Grip force regulates hand impedance to optimize object stability in high impact loads

A haptic illusion created by gravity

Human dexterity requires very fine and efficient control of fingertip forces, which relies on the integration of cutaneous and proprioceptive feedback. Here, we examined the influence of gravity on isometric force control. We trained participants to reproduce isometric vertical forces on a dynamometer held between the thumb and the index finger in normal gravity and tested them during parabolic flight creating phases of microgravity and hypergravity, thereby strongly influencing the motor commands and the proprioceptive feedback. We found that gravity creates the illusion that upward forces are larger than downward forces of the same magnitude. The illusion increased under hypergravity and was abolished under microgravity. Gravity also affected the control of the grip force employed to secure the grasp. These findings suggest that gravity biases the haptic estimation of forces, which has implications for the design of haptic devices to be used during flight or space activities.

Object motion influences feedforward motor responses during mechanical stopping of virtual projectiles: a preliminary study

An important window into sensorimotor function is how humans interact and stop moving projectiles, such as stopping a door from closing shut or catching a ball. Previous studies have suggested that humans time the initiation and modulate the amplitude of their muscle activity based on the momentum of the approaching object. However, real-world experiments are constrained by laws of mechanics, which cannot be manipulated experimentally to probe the mechanisms of sensorimotor control and learning. An augmented-reality variant of such tasks allows for experimental manipulation of the relationship between motion and force to obtain novel insights into how the nervous system prepares motor responses to interact with moving stimuli. Existing paradigms for studying interactions with moving projectiles use massless objects and are primarily focused on quantifying gaze and hand kinematics. Here, we developed a novel collision paradigm using a robotic manipulandum where participants mechanically stopped a virtual object moving in the horizontal plane. On each block of trials, we varied the virtual object's momentum by increasing either its velocity or mass. Participants stopped the object by applying a force impulse that matched the object momentum. We observed that hand force increased as a function of object momentum linked to changes in virtual mass or velocity, similar to results from studies involving catching free-falling objects. In addition, increasing object velocity resulted in later onset of hand force relative to the impending time-to-contact. These findings show that the present paradigm can be used to determine how humans process projectile motion for hand motor control.

Fine adaptive precision grip control without maximum pinch strength changes after upper limb neurodynamic mobilization

Before and immediately after passive upper limb neurodynamic mobilizations targeting the median nerve, grip (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF) and load (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF) forces applied by the thumb, index and major fingers (three-jaw chuck pinch) were collected using a manipulandum during three different grip precision tasks: grip-lift-hold-replace (GLHR), vertical oscillations (OSC), and vertical oscillations with up and down collisions (OSC/COLL/u, OSC/COLL/d). Several parameters were collected or computed from \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF. Maximum pinch strength and fingertips pressure sensation threshold were also examined. After the mobilizations, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF max changes from 3.2 ± 0.4 to 3.4 ± 0.4 N (p = 0.014), d\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF from 89.0 ± 66.6 to 102.2 ± 59.6 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N~\text{s}^{-1}$$\end{document}Ns-1 (p = 0.009), and d\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 43.6 ± 17.0 to 56.0 ± 17.9 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N~\text{s}^{-1}$$\end{document}Ns-1 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<$$\end{document}p<0.001) during GLHR. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF SD changes from 0.9 ± 0.3 to 1.0 ± 0.2 N (p = 0.004) during OSC. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF peak changes from 17.4 ± 8.3 to 15.1 ± 7.5 N (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<$$\end{document}p<0.001), \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF from 12.4 ± 6.7 to 11.3 ± 6.8 N (p = 0.033), and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 2.9 ± 0.4 to 3.00 ± 0.4 N (p = 0.018) during OSC/COLL/u. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF peak changes from 13.5 ± 7.4 to 12.3 ± 7.7 N (p = 0.030) and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 14.5 ± 6.0 to 13.6 ± 5.5 N (p = 0.018) during OSC/COLL/d. Sensation thresholds at index and thumb were reduced (p = 0.001, p = 0.008). Precision grip adaptations observed after the mobilizations could be partly explained by changes in cutaneous median-nerve pressure afferents from the thumb and index fingertips.

