Control Of Human Arm Movements Research Articles

Robust sensorimotor control of human arm model under state-dependent noises, control-dependent noises and additive noises

The robust control of human arm movements is planned by the integration of sensory information, sensorimotor transformation and human brain computation. The human arm is controlled to adopt an acceptable posture in a robust optimal way. Due to the intelligent nature of human judgments, the application of the Takagi–Sugeno (T–S) fuzzy model to human judgments may be useful for emulating intelligent computation in the prefrontal cortex of the human brain in the sensorimotor control of human arm movements. In this study, we aimed to develop a robust fuzzy estimator-based control scheme to mimic the sensorimotor control of realistic planar movements of the human arm. The state variables of the planar model of the human arm are all available based on visual and proprioception information. Using posture (state) estimation based on human sensory information in the human brain, robust fuzzy estimator-based control was introduced to model the sensorimotor reference tracking control of arm movements in the presence of internal noises, state-dependent noises and environmental noises. Based on the fuzzy interpolation of a nonlinear stochastic arm system, the complex noise-tolerant robust control of the human arm tracking problem was simplified by solving a set of linear matrix inequalities using Newton׳s iterative method via an interior point scheme for convex optimization. Finally, a simulation was conducted to illustrate the control procedure and to validate the performance of robust fuzzy estimator-based sensorimotor control for the human arm system.

Spinal circuits can accommodate interaction torques during multijoint limb movements.

The dynamic interaction of limb segments during movements that involve multiple joints creates torques in one joint due to motion about another. Evidence shows that such interaction torques are taken into account during the planning or control of movement in humans. Two alternative hypotheses could explain the compensation of these dynamic torques. One involves the use of internal models to centrally compute predicted interaction torques and their explicit compensation through anticipatory adjustment of descending motor commands. The alternative, based on the equilibrium-point hypothesis, claims that descending signals can be simple and related to the desired movement kinematics only, while spinal feedback mechanisms are responsible for the appropriate creation and coordination of dynamic muscle forces. Partial supporting evidence exists in each case. However, until now no model has explicitly shown, in the case of the second hypothesis, whether peripheral feedback is really sufficient on its own for coordinating the motion of several joints while at the same time accommodating intersegmental interaction torques. Here we propose a minimal computational model to examine this question. Using a biomechanics simulation of a two-joint arm controlled by spinal neural circuitry, we show for the first time that it is indeed possible for the neuromusculoskeletal system to transform simple descending control signals into muscle activation patterns that accommodate interaction forces depending on their direction and magnitude. This is achieved without the aid of any central predictive signal. Even though the model makes various simplifications and abstractions compared to the complexities involved in the control of human arm movements, the finding lends plausibility to the hypothesis that some multijoint movements can in principle be controlled even in the absence of internal models of intersegmental dynamics or learned compensatory motor signals.

Control of human arm movement in machine-human cooperative welding process

This paper studies accurate control of human arm movement in machine-human cooperative control of GTAW process. An innovative teleoperated virtualized welding platform is utilized to conduct dynamic experiments to correlate the human welder arm movement with the visual signal input. An adaptive ANFIS model is proposed to model the intrinsic nonlinear and time-varying characteristic of the human welder response. A model based predictive control algorithm is then proposed and an analytical solution is derived. Human control experimental results verify that the proposed controller is able to track varying set-points and is robust under measurement and input disturbances.

Models of human movement: Trajectory planning and inverse kinematics studies

The seemingly simple everyday actions of moving limb and body to accomplish a motor task or interact with the environment are incredibly complex. To reach for a target we first need to sense the target’s position with respect to an external coordinate system; we then need to plan a limb trajectory which is executed by issuing an appropriate series of neural commands to the muscles. These, in turn, exert appropriate forces and torques on the joints leading to the desired movement of the arm. Here we review some of the earlier work as well as more recent studies on the control of human movement, focusing on behavioral and modeling studies dealing with task space and joint-space movement planning. At the task level, we describe studies investigating trajectory planning and inverse kinematics problems during point-to-point reaching movements as well as two-dimensional (2D) and three-dimensional (3D) drawing movements. We discuss models dealing with the two-thirds power law, particularly differential geometrical approaches dealing with the relation between path geometry and movement velocity. We also discuss optimization principles such as the minimum-jerk model and the isochrony principle for point-to-point and curved movements.We next deal with joint-space movement planning and generation, discussing the inverse kinematics problem and common solutions to the problems of kinematic redundancy. We address the question of which reference frames are used by the nervous system and review studies examining the employment of kinematic constraints such as Donders’ and Listing’s laws. We also discuss optimization approaches based on Riemannian geometry.One principle of motor coordination during human locomotion emerging from this body of work is the intersegmental law of coordination. However, the nature of the coordinate systems underlying motion planning remains of interest as they are related to the principles governing the control of human arm movements.

