Are Complex Control Signals Required for Human Arm Movement?

1998 ◽  
Vol 79 (3) ◽  
pp. 1409-1424 ◽  
Author(s):  
Paul L. Gribble ◽  
David J. Ostry ◽  
Vittorio Sanguineti ◽  
Rafael Laboissière
Keyword(s):  
Joint Stiffness ◽  
Arm Movement ◽  
Movement Speed ◽  
Muscle Properties ◽  
Complex Control ◽  
Equilibrium Trajectory ◽  
Control Signals ◽  
Human Arm ◽  
Constant Rate ◽  
Arm Motion

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.

Task motion planning for anthropomorphic arms based on human arm movement primitives

2020 ◽  
Vol 47 (5) ◽  
pp. 669-681
Author(s):  
Shiqiu Gong ◽  
Jing Zhao ◽  
Ziqiang Zhang ◽  
Biyun Xie
Keyword(s):  
Motion Planning ◽  
Arm Movement ◽  
Humanoid Robots ◽  
Planning Method ◽  
Service Robots ◽  
Joint Angles ◽  
Content Type ◽  
Structure And Motion ◽  
Human Arm ◽  
Arm Motion

Purpose This paper aims to introduce the human arm movement primitive (HAMP) to express and plan the motions of anthropomorphic arms. The task planning method is established for the minimum task cost and a novel human-like motion planning method based on the HAMPs is proposed to help humans better understand and plan the motions of anthropomorphic arms. Design/methodology/approach The HAMPs are extracted based on the structure and motion expression of the human arm. A method to slice the complex tasks into simple subtasks and sort subtasks is proposed. Then, a novel human-like motion planning method is built through the selection, sequencing and quantification of HAMPs. Finally, the HAMPs are mapped to the traditional joint angles of a robot by an analytical inverse kinematics method to control the anthropomorphic arms. Findings For the exploration of the motion laws of the human arm, the human arm motion capture experiments on 12 subjects are performed. The results show that the motion laws of human arm are reflected in the selection, sequencing and quantification of HAMPs. These motion laws can facilitate the human-like motion planning of anthropomorphic arms. Originality/value This study presents the HAMPs and a method for selecting, sequencing and quantifying them in human-like style, which leads to a new motion planning method for the anthropomorphic arms. A similar methodology is suitable for robots with anthropomorphic arms such as service robots, upper extremity exoskeleton robots and humanoid robots.

Coordinating two degrees of freedom during human arm movement: load and speed invariance of relative joint torques

1996 ◽  
Vol 76 (5) ◽  
pp. 3196-3206 ◽  
Author(s):  
G. L. Gottlieb ◽  
Q. Song ◽  
D. A. Hong ◽  
D. M. Corcos
Keyword(s):  
Degrees Of Freedom ◽  
Arm Movement ◽  
Movement Speed ◽  
Emg Activity ◽  
Joint Torques ◽  
Muscle Torque ◽  
Shoulder Flexion ◽  
Human Arm ◽  
The Individual ◽  
Finger Tip

1. Eight subjects performed three series of pointing tasks with the unconstrained arm. Series one and two required subjects to move between two fixed targets as quickly as possible with different weights attached to the wrist. By specifying initial and final positions of the finger tip, the first series was performed by flexion of both shoulder and elbow and the second by shoulder flexion and elbow extension. The third series required flexion at both joints, and subjects were instructed to vary movement speed. We examined how variations in load or intended speed were associated with changes in the amount and timing of the electromyographic (EMG) activity and the net muscle torque production. 2. EMG and torque patterns at the individual joints varied with load and speed according to most of the same rules we have described for single-joint movements. 1) Movements were produced by biphasic torque pulses and biphasic or triphasic EMG bursts at both joints. 2) The accelerating impulse was proportional to the load when the subject moved “as fast and accurately as possible” or to speed if that was intentionally varied. 3) The area of the EMG bursts of agonist muscles varied with the impulse. 4) The rates of rise of the net muscle torques and of the EMG bursts were proportional to intended speed and insensitive to inertial load. 5) The areas of the antagonist muscle EMG bursts were proportional to intended movement speed but showed less dependence on load, which is unlike what is observed during single-joint movements. 3. Comparisons across joints showed that the impulse produced at the shoulder was proportional to that produced at the elbow as both varied together with load and speed. The torques at the two joints varied in close synchrony, achieving maxima and going through zero almost simultaneously. 4. We hypothesize that “coordination” of the elbow and shoulder is by the planning and generation of synchronized, biphasic muscle torque pulses that remain in near linear proportionality to each other throughout most of the movement. This linear synergy produces movements with the commonly observed kinematic properties and that are preserved over changes in speed and load.

