Directional Biases Reveal Utilization of Arm's Biomechanical Properties for Optimization of Motor Behavior

Abstract

Strategies used by the CNS to optimize arm movements in terms of speed, accuracy, and resistance to fatigue remain largely unknown. A hypothesis is studied that the CNS exploits biomechanical properties of multijoint limbs to increase efficiency of movement control. To test this notion, a novel free-stroke drawing task was used that instructs subjects to make straight strokes in as many different directions as possible in the horizontal plane through rotations of the elbow and shoulder joints. Despite explicit instructions to distribute strokes uniformly, subjects showed biases to move in specific directions. These biases were associated with a tendency to perform movements that included active motion at one joint and largely passive motion at the other joint, revealing a tendency to minimize intervention of muscle torque for regulation of the effect of interaction torque. Other biomechanical factors, such as inertial resistance and kinematic manipulability, were unable to adequately account for these significant biases. Also, minimizations of jerk, muscle torque change, and sum of squared muscle torque were analyzed; however, these cost functions failed to explain the observed directional biases. Collectively, these results suggest that knowledge of biomechanical cost functions regarding interaction torque (IT) regulation is available to the control system. This knowledge may be used to evaluate potential movements and to select movement of "low cost." The preference to reduce active regulation of interaction torque suggests that, in addition to muscle energy, the criterion for movement cost may include neural activity required for movement control. I N T R O D U C T I O NDemands of daily living promote optimization of movement characteristics, such as speed and accuracy, while minimizing effort for movement production. How this optimization is achieved has been a focus of extensive research in the area of optimal control of human movements. Various cost functions have been proposed (Todorov 2004); however, it is difficult to ascertain what is actually being optimized, as well as how this optimization process is organized. We hypothesize that the CNS exploits biomechanical properties of the limbs to increase efficiency of movement control. The study specifically focuses on biomechanical factors that influence performance of multijoint arm movements. Three such factors have been recognized: interaction torque (IT), inertial resistance, and kinematic manipulability. IT results from mechanical influence of arm segments on each other during motion (Hollerbach and Flash 1982). Inertial resistance characterizes muscle effort necessary to produce a given acceleration of the arm endpoint (Hogan 1985). Kinematic manipulability characterizes angular velocity at the joints required to produce a given endpoint velocity (Yoshikawa 1985(Yoshikawa , 1990.To produce goal-directed movements, muscular control must be adjusted to all these factors. Each factor depends on movement direction, thus imposing differential demands for...

A preferred pattern of joint coordination during arm movements with redundant degrees of freedom

“…This interpretation is predicted by Goble et al (2007), who studied selection of joint coordination patterns during arm movements constrained to shoulder and elbow horizontal rotations. The opportunity to select a joint coordination pattern was created by a free-stroke drawing task that required subjects to perform straight strokes from the center to the perimeter of a horizontal circle, selecting stroke directions in a random order.…”

“…Subjects consistently preferred certain directions and avoided some other directions. Further investigations yielded a conclusion that the directional preferences were caused by a propensity to use a simplified pattern of shoulder and elbow control during which one of the two joints was rotated actively and the other joint was rotated predominantly passively by interaction torque Dounskaia et al , 2014Goble et al 2007;. The preference for this control pattern resulted in four preferred directions, the two longitudinal directions (along the lower arm axis) achieved through active shoulder motion and passive elbow motion and the two transverse directions (orthogonal to the lower arm axis) achieved through active elbow motion and passive shoulder motion.…”

“…The C condition was provided by placing the circle in the horizontal plane at the shoulder level, as in Goble et al (2007), which restricted joint motions to three DOFs: shoulder, elbow, and wrist horizontal flexion/extension. In the U condition, the horizontal circle was placed at the waist level.…”

Modeling constraints to redundancy in bimanual force coordination

“…In both discrete (Schmidt et al 1979) and continuous (Slifkin and Newell 1999) isometric force production, the variability in the force is scaled with force amplitude, and it has been suggested that the task variability is minimized during motor planning (Harris and Wolpert 1998). Alternatively, an efficient coordination strategy (i.e., minimum muscle force output) has been proposed (Goble et al 2007;Nelson 1983). The unequal coefficients imposed on the finger forces essentially changed the finger "strength" or the relative efficiency of the individual finger force that contributes to the total force output.…”

Joint torque and velocity optimization for a redundant leg of quadruped robot

“…8 The redundant degrees of freedom could also be utilized to optimize various motion performance criteria. [9][10][11][12] On that account, a number of researchers optimized the inverse kinematics of the redundant robot based on various performance criteria. The problems without inequality constraints have closed-form analytical solutions, while those with inequality constraints could obtain numerical solution by iterative method.…”