Visual-haptic cue integration with spatial and temporal disparity during pointing movements

Many perceptual cue combination studies have shown that humans can integrate sensory information across modalities as well as within a modality in a manner that is close to optimal. While the limits of sensory cue integration have been extensively studied in the context of perceptual decision tasks, the evidence obtained in the context of motor decisions provides a less consistent picture. Here, we studied the combination of visual and haptic information in the context of human arm movement control. We implemented a pointing task in which human subjects pointed at an invisible unknown target position whose vertical position varied randomly across trials. In each trial, we presented a haptic and a visual cue that provided noisy information about the target position half-way through the reach. We measured pointing accuracy as function of haptic and visual cue onset and compared pointing performance to the predictions of a multisensory decision model. Our model accounts for pointing performance by computing the maximum a posteriori estimate, assuming minimum variance combination of uncertain sensory cues. Synchronicity of cue onset has previously been demonstrated to facilitate the integration of sensory information. We tested this in trials in which visual and haptic information was presented with temporal disparity. We found that for our sensorimotor task temporal disparity between visual and haptic cue had no effect. Sensorimotor learning appears to use all available information and to apply the same near-optimal rules for cue combination that are used by perception.

A modular planar robotic manipulandum with end-point torque control

Robotic manipulanda are extensively used in investigation of the motor control of human arm movements. They permit the application of translational forces to the arm based on its state and can be used to probe issues ranging from mechanisms of neural control to biomechanics. However, most current designs are optimized for studying either motor learning or stiffness. Even fewer include end-point torque control which is important for the simulation of objects and the study of tool use. Here we describe a modular, general purpose, two-dimensional planar manipulandum (vBOT) primarily optimized for dynamic learning paradigms. It employs a carbon fibre arm arranged as a parallelogram which is driven by motors via timing pulleys. The design minimizes the intrinsic dynamics of the manipulandum without active compensation. A novel variant of the design (WristBOT) can apply torques at the handle using an add-on cable drive mechanism. In a second variant (StiffBOT) a more rigid arm can be substituted and zero backlash belts can be used, making the StiffBOT more suitable for the study of stiffness. The three variants can be used with custom built display rigs, mounting, and air tables. We investigated the performance of the vBOT and its variants in terms of effective end-point mass, viscosity and stiffness. Finally we present an object manipulation task using the WristBOT. This demonstrates that subjects can perceive the orientation of the principal axis of an object based on haptic feedback arising from its rotational dynamics.

Model-Based Sensorimotor Integration for Multi-Joint Control: Development of a Virtual Arm Model

An integrated, sensorimotor virtual arm (VA) model has been developed and validated for simulation studies of control of human arm movements. Realistic anatomical features of shoulder, elbow and forearm joints were captured with a graphic modeling environment, SIMM. The model included 15 musculotendon elements acting at the shoulder, elbow and forearm. Muscle actions on joints were evaluated by SIMM generated moment arms that were matched to experimentally measured profiles. The Virtual Muscle (VM) model contained appropriate admixture of slow and fast twitch fibers with realistic physiological properties for force production. A realistic spindle model was embedded in each VM with inputs of fascicle length, gamma static (gamma(stat)) and dynamic (gamma(dyn)) controls and outputs of primary (I(a)) and secondary (II) afferents. A piecewise linear model of Golgi Tendon Organ (GTO) represented the ensemble sampling (I(b)) of the total muscle force at the tendon. All model components were integrated into a Simulink block using a special software tool. The complete VA model was validated with open-loop simulation at discrete hand positions within the full range of alpha and gamma drives to extrafusal and intrafusal muscle fibers. The model behaviors were consistent with a wide variety of physiological phenomena. Spindle afferents were effectively modulated by fusimotor drives and hand positions of the arm. These simulations validated the VA model as a computational tool for studying arm movement control. The VA model is available to researchers at website http://pt.usc.edu/cel .