Origins of the power law relation between movement velocity and curvature: modeling the effects of muscle mechanics and limb dynamics

1996 ◽  
Vol 76 (5) ◽  
pp. 2853-2860 ◽  
Author(s):  
P. L. Gribble ◽  
D. J. Ostry
Keyword(s):  
Power Law ◽  
Neural Control ◽  
Muscle Mechanics ◽  
Movement Control ◽  
Arm Movement ◽  
Movement Velocity ◽  
Muscle Properties ◽  
Control Signals ◽  
Limb Dynamics ◽  
Speed Up

1. When subjects trace patterns such as ellipses, the instantaneous velocity of movements is related to the instantaneous curvature of the trajectories according to a power law-movements tend to slow down when curvature is high and speed up when curvature is low. It has been proposed that this relationship is centrally planned. 2. The arm's muscle properties and dynamics can significantly affect kinematics. Even under isometric conditions, muscle mechanical properties can affect the development of muscle forces and torques. Without a model that accounts for these effects, it is difficult to distinguish between kinematic patterns that are attributable to central control and patterns that arise because of dynamics and muscle properties and are not represented in the underlying control signals. 3. In this paper we address the nature of the control signals that underlie movements that obey the power law. We use a numerical simulation of arm movement control based on the lambda version of the equilibrium point hypothesis. We demonstrate that simulated elliptical and circular movements, and elliptical force trajectories generated under isometric conditions, obey the power law even though there was no relation between curvature and speed in the modeled control signals. 4. We suggest that limb dynamics and muscle mechanics-specifically, the springlike properties of muscles-can contribute significantly to the emergence of the power law relationship in kinematics. Thus, without a model that accounts for these effects, care must be taken when making inferences about the nature of neural control.

Selective activation of quadriceps muscle fibers according to bicycling rate

1984 ◽  
Vol 57 (2) ◽  
pp. 371-379 ◽  
Author(s):  
G. Citterio ◽  
E. Agostoni
Keyword(s):  
Muscle Activity ◽  
Peak Power ◽  
Moving Average ◽  
Quadriceps Muscle ◽  
Velocity Curve ◽  
Movement Speed ◽  
Selective Activation ◽  
Muscle Properties ◽  
Inspiratory Muscles ◽  
Constant Rate

Moving average electromyography (MA) of quadriceps muscle bellies has been recorded during bicycling at different rates (30–70 cycles/min) or forces (1–3 kg). For power increments (50–100%) achieved by increasing force at constant rate, MA during pedal downstroke always increased. For similar power increments achieved by increasing the rate at constant force, MA did not increase (37% of cases), increased less (37%), or increased similarly (26%). Investigations by others on the rat suggest that the lack of increase of MA despite power increment was not compensated by other muscle activity; hence it indicates a shift from slow to fast fibers, which provide greater power per unit stimulus. Smaller increase of MA with increasing rate rather than force at isopower could depend on this shift or on muscle properties, if operating on ascending limb of power-velocity curve. This, however, does not seem the case for slow fibers, which should develop peak power at about 25 cycles/min. Hence, fibers of quadriceps muscle of humans seem selectively activated according to movement speed, as previously found in inspiratory muscles of rabbits.