Grip Force Control During Virtual Interaction With Deformable and Rigid Objects Via a Haptic Gripper

Most studies of grip force control focus on the manipulation of rigid objects. However, in virtual and teleoperation applications, objects are often elastic in the pinch degree-of-freedom, and are manipulated using a handle that presents haptic feedback to the user. When designing controllers for haptic grippers, it is crucial to understand how grip force is controlled when manipulating rigid and deformable objects. Here, we used a virtual teleoperation setup with a haptic gripper interface to investigate grip force control in virtual environments. Ten participants lifted virtual objects and performed vertical, cyclic motions using a haptic gripper. We manipulated the control signal to the virtual interface, the haptic properties of the gripper, and the visual properties of the virtual objects to test their effect on the grip force control. We found that participants modulated their grip force as a function of the anticipated load force in all of the experimental conditions. The control signal and properties of the haptic gripper, but not the visual properties of the objects, affected the baseline and the extent of the grip force modulation. These results can provide design guidelines for haptic grippers that elicit natural grasping in virtual and bilateral teleoperation applications.

A review of the neurobiomechanical processes underlying secure gripping in object manipulation

O'SHEA, H. and S. J. Redmond. A review of the neurobiomechanical processes underlying secure gripping in object manipulation. NEUROSCI BIOBEHAV REV 286-300, 2021. Humans display skilful control over the objects they manipulate, so much so that biomimetic systems have yet to emulate this remarkable behaviour. Two key control processes are assumed to facilitate such dexterity: predictive cognitive-motor processes that guide manipulation procedures by anticipating action outcomes; and reactive sensorimotor processes that provide important error-based information for movement adaptation. Notwithstanding increased interdisciplinary research interest in object manipulation behaviour, the complexity of the perceptual-sensorimotor-cognitive processes involved and the theoretical divide regarding the fundamentality of control mean that the essential mechanisms underlying manipulative action remain undetermined. In this paper, following a detailed discussion of the theoretical and empirical bases for understanding human dexterous movement, we emphasise the role of tactile-related sensory events in secure object handling, and consider the contribution of certain biophysical and biomechanical phenomena. We aim to provide an integrated account of the current state-of-art in skilled human-object interaction that bridges the literature in neuroscience, cognitive psychology, and biophysics. We also propose novel directions for future research exploration in this area.

Independent control of cocontraction and reciprocal activity during goal-directed reaching in muscle space

The movement in a joint is facilitated by a pair of muscles that pull in opposite directions. The difference in the pair’s muscle force or reciprocal activity results in joint torque, while the overlapping muscle force or the cocontraction is related to the joint’s stiffness. Cocontraction knowingly adapts implicitly over a number of movements, but it is unclear whether the central nervous system can actively regulate cocontraction in a goal-directed manner in a short span of time. We developed a muscle interface where a cursor’s horizontal position was determined by the reciprocal activity of the shoulder flexion–extension muscle pair, while the vertical position was controlled by its cocontraction. Participants made goal-directed movements to single and via-point targets in the two-dimensional muscle space, learning to move the cursor along the shortest path. Simulations using an optimal control framework suggest that the reciprocal activity and the cocontraction may be controlled independently by the CNS, albeit at a rate orders of magnitude slower than the muscle’s maximal activation speed.

The gravitational imprint on sensorimotor planning and control

Humans excel at learning complex tasks, and elite performers such as musicians or athletes develop motor skills that defy biomechanical constraints. All actions require the movement of massive bodies. Of particular interest in the process of sensorimotor learning and control is the impact of gravitational forces on the body. Indeed, efficient control and accurate internal representations of the body configuration in space depend on our ability to feel and anticipate the action of gravity. Here we review studies on perception and sensorimotor control in both normal and altered gravity. Behavioral and modeling studies together suggested that the nervous system develops efficient strategies to take advantage of gravitational forces across a wide variety of tasks. However, when the body was exposed to altered gravity, the rate and amount of adaptation exhibited substantial variation from one experiment to another and sometimes led to partial adjustment only. Overall, these results support the hypothesis that the brain uses a multimodal and flexible representation of the effect of gravity on our body and movements. Future work is necessary to better characterize the nature of this internal representation and the extent to which it can adapt to novel contexts.

Stretching the skin immediately enhances perceived stiffness and gradually enhances the predictive control of grip force

When manipulating objects, we use kinesthetic and tactile information to form an internal representation of their mechanical properties for cognitive perception and for preventing their slippage using predictive control of grip force. A major challenge in understanding the dissociable contributions of tactile and kinesthetic information to perception and action is the natural coupling between them. Unlike previous studies that addressed this question either by focusing on impaired sensory processing in patients or using local anesthesia, we used a behavioral study with a programmable mechatronic device that stretches the skin of the fingertips to address this issue in the intact sensorimotor system. We found that artificial skin-stretch increases the predictive grip force modulation in anticipation of the load force. Moreover, the stretch causes an immediate illusion of touching a harder object that does not depend on the gradual development of the predictive modulation of grip force.

