Equilibrium point control of a monkey arm simulator by a fast learning tree structured artificial neural network

Morphometry of Macaca mulatta forelimb. III. Moment arm of shoulder and elbow muscles

The conversion of muscle activity into smooth, purposeful movement of the limb depends complexly on the morphometry of muscles and their mechanical action on the skeleton. Although nonhuman primates are common subjects in motor control experiments (Scott [2000] Can J Physiol Pharmacol 78:923-933), little information is available on the morphometric properties of their upper limbs. One key variable is muscle moment arm, or mechanical advantage, which defines how linear motion or force of a muscle is translated into angular motion or torque at a joint. This study reports moment arm values with respect to joint angle (flexion/extension) of 14 muscles spanning the shoulder and elbow in Macaca mulatta. The magnitude of moment arm values ranged widely across muscles. In some muscles mechanical advantage remained constant with joint angle, whereas the moment arm of others varied strongly. The angle (Theta(f)(o)) at which optimal fascicle length (L(f)(o)) occurred showed strong trends, where the elbow-spanning muscles had Theta(f)(o) values clustered at mid-flexion and the shoulder musculature Theta(f)(o) values tended to be grouped around the neutral joint angle of 0 degrees. Estimates of peak muscle torque for flexor and extensor muscle groups at each joint were surprisingly similar in both magnitude and dependency on joint angle. The present study, along with the previous two in this series (Cheng and Scott [2000] J Morphol 245:206-224; Singh et al. [2002] J Morphol 251:323-332), provides a comprehensive description of the morphology of the proximal portion of the limb suitable for the development of a musculoskeletal model of the M. mulatta upper limb.

Role of intrinsic muscle properties in producing smooth movements

Human upper limb movement trajectories have been shown to be quite smooth, in that time derivatives of end point position (r), including d3r/dt3 (i.e., jerk), appear to be minimized during rapid voluntary reaching tasks. Studies have suggested that these movements are implemented by an optimal neural controller which seeks to minimize a cost function, such as average jerk cost, over the course of these motions. While this hypothetical control strategy is widely supported, there are substantial difficulties associated with implementing such a controller, including ambiguities inherent in transformations from Cartesian to joint coordinates, and the lack of appropriate transducers to provide information about higher derivatives of limb motion to the nervous system. Given these limitations, we evaluate the possibility that smoothing of movement might be induced primarily by the intrinsic mechanical properties of muscle by recording the trajectories of inertially loaded muscle with the excitatory input held constant. These trajectories are compared with those predicted by a minimum-jerk optimization model, and by a Hill-based muscle model. Our results indicate that trajectories produced by inertially loaded muscle alone are smooth (in the minimum-jerk sense), and that muscle properties may suffice to account for much of the observed smoothing of voluntary motion, obviating the need for an optimizing neural strategy.

Minimum Muscle-Tension Change Trajectories Predicted by Using a 17-Muscle Model of the Monkey's Arm

Four computational problems to be solved for visually guided reaching movements, hand path, and trajectory formations, coordinate transformation, and calculations of muscle tensions are ill-posed in redundant biological control systems. These problems are ill-posed in the sense that there exist an infinite number of possible solutions. In this article, it is shown that the nervous system can solve those problems simultaneously by imposing a single global constraint: finding the smoothest muscle- tension trajectory that satisfies the desired final hand position, velocity, and acceleration. Horizontal trajectories were simulated by using a l7-muscle model of the monkey's arm as the controlled object. The simulations predicted gently curved hand paths for lateral hand movements and for movements from the side of the body to the front, and a roughly straight hand path for anterioposterior movements. The tangential hand velocities were roughly bell shaped. The simulated results were in agreement with the actual biological movements.