A Myokinetic Arm Model for Estimating Joint Torque and Stiffness From EMG Signals During Maintained Posture

2009 ◽  
Vol 101 (1) ◽  
pp. 387-401 ◽  
Author(s):  
Duk Shin ◽  
Jaehyo Kim ◽  
Yasuharu Koike
Keyword(s):  
Perturbation Method ◽  
Muscle Activation ◽  
Muscle Tension ◽  
Joint Stiffness ◽  
Quadratic Function ◽  
Joint Torque ◽  
Physiological Data ◽  
Muscle Properties ◽  
Human Arm ◽  
Novel Method

The perturbation method has been used to measure stiffness of the human arm with a manipulator. Results are averages of stiffness during short perturbation intervals (<0.4 s) and also vary with muscle activation. We therefore propose a novel method for estimating static arm stiffness from muscle activation without the use of perturbation. We developed a mathematical muscle model based on anatomical and physiological data to estimate joint torque solely from EMG. This model expresses muscle tension using a quadratic function of the muscle activation and parameters representing muscle properties. The parameters are acquired from the relation between EMG and measured torque. Using this model, we were able to reconstruct joint torque from EMG signals with or without co-contraction. Joint stiffness is directly obtained by differentiation of this model analytically. We confirmed that the proposed method can be used to estimate joint torque, joint stiffness, and stiffness ellipses simultaneously for various postures with the same parameters and produces results consistent with the conventional perturbation method.

ROBOTIC HANDWRITING

2005 ◽  
Vol 02 (01) ◽  
pp. 105-124 ◽  
Author(s):  
VELJKO POTKONJAK
Keyword(s):  
Mathematical Models ◽  
Muscle Fatigue ◽  
Simulation Study ◽  
Robot Control ◽  
Robot Arm ◽  
Redundancy Resolution ◽  
Kinematic Redundancy ◽  
New Concepts ◽  
Human Arm ◽  
Arm Motion

Handwriting has always been considered an important human task, and accordingly it has attracted the attention of researchers working in biomechanics, physiology, and related fields. There exist a number of studies on this area. This paper considers the human–machine analogy and relates robots with handwriting. The work is two-fold: it improves the knowledge in biomechanics of handwriting, and introduces some new concepts in robot control. The idea is to find the biomechanical principles humans apply when resolving kinematic redundancy, express the principles by means of appropriate mathematical models, and then implement them in robots. This is a step forward in the generation of human-like motion of robots. Two approaches to redundancy resolution are described: (i) "Distributed Positioning" (DP) which is based on a model to represent arm motion in the absence of fatigue, and (ii) the "Robot Fatigue" approach, where robot movements similar to the movements of a human arm under muscle fatigue are generated. Both approaches are applied to a redundant anthropomorphic robot arm performing handwriting. The simulation study includes the issues of legibility and inclination of handwriting. The results demonstrate the suitability and effectiveness of both approaches.

scholarly journals Targeting in Virtual Workspaces: motor learning consolidates spatial memory for performance clusters

2019 ◽  
Author(s):  
Bradly Alicea ◽  
Corey Bohil ◽  
Frank Biocca ◽  
Charles Owen
Keyword(s):  
Repeated Measures ◽  
Target Location ◽  
Movement Time ◽  
Three Dimensional ◽  
Arm Movement ◽  
Hierarchical Cluster ◽  
Movement Speed ◽  
Advantages And Disadvantages ◽  
Training Interval ◽  
Speed And Accuracy

Our objective was to focus on linkages between the process of learning and memory and the placement of objects within an array of targets in a virtual workspace. Participants were instructed to place virtual objects serially within a three-dimensional target array. One phase presented each target sequentially, and required participants to make timed ballistic arm movements. The other phase presented all nine targets simultaneously, which required ballistic arm movement towards the correct target location as recalled from the learning phase. Movement time and accuracy were assessed using repeated-measures ANOVA, a hierarchical cluster analysis, and a multiple linear regression. Collectively, this revealed numerous speed and accuracy advantages and disadvantages for various positional combinations. Upper positions universally yielded longer movement times and larger error measurements. Individual ability for mental rotation combined with task learning over a fixed training interval was found to predict accuracy for specific locations. The prediction that location influences movement speed and accuracy was supported, but with some caveats. These results may be particularly useful in the design of instructor stations and other hybrid physical-virtual workspaces.

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