Grip force preparation for collisions

Grip force has been studied widely in a variety of interaction and movement tasks, however, not much is known about the timing of the grip force control in preparation for interaction with objects. For example, it is unknown whether and how the temporal preparation for a collision is related to (the prediction of) the impact load. To study this question, we examined the anticipative timing of the grip force in preparation for impact loads. We designed a collision task with different types of load forces in a controlled virtual environment. Participants interacted with a robotic device (KINARM, BKIN Technologies, Kingston) whose handles were equipped with force sensors which the participants held in precision grip. Representations of the hand and objects were visually projected on a virtual reality display and forces were applied onto the participant's hand to simulate a collision with the virtual objects. The collisions were alternating between the two hands to allow transfer and learning between the hands. The results show that there is immediate transfer of object information between the two hands, since the grip force levels are (almost) fully adjusted after one collision with the opposite hand. The results also show that the grip force levels are nicely adjusted based on the mass and stiffness of the object. Surprisingly, the temporal onset of the grip force build up did not depend on the impact load, so that participants avoid slippage by adjusting the other grip force characteristics (e.g., grip force level and rate of change), therefore considering these self-imposed timing constraints. With the use of catch trials, for which no impact occurred, we further analyzed the temporal profile of the grip force. The catch trial data showed that the timing of the grip force peak is also independent of the impact load and its timing, which suggests a time-locked planning of the complete grip force profile.

Adaptivity of End Effector Motor Control Under Different Sensory Conditions: Experiments With Humans in Virtual Reality and Robotic Applications

The investigation of human perception and movement kinematics during manipulation tasks provides insights that can be applied in the design of robotic systems in order to perform human-like manipulations in different contexts and with different performance requirements. In this paper we investigate control in a motor task, in which a tool is moved vertically until it touches a support surface. We evaluate how acoustic and haptic sensory information generated at the moment of contact modulates the kinematic parameters of the movement. Experimental results show differences in the achieved motor control precision and adaptation rate across conditions. We describe how the experimental results can be used in robotics applications in the fields of unsupervised learning, supervised learning from human demonstrators and teleoperations.

Switching in Feedforward Control of Grip Force During Tool-Mediated Interaction With Elastic Force Fields

Switched systems are common in artificial control systems. Here, we suggest that the brain adopts a switched feedforward control of grip forces during manipulation of objects. We measured how participants modulated grip force when interacting with soft and rigid virtual objects when stiffness varied continuously between trials. We identified a sudden phase transition between two forms of feedforward control that differed in the timing of the synchronization between the anticipated load force and the applied grip force. The switch occurred several trials after a threshold stiffness level in the range 100–200 N/m. These results suggest that in the control of grip force, the brain acts as a switching control system. This opens new research questions as to the nature of the discrete state variables that drive the switching.

Precision Grip Control while Walking Down a Stair Step

The aim of this study was to determine whether the internal model regulating grip force (GF)/load force (LF) coordination during a brisk load increase is preserved when the lower extremities produce a perturbation during a single step-down task. We observed the coordination of the vertical ground reaction force (vGRF), GF and LF while holding a handheld object during a single step-down task. The 3 forces (vGRF, GF and LF) decreased during the start of the task. While the subject was descending, LF and GF became dissociated from vGRF and increased in value, probably to anticipate the first foot contact. Coordination of LF and GF was maintained until the maximal vGRF (knee extension). LF peaked in the same time window as vGRF, whereas GF peaked about 70 ms later. This desynchronization, which was previously observed in direct load increase on a handheld object, was interpreted to be a predictive action to ensure the smooth management of the brisk increase in load induced by the lower extremities. Incidentally, in this group, kinematic and dynamic differences were observed between men and women, which may highlight a gender-specific strategy to perform the step-down task. In conclusion, these results suggest that the internal model of precision grip is able to integrate a brisk load change, whatever its origin, and regulate the forces to provide an ideal GF to dampen a brisk load increase and secure the object.

