Minimum muscle tension-change model for human arm movement

1990 ◽  
Vol 11 ◽  
pp. S54 ◽  
Author(s):  
Yoji Uno ◽  
Mitsuo Kawato ◽  
Ryoji Suzuki
1990 ◽  
Vol 15 ◽  
pp. S54
Author(s):  
Yoji Uno ◽  
Mitsuo Kawato ◽  
Ryoji Suzuki

2021 ◽  
Vol 33 (1) ◽  
pp. 129-156
Author(s):  
Masami Iwamoto ◽  
Daichi Kato

This letter proposes a new idea to improve learning efficiency in reinforcement learning (RL) with the actor-critic method used as a muscle controller for posture stabilization of the human arm. Actor-critic RL (ACRL) is used for simulations to realize posture controls in humans or robots using muscle tension control. However, it requires very high computational costs to acquire a better muscle control policy for desirable postures. For efficient ACRL, we focused on embodiment that is supposed to potentially achieve efficient controls in research fields of artificial intelligence or robotics. According to the neurophysiology of motion control obtained from experimental studies using animals or humans, the pedunculopontine tegmental nucleus (PPTn) induces muscle tone suppression, and the midbrain locomotor region (MLR) induces muscle tone promotion. PPTn and MLR modulate the activation levels of mutually antagonizing muscles such as flexors and extensors in a process through which control signals are translated from the substantia nigra reticulata to the brain stem. Therefore, we hypothesized that the PPTn and MLR could control muscle tone, that is, the maximum values of activation levels of mutually antagonizing muscles using different sigmoidal functions for each muscle; then we introduced antagonism function models (AFMs) of PPTn and MLR for individual muscles, incorporating the hypothesis into the process to determine the activation level of each muscle based on the output of the actor in ACRL. ACRL with AFMs representing the embodiment of muscle tone successfully achieved posture stabilization in five joint motions of the right arm of a human adult male under gravity in predetermined target angles at an earlier period of learning than the learning methods without AFMs. The results obtained from this study suggest that the introduction of embodiment of muscle tone can enhance learning efficiency in posture stabilization disorders of humans or humanoid robots.


2002 ◽  
Vol 43 (5) ◽  
pp. 637 ◽  
Author(s):  
Jong Chan Kim ◽  
Soo Chan Kim ◽  
Ki Chang Nam ◽  
Seon Hui Ahn ◽  
Mignon Park ◽  
...  

Author(s):  
Kai Chen ◽  
Richard A. Foulds ◽  
Katharine Swift ◽  
Sergei Adamovich

This paper discusses a new model of neuromuscular control of elbow and shoulder joints based on the Equilibrium Point Hypothesis (EPH). The earlier model [1] suggests that the incorporation of relative damping within reflex loops can maintain the dynamic simplicity of the EPH, while being robust over the range of human joint velocities. The model presented here, extends previous work with the use of experimental Electromyography data of 2 muscles to determine the timing parameters of the virtual trajectories and the inclusion of physiological time delays to account for neural transmission and muscle stimulation/activation delays. This model uses delays presented in the literature by other researchers, with a goal of contributing to a resolution of arguments regarding the controversial arguments in the planning sequences. Therefore, this study attempts to demonstrate the possibility for using descending CNS signals to represent relatively simple, monotonic virtual trajectories of the time varying Equilibrium Point for the control of human arm movement. In addition, the study demonstrates that these virtual trajectories were robust enough to control and coordinated movement of elbow and shoulder joints discussed.


1997 ◽  
Vol 78 (6) ◽  
pp. 2985-2998 ◽  
Author(s):  
Gerald L. Gottlieb ◽  
Qilai Song ◽  
Gil L. Almeida ◽  
Di-An Hong ◽  
Daniel Corcos

