Kinematics and Kinetics of Multijoint Reaching in Nonhuman Primates

Section: Discussionmentioning

confidence: 73%

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

Dounskaia

Wang

2014

“…Here, we addressed the role of biomechanical factors in directional preferences by taking advantage of horizontal shoulder-elbow movements for which dynamic models have been developed and widely used (Dounskaia et al 2002a;Hoy and Zernicke 1985;Putnam 1993;Schneider et al 1989) and influential biomechanical factors have been extensively explored (Graham et al 2003;Hogan 1985;Hollerbach and Flash 1982). The obtained results support the notion that biomechanical factors, and specifically IT, influence organization of multijoint movements.…”

Section: Discussionmentioning

confidence: 99%

“…The magnitude of the resultant velocity experienced at the endpoint is greater when the two joints rotate in flexion compared with the case when the shoulder flexes and the elbow extends. The dependence of endpoint velocity on the joint coordination pattern, referred to as kinematic manipulability, has been quantified for multijoint movements of robotic systems by Yoshikawa (1985Yoshikawa ( , 1990 and discussed with respect to arm movements (Dounskaia 2007; Graham et al 2003;Sabes and Jordan 1997). The matrix of kinematic manipulability (T KM ) quantifying this relationship has the form…”

Section: Index Of Kinematic Manipulability (I Km )mentioning

confidence: 99%

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

Goble¹,

Zhang²,

Shimansky³

et al. 2007

101

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...

“…Kinematic manipulability has been quantified for multijoint movements of robotic arms by Yoshikawa (1985Yoshikawa ( , 1990 and discussed with respect to arm movements (Graham et al 2003;Dounskaia 2007;Sabes and Jordan 1997). The matrix of kinematic manipulability quantifying this relationship is T KM ϭ JJ=.…”

Section: Appendixmentioning

confidence: 99%

The role of intrinsic factors in control of arm movement direction: implications from directional preferences

Dounskaia¹,

Goble

Wang³

2011

-The role of extrinsic and intrinsic factors in control of arm movement direction remains under debate. We addressed this question by investigating preferences in selection of movement direction and whether factors causing these preferences have extrinsic or intrinsic nature. An unconstrained freestroke drawing task was used during which participants produced straight strokes on a horizontal table, choosing the direction and the beginning and end of each stroke arbitrarily. The variation of the initial arm postures across strokes provided a possibility to distinguish between the extrinsic and intrinsic origins of directional biases. Although participants were encouraged to produce strokes equally in all directions, each participant demonstrated preferences for some directions over the others. However, the preferred directions were not consistent across participants, suggesting no directional preferences in extrinsic space. Consistent biases toward certain directions were revealed in intrinsic space representing initial arm postures. Factors contributing to the revealed preferences were analyzed within the optimal control framework. The major bias was explained by a tendency predicted by the leading joint hypothesis (LJH) to minimize active interference with interaction torque generated by shoulder motion at the elbow. Some minor biases may represent movements of minimal inertial resistance or maximal kinematic manipulability. These results support a crucial role of intrinsic factors in control of the movement direction of the arm. Based on the LJH interpretation of the major bias, we hypothesize that the dominant tendency was to minimize neural effort for control of arm intersegmental dynamics. Possible organization of neural processes underlying optimal selection of movement direction is discussed. arm movements; optimal control; multijoint; movement planning; intersegmental dynamics CONTROL OF ARM MOVEMENT DIRECTION has been extensively studied. Correlation between directions of motion and activity of neurons in primary motor cortex (M1) revealed with a population vector method (Georgopoulos et al. 1982) suggested a cortical representation of movement direction. This finding supported an interpretation that movement direction is planned in extrinsic space and is implemented through control relying on inverse kinematic and dynamic transformations. However, later findings revealed that M1 also contains neurons tuned to joint motions and muscle torques (Scott et al. 2001;Caminiti et al. 1991). Furthermore, directionally tuned neurons are not uniformly distributed. During horizontal shoulderelbow movements, directions achieved with flexion at one joint and extension at the other joint are represented by much more numerous neurons compared with directions in which both joints flex or both extend (Scott et al. 2001). These findings suggested that intrinsic factors (associated with joint motions and intersegmental dynamics) may play a primary role in formation of movement characteristics, including direction.Here, we...