Simple and Reliable Method to Estimate the Fingertip Static Coefficient of Friction in Precision Grip

The static coefficient of friction (µ_static) plays an important role in dexterous object manipulation. Minimal normal force (i.e., grip force) needed to avoid dropping an object is determined by the tangential force at the fingertip-object contact and the frictional properties of the skin-object contact. Although frequently assumed to be constant for all levels of normal force (NF, the force normal to the contact), µ _static actually varies nonlinearly with NF and increases at low NF levels. No method is currently available to measure the relationship between µ_static and NF easily. Therefore, we propose a new method allowing the simple and reliable measurement of the fingertip µ_static at different NF levels, as well as an algorithm for determining µ_static from measured forces and torques. Our method is based on active, back-and-forth movements of a subject's finger on the surface of a fixed six-axis force and torque sensor. µ_static is computed as the ratio of the tangential to the normal force at slip onset. A negative power law captures the relationship between µ_static and NF. Our method allows the continuous estimation of µ_static as a function of NF during dexterous manipulation, based on the relationship between µ_static and NF measured before manipulation.

Motor learning of cue-dependent pull-force changes during an isometric precision grip task

The "raspberry task" represents a precision grip task that requires continuous adjustment of grip and pull forces. During this task subjects grip a specialized grip rod and have to increase the pull force linearly while the rod is locked. The aim of this study was to determine whether an associated, initially neutral cue is able to evoke pull-force changes in the raspberry task. A standard delay paradigm was used to study cued pull-force changes during an ongoing movement resulting in unloading. Pull force and EMG activity of hand and arm muscles were recorded from 13 healthy, young subjects. The cue was associated with a complex change in motor behavior. In this task, cued force changes take place more rapidly than in protective reflex systems (in median after the second presentation of the cueing stimulus). A cued force change was detectable in two-thirds of paired trials. Although the force change is produced by a decrease of the EMG activity in several grip- and pull-force-producing muscles, the most significant effect in the majority of the subjects was an increase of the activity of the flexor carpi ulnaris muscle which antagonises corresponding pull-force-producing muscles. Cued force changes require adequately and precisely controlled activation of the muscle groups involved in the movement.

Analysis of the effects of surface stiffness on the contact interaction between a finger and a cylindrical handle using a three-dimensional hybrid model

Contact interactions between the hand and handle, such as the contact surface softness and contact surface curvature, will affect both physical effort and musculoskeletal fatigue, thereby the comfort and safety of power tool operations. Previous models of hand gripping can be categorized into two groups: multi-body dynamic models and finite element (FE) models. The goal of the current study is to develop a hybrid FE hand gripping model, which combines the features of conventional FE models and multi-body dynamic models. The proposed model is applied to simulate hand-gripping on a cylindrical handle with covering materials of different softness levels. The model included three finger segments (distal, middle, and proximal phalanxes), three finger joints (the distal interphalangeal (DIP), proximal interphalangeal (PIP), and metacarpophalangeal (MCP) joint), and major anatomical substructures. The model was driven by joint moments, which are the net effects of all passive and active muscular forces acting about the joints. The finger model was first calibrated by using experimental data of human subject tests, and then applied to investigate the effects of surface softness on contact interactions between a finger and a cylindrical handle. Our results show that the maximal compressive stress and strain in the soft tissues of the fingers can be effectively reduced by reducing the stiffness of the covering material.

Grip force control during virtual object interaction: effect of force feedback,accuracy demands, and training

When grasping and manipulating objects, people are able to efficiently modulate their grip force according to the experienced load force. Effective grip force control involves providing enough grip force to prevent the object from slipping, while avoiding excessive force to avoid damage and fatigue. During indirect object manipulation via teleoperation systems or in virtual environments, users often receive limited somatosensory feedback about objects with which they interact. This study examines the effects of force feedback, accuracy demands, and training on grip force control during object interaction in a virtual environment. The task required subjects to grasp and move a virtual object while tracking a target. When force feedback was not provided, subjects failed to couple grip and load force, a capability fundamental to direct object interaction. Subjects also exerted larger grip force without force feedback and when accuracy demands of the tracking task were high. In addition, the presence or absence of force feedback during training affected subsequent performance, even when the feedback condition was switched. Subjects' grip force control remained reminiscent of their employed grip during the initial training. These results motivate the use of force feedback during telemanipulation and highlight the effect of force feedback during training.