Computational Approaches to Human Arm Movement Control – A Review

Human arm movement control theories are reviewed in the current paper. The motor planning problem stated as a generation of a time plan for the execution of a movement task, is a major concern of the current paper. It will be suggested that computational models of motor control have a strong potential for the use in the area of human motor rehabilitation. Their use can be discriminated in three main areas of application: the generation of correct trajectories to be demonstrated to human subjects during physiotherapy; the assessment of motion disorders and movement quality; and the devising of challenging interaction exercises to promote recovery.

Posture-based or trajectory-based movement planning: a comparison of direct and indirect pointing movements

Various models have been proposed in the literature to explain the control of human arm movements. To make a quantitative comparison between the predictions of various models, we tested subjects for movements to targets on a vertical screen in various conditions. Subjects were asked to move directly from one target to another, or to move by a via-point, at various movement velocities and in a condition with a weight of 0.6 kg attached to the forearm. This set of experimental data was used for comparison with the predictions by various posture-based and trajectory-based models on 3-D movement planning and control. Small but significant effects of starting position and path towards the target were found on the torsion of the arm at the end of the movement. No effects of movement velocity and weight attached to the forearm were found. The experimental results differed significantly from the predictions by any of the models considered. Of the models considered, Donders' law best predicts the experimental data. Our data indicate that future tests of models for motor control (1) should compare the predictions of not just one, but several models to a data set, and (2) should include not only planar, but rather 3-D movements in such a comparison.

915 ヒトの腕運動軌道の解析と制御に関する一考察(GS-2 バイオエンジニアリング(1))

915 ヒトの腕運動軌道の解析と制御に関する一考察(GS-2 バイオエンジニアリング(1))

Analysis of the role of proprioceptive information during arm movements using a model of the human arm.

Using a model for the neuromuscular control of human arm movements, the possible roles of different proprioceptive signals are analyzed. The control model is represented by a neural network and includes both feedback and feedforward control modes. After a learning process, the controller regulates a wide range of arm movements. Evaluation of the roles of different afferent signals shows that sensed muscle forces are important to achieve accurate control of fast movements. For a moderately high look delay (50 ms), velocity feedback is not essential, but for small look delays (0 to 25 ms) an increased performance is attained by feedback of velocity. Position sense is essential to prevent steady-state errors. The arm impedance is affected considerably by the delay in the control loop and by the configuration of the motor control system. The achieved relation between muscle length and force is similar to the invariant characteristics laying at the basis of the equilibrium-point (EP) hypothesis. However, control of fast movements on the basis of EP along is not feasible, but required feedforward control. During training in a velocity-dependent force field, the impedance of the arm increases at first, due to enhanced cocontraction. Subsequently, both impedance and movement errors decrease, indicating a successful representation of the changed inverse dynamics.

Control of Human Arm Movements in Two Dimensions: Influence of Pointer Length on Obstacle Avoidance

Human subjects (N = 13) made arm movements in a horizontal plane by using the shoulder, elbow, and wrist to move a pointer to a target while avoiding simple obstacles. Movements with no pointer and with pointers of three different lengths were tested so that the lever arm of the wrist could be changed and its effective redundancy altered. With increasing pointer length, movement durations decreased, wrist movement used in avoiding obstacles increased, and variability in proximal joint angles increased. Most characteristics of paths and joint movements previously described for movements with the long pointer were found to generalize to movements with shorter pointers or with no pointer—the condition used in several previous comparisons of 2- and 3-joint movements. Both joint angles and path parameters changed in accommodating to the constraints added by obstacles and by increasing pointer length, implying that criteria defined in workspace and in joint space together influence paths in workspace and joint movement, as postulated by bidirectional models. Increased wrist extension and flexion during movement, compared with static pointing, indicate that dynamic factors are also important.

Spatial patterns in the control of human arm movement.

