dominant hands. In addition, through a simulation, the interaction torque of simulated trajectories was modulated to examine the corresponding effect on the arm movements. For a point-to-point movement, certain characteristics of the actual movements were reproduced in the simulated trajectories. However, for a three-point movement, the characteristics of the simulated trajectories were only partially similar to those of the measured trajectories. The findings indicate that the interaction torque notably influences the motor control, and the tuning of the interaction torque is more complex than the other criteria of motor control.

Full Text:



Bagesteiro, L. B., & Sainburg, R. L. (2002). Handedness: dominant arm advantages in control of limb dynamics, Journal of Neurophysiology, 88(5), 2408-2421.

Bagesteiro, L. B., & Sainburg, R. L. (2003). Nondominant arm advantages in load compensation during rapid elbow joint movements, Journal of Neurophysiology, 90(3), 1503-1513.

Bastian, A. J., Martin, T. A., Keating, J. G., & Thach, W.T. (1996). Cerebellar ataxia: abnormal control of interaction torques across multiple joints, Journal of Neurophysiology, 76(1), 429-509.

Flanagan, J. R., & Rao, A. K. (1995). Trajectory adaptation to a nonlinear visuomotor transformation: evidence of motion planning in visually perceived space, Journal of Neurophysiology, 74(5), 2174-2178.

Flash, T., & Hogan, N. (1985). The coordination of arm movements: an experimentally confirmed mathematical model, Journal of Neuroscience, 5(7), 1688-1703.

Frith, C. D., Blakemore, S. J., & Wolpert, D. M. (2000). Abnormalities in the awareness and control of action, Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 355(1404), 1771-1788.

Gribble, P. L., & Ostry, D. J. (1999). Compensation for interaction torques during single- and multijoint limb movement, Journal of Neurophysiology, 82(5), 2310-2326.

Harris, C. M., & Wolpert, D. M. (1998). Signal-dependent noise determines motor planning, Nature, 394(6695), 780-784.

Hirashima, M., Ohgane, K., Kudo, K., Hase, K., & Ohtsuki, T. (2003). Counteractive relationship between the interaction torque and muscle torque at the wrist is predestined in ball-throwing, Journal of Neurophysiology, 90(3), 1449-1463.

Karniel, A. (2013). The minimum transition hypothesis for intermittent hierarchical motor control, Frontiers in Computational Neuroscience, 7(12), doi: 10.3389/fncom.2013.00012.

Messier, J., Adamovich, S., Berkinblit, M., Tunik, E., & Poizner, H. (2003). Influence of movement speed on accuracy and coordination of reaching movements to memorized targets in three-dimensional space in a deafferented subject, Experimental Brain Research, 150(4), 399-416.

Morishige, K., Miyamoto, H., Osu, R., & Kawato, M. (2004). Positional variance on via-point reaching movement supports sequential trajectory planning and execution model, IEICE Transactions on Information and Systems, J87-D2(2), 716-725.

Nakano, E., Imamizu, H., Osu, R., Uno, Y., Gomi, H., Yoshioka, T., & Kawato, M. (1999). Quantitative examinations of internal representations for arm trajectory planning: minimum commanded torque change model, Journal of Neurophysiology, 81(5), 2140-2155.

Sainburg, R. L., & Kalakanis, D. (2000). Differences in control of limb dynamics during dominant and nondominant arm reaching, Journal of Neurophysiology, 83(5), 2661-2675.

Sakaguchi, Y., & Ikeda, S. (2007). Motor planning and sparse motor command representation, Neurocomputing, 70(10-12), 1748-1752.

Suzuki, K., & Uno, Y. (2000). Brain adopts the criterion of smoothness for most quick reaching movements, IEICE Transactions on Information and Systems, J88-D-II(2), 711-722.

Wolpert, D. M., Ghahramani, Z., & Jordan, M. I. (1995). An internal model for sensorimotor integration, Science, 269(5232), 1880-1882.

Wolpert, D. M., Miall, R. C., & Kawato, M. (1998). Internal models in the cerebellum, Trends in Cognitive Science, 2(9), 338-347.

Yamasaki, H., Tagami, Y., Fujisawa, H., Hoshi, F., & Nagasaki, H. (2008). Interaction torque contributes to planar reaching at slow speed, Biomedical Engineering Online, 7(1), 27. doi: 10.1186/1475-925X-7-27.

PRINT ISSN No.: 2180-1053
E ISSN No.: 2289-8123