Task dependency of grip stiffness--a study of human grip force and grip stiffness dependency during two different tasks with same grip forces

It is widely known that the pinch-grip forces of the human hand are linearly related to the weight of the grasped object. Less is known about the relationship between grip force and grip stiffness. We set out to determine variations to these dependencies in different tasks with and without visual feedback. In two different settings, subjects were asked to (a) grasp and hold a stiffness-measuring manipulandum with a predefined grip force, differing from experiment to experiment, or (b) grasp and hold this manipulandum of which we varied the weight between trials in a more natural task. Both situations led to grip forces in comparable ranges. As the measured grip stiffness is the result of muscle and tendon properties, and since muscle/tendon stiffness increases more-or-less linearly as a function of muscle force, we found, as might be predicted, a linear relationship between grip force and grip stiffness. However, the measured stiffness ranges and the increase of stiffness with grip force varied significantly between the two tasks. Furthermore, we found a strong correlation between regression slope and mean stiffness for the force task which we ascribe to a force stiffness curve going through the origin. Based on a biomechanical model, we attributed the difference between both tasks to changes in wrist configuration, rather than to changes in cocontraction. In a new set of experiments where we prevent the wrist from moving by fixing it and resting it on a pedestal, we found subjects exhibiting similar stiffness/force characteristics in both tasks.

Unintended hand movements after abrupt cessation of variable and constant opposing forces

Humans are highly efficient in moving in a world of variable resistive forces which result, e.g., from different masses of objects or different directions of movements relative to gravity. However, the underlying mechanisms are challenged when an opposing force is suddenly removed. The resulting involuntary movements are known as accident risks in everyday life. We studied their characteristics upon abrupt cessations of opposing forces of 1, 2, and 4N which were presented in a series of variable or constant forces. The characteristics of the involuntary hand movements are largely determined by the mechanical impedance of the limb. The involuntary movements are oscillatory in nature, and their amplitude increases with stronger opposing force. Limb impedance is modulated both in a reactive and in an anticipatory manner. The reactive modulation occurs during each involuntary movement as a consequence of the neural responses elicited by the rapid limb acceleration consequent upon the cessation of the opposing force. Anticipatory modulation of limb impedance may serve to produce similar involuntary movements in spite of different opposing forces. The modulation is thus stronger with variable forces, where differences between resulting involuntary movements can be experienced more easily, than with constant forces.

Active collisions in altered gravity reveal eye-hand coordination strategies

Most object manipulation tasks involve a series of actions demarcated by mechanical contact events, and gaze is usually directed to the locations of these events as the task unfolds. Typically, gaze foveates the target 200 ms in advance of the contact. This strategy improves manual accuracy through visual feedback and the use of gaze-related signals to guide the hand/object. Many studies have investigated eye-hand coordination in experimental and natural tasks; most of them highlighted a strong link between eye movements and hand or object kinematics. In this experiment, we analyzed gaze strategies in a collision task but in a very challenging dynamical context. Participants performed collisions while they were exposed to alternating episodes of microgravity, hypergravity and normal gravity. First, by isolating the effects of inertia in microgravity, we found that peak hand acceleration marked the transition between two modes of grip force control. Participants exerted grip forces that paralleled load force profiles, and then increased grip up to a maximum shifted after the collision. Second, we found that the oculomotor strategy adapted visual feedback of the controlled object around the collision, as demonstrated by longer durations of fixation after collision in new gravitational environments. Finally, despite large variability of arm dynamics in altered gravity, we found that saccades were remarkably time-locked to the peak hand acceleration in all conditions. In conclusion, altered gravity allowed light to be shed on predictive mechanisms used by the central nervous system to coordinate gaze, hand and grip motor actions during a mixed task that involved transport of an object and high impact loads.

Stability control of grasping objects with different locations of center of mass and rotational inertia

The objective of this study was to observe how the digits of the hand adjust to varying location of the center of mass (CoM) above or below the grasp and rotational inertia (RI) of a handheld object. Such manipulations do not immediately affect the equilibrium equations while stability control is affected. Participants were instructed to hold a handle, instrumented with 5 force-torque transducers and a 3-D rotational tilt sensor, while either the location of the CoM or the RI values were adjusted. On the whole, people use 2 mechanisms to adjust to the changed stability requirements; they increase the grip force and redistribute the total moment between the normal and tangential forces offsetting internal torques. The increase in grip force, an internal force, and offsetting internal torques allows for increases in joint and hand rotational apparent stiffness while not creating external forces-torques that would unbalance the equations of equilibrium.