Gottlieb, Gerald L., Qilai Song, Gil L. Almeida, Di-an Hong, and Daniel Corcos. Directional control of planar human arm movement. J. Neurophysiol. 78: 2985–2998, 1997. We examined the patterns of joint kinematics and torques in two kinds of sagittal plane reaching movements. One consisted of movements from a fixed initial position with the arm partially outstretched, to different targets, equidistant from the initial position and located according to the hours of a clock. The other series added movements from different initial positions and directions and >40–80 cm distances. Dynamic muscle torque was calculated by inverse dynamic equations with the gravitational components removed. In making movements in almost every direction, the dynamic components of the muscle torques at both the elbow and shoulder were related almost linearly to each other. Both were similarly shaped, biphasic, almost synchronous and symmetrical pulses. These findings are consistent with our previously reported observations, which we termed a linear synergy. The relative scaling of the two joint torques changes continuously and regularly with movement direction. This was confirmed by calculating a vector defined by the dynamic components of the shoulder and elbow torques. The vector rotates smoothly about an ellipse in intrinsic, joint torque space as the direction of hand motion rotates about a circle in extrinsic Cartesian space. This confirms a second implication of linear synergy that the scaling constant between the linearly related joint torques is directionally dependent. Multiple linear regression showed that the torque at each joint scales as a simple linear function of the angular displacement at both joints, in spite of the complex nonlinear dynamics of multijoint movement. The coefficients of this function are independent of the initial arm position and movement distance and are the same for all subjects. This is an unanticipated finding. We discuss these observations in terms of the hypothesis that voluntary, multiple degrees of freedom, rapid reaching movements may use rule-based, feed-forward control of dynamic joint torque. Rule-based control of joint torque with separate dynamic and static controllers is an alternative to models such as those based on the equilibrium point hypotheses that rely on a positionally based controller to produce both dynamic and static torque components. It is also an alternative to feed-forward models that directly solve the problems of inverse dynamics. Our experimental findings are not necessarily incompatible with any of the alternative models, but they describe new, additional findings for which we need to account. The rules are chosen by the nervous system according to features of the kinematic task to couple muscle contraction at the shoulder and elbow in a linear synergy. Speed and load control preserves the relative magnitudes of the dynamic torques while directional control is accomplished by modulating them in a differential manner. This control system operates in parallel with a positional control system that solves the problems of postural stability.


1998 ◽  
Vol 79 (3) ◽  
pp. 1409-1424 ◽  
Author(s):  
Paul L. Gribble ◽  
David J. Ostry ◽  
Vittorio Sanguineti ◽  
Rafael Laboissière

Gribble, Paul L., David J. Ostry, Vittorio Sanguineti, and Rafael Laboissière. Are complex control signals required for human arm movement? J. Neurophysiol. 79: 1409–1424, 1998. It has been proposed that the control signals underlying voluntary human arm movement have a “complex” nonmonotonic time-varying form, and a number of empirical findings have been offered in support of this idea. In this paper, we address three such findings using a model of two-joint arm motion based on the λ version of the equilibrium-point hypothesis. The model includes six one- and two-joint muscles, reflexes, modeled control signals, muscle properties, and limb dynamics. First, we address the claim that “complex” equilibrium trajectories are required to account for nonmonotonic joint impedance patterns observed during multijoint movement. Using constant-rate shifts in the neurally specified equilibrium of the limb and constant cocontraction commands, we obtain patterns of predicted joint stiffness during simulated multijoint movements that match the nonmonotonic patterns reported empirically. We then use the algorithm proposed by Gomi and Kawato to compute a hypothetical equilibrium trajectory from simulated stiffness, viscosity, and limb kinematics. Like that reported by Gomi and Kawato, the resulting trajectory was nonmonotonic, first leading then lagging the position of the limb. Second, we address the claim that high levels of stiffness are required to generate rapid single-joint movements when simple equilibrium shifts are used. We compare empirical measurements of stiffness during rapid single-joint movements with the predicted stiffness of movements generated using constant-rate equilibrium shifts and constant cocontraction commands. Single-joint movements are simulated at a number of speeds, and the procedure used by Bennett to estimate stiffness is followed. We show that when the magnitude of the cocontraction command is scaled in proportion to movement speed, simulated joint stiffness varies with movement speed in a manner comparable with that reported by Bennett. Third, we address the related claim that nonmonotonic equilibrium shifts are required to generate rapid single-joint movements. Using constant-rate equilibrium shifts and constant cocontraction commands, rapid single-joint movements are simulated in the presence of external torques. We use the procedure reported by Latash and Gottlieb to compute hypothetical equilibrium trajectories from simulated torque and angle measurements during movement. As in Latash and Gottlieb, a nonmonotonic function is obtained even though the control signals used in the simulations are constant-rate changes in the equilibrium position of the limb. Differences between the “simple” equilibrium trajectory proposed in the present paper and those that are derived from the procedures used by Gomi and Kawato and Latash and Gottlieb arise from their use of simplified models of force generation.


Sign in / Sign up

Export Citation Format

Share Document