Generalized Procrustes analysis was used to investigate the spatial paths of pointing movements. In Experiment 1, 3 participants produced similar spatial paths of the hand when repeating a pointing movement many times, despite variability in the position and orientation of the movements. The average spatial path indicates a fundamental spatial pattern of the motor system, or motor primitive. This pattern varied across the workspace. Anterioposterior movements were straight, but repeated movements had variable spatial patterns. Lateral movements were curved away from the body but had regular spatial patterns. Experiment 2 extended these results to movements of different amplitudes in 7 participants. The motor primitive seems to be abandoned at the end of the movement in favor of final adjustments to bring the hand to the target position. In Experiment 3, the same participants produced similar motor primitives both with and without vision.

Spatial patterns in the control of human arm movement.

Generalized Procrustes analysis was used to investigate the spatial paths of pointing movements. In Experiment 1, 3 participants produced similar spatial paths of the hand when repeating a pointing movement many times, despite variability in the position and orientation of the movements. The average spatial path indicates a fundamental spatial pattern of the motor system, or motor primitive. This pattern varied across the workspace. Anterioposterior movements were straight, but repeated movements had variable spatial patterns. Lateral movements were curved away from the body but had regular spatial patterns. Experiment 2 extended these results to movements of different amplitudes in 7 participants. The motor primitive seems to be abandoned at the end of the movement in favor of final adjustments to bring the hand to the target position. In Experiment 3, the same participants produced similar motor primitives both with and without vision.

Control of human arm movements in two dimensions: Use of the wrist in short pointing movements

In order to examine how humans utilize redundant degrees of freedom in the arm, movements of the shoulder, elbow and wrist were recorded as subjects made short pointing movements in a horizontal plane. The results show that the wrist is used considerably less than the elbow, even when geometrical relationships would allow either joint to perform the movement. The wrist is used relatively more in short movements (5 to 10 cm), particularly those at right angles to the line of the hand and lower arm, and in fast movements. These changes are not predicted by cost functions which describe static postures. Repetition of movements does not greatly change the amount of wrist movement, but when use of the wrist is explicitly requested, large wrist movements can be incorporated into fast movements with no penalties in duration or peak velocity. For directions where wrist movement is larger and shoulder movement is small, peak velocity is higher and duration is shorter, indicating that subjects do not fully compensate for the anisotropy in the effective inertia of the arm to keep durations and peak velocities constant but instead take advantage of the low inertia at the wrist.

Control of human arm movements in two dimensions: paths and joint control in avoiding simple linear obstacles.

In order to examine path planning and the control of redundant degrees of freedom in the human arm, the movements of the shoulder, elbow and wrist were recorded as subjects moved a pointer to a target and avoided a simple obstacle. With respect to joint control, the results show that the extra degree of freedom provided by the wrist is incorporated into target movements in a systematic manner for both large and small obstacles; it is not used only when there is no geometrical alternative. For the wrist, two strategies are apparent, depending upon the length of the obstacle. Wrist extension predominates for shorter obstacles, while flexion or extension and flexion predominate for longer obstacles. These wrist movements shorten the effective length of the distal segments (lower arm plus hand and pointer) and thus reduce the excursion required at the proximal joints. In part, they correspond to assuming the most comfortable arm configuration at each point in the new path necessitated by the obstacle and can be described by static cost functions. However, wrist extension is also used to move the hand and pointer away from the obstacle as shoulder and elbow movements carry the wrist itself towards the obstacle. Wrist flexion is also used to move the pointer tip rapidly past the obstacle. These components, which cannot be explained by static cost functions alone, confirm for the human arm the hypothesized use of redundant degrees of freedom in obstacle avoidance. With respect to path planning, the results show that the minimum distance between pointer and obstacle remains fairly constant over a large range of obstacle lengths; this relative invariance is interpreted to support the hypothesis that workspace coordinates are important for movement planning. However, minimum distance and several other path parameters do depend significantly on the orientation and location of the movement in the workspace. This inhomogeneity implies that movement planning does not occur exclusively in workspace coordinates; it suggests an influence of joint space criteria. In frontal movements, for example, the systematic decline in the minimum distance with increasing obstacle length is interpreted as a compromise reducing the amount of extra joint movement and the discomfort of arm configurations.