Impact of the surface slipperiness of grasped objects on their subsequent acceleration

Evidence for an internal model of friction when controlling kinetic energy at impact to slide an object along a surface toward a target

Although the role of an internal model of gravity for the predictive control of the upper limbs is quite well established, evidence is lacking regarding an internal model of friction. In this study, 33 male and female human participants performed a striking movement (with the index finger) to slide a plastic cube-like object to a given target distance. The surface material (aluminum or balsa wood) on which the object slides, the surface slope (-10°, 0, or +10°) and the target distance (25 cm or 50 cm) varied across conditions, with ten successive trials in each condition. Analysis of the object speed at impact and spatial error suggests that: 1) the participants chose to impart a similar speed to the object in the first trial regardless of the surface material to facilitate the estimation of the coefficient of friction; 2) the movement is parameterized across repetitions to reduce spatial error; 3) an internal model of friction can be generalized when the slope changes. Biomechanical analysis showed interindividual variability in the recruitment of the upper limb segments and in the adjustment of finger speed at impact in order to transmit the kinetic energy required to slide the object to the target distance. In short, we provide evidence that the brain builds an internal model of friction that makes it possible to parametrically control a striking movement in order to regulate the amount of kinetic energy required to impart the appropriate initial speed to the object.

Illusion of Wetness by Dynamic Touch

Humans perceive wetness on contact with a dry-cold material; however, the magnitude of wetness that can be perceived using dynamic touch remains unclear. This study assessed how the type of touch, namely hand movement (either statically or dynamically) and pressing force (either low or high pressure), affect the perception of wetness. The participants judged the magnitude of perceived wetness after four types of touch of four stimuli comprising four fabrics of varying water content and surface temperatures. Overall, the perceived wetness was differed between static and dynamic touch independent of pressure and the participants scored the dry-cold stimulus as relatively dry for dynamic touch. Furthermore, cluster analysis revealed individual differences in the recognition of wetness in dynamic touch conditions. These results revealed the variability in the mechanisms used by humans to perceive wetness. Additionally, we discussed the optimal methods to reproduce the wetness perception using this illusion.

Peripheral and central determinants of skin wetness sensing in humans

Evolutionarily, our ability to sense skin wetness and humidity (i.e., hygroreception) could have developed as a way of helping to maintain thermal homeostasis, as much as it is the case for the role of temperature sensation and thermoreception. Humans are not provided with a specific skin hygroreceptor, and recent studies have indicated that skin wetness is likely to be centrally processed as a result of the multisensory integration of peripheral inputs from skin thermoreceptors and mechanoreceptors coding the biophysical interactions between skin and moisture. The existence of a specific hygrosensation strategy for human wetness perception has been proposed and the first neurophysiologic model of skin wetness sensing has been recently developed. However, while these recent findings have shed light on some of the peripheral and central neural mechanisms underlying wetness sensing, our understanding of how the brain processes the thermal and mechanical inputs that give rise to one of our "most worn" skin sensory experiences is still far from being conclusive. Understanding these neural mechanisms is clinically relevant in the context of those neurologic conditions that are accompanied by somatosensory abnormalities. The present chapter will present the current knowledge on the peripheral and central determinants of skin wetness sensing in humans.

The biology of skin wetness perception and its implications in manual function and for reproducing complex somatosensory signals in neuroprosthetics

Our perception of skin wetness is generated readily, yet humans have no known receptor (hygroreceptor) to signal this directly. It is easy to imagine the sensation of water running over our hands or the feel of rain on our skin. The synthetic sensation of wetness is thought to be produced from a combination of specific skin thermal and tactile inputs, registered through thermoreceptors and mechanoreceptors, respectively. The present review explores how thermal and tactile afference from the periphery can generate the percept of wetness centrally. We propose that the main signals include information about skin cooling, signaled primarily by thinly myelinated thermoreceptors, and rapid changes in touch, through fast-conducting, myelinated mechanoreceptors. Potential central sites for integration of these signals, and thus the perception of skin wetness, include the primary and secondary somatosensory cortices and the insula cortex. The interactions underlying these processes can also be modeled to aid in understanding and engineering the mechanisms. Furthermore, we discuss the role that sensing wetness could play in precision grip and the dexterous manipulation of objects. We expand on these lines of inquiry to the application of the knowledge in designing and creating skin sensory feedback in prosthetics. The addition of real-time, complex sensory signals would mark a significant advance in the use and incorporation of prosthetic body parts for amputees in everyday life.NEW & NOTEWORTHY Little is known about the underlying mechanisms that generate the perception of skin wetness. Humans have no specific hygroreceptor, and thus temperature and touch information combine to produce wetness sensations. The present review covers the potential mechanisms leading to the perception of wetness, both peripherally and centrally, along with their implications for manual function. These insights are relevant to inform the design of neuroengineering interfaces, such as sensory prostheses for amputees.

Correlation of fingertip shear force direction with somatosensory cortical activity in monkey

To examine the activity of somatosensory cortex (S1) neurons to self-generated shear forces on the index and thumb, two monkeys were trained to grasp a stationary metal tab with a key grip and exert forces without the fingers slipping in one of four orthogonal directions for 1 s. A majority (∼85%) of slowly adapting and rapidly adapting (RA) S1 neurons had activity modulated with shear force direction. The cells were recorded mainly in areas 1 and 2 of the S1, although some area 3b neurons also responded to shear direction or magnitude. The preferred shear vectors were distributed in every direction, with tuning arcs varying from 50° to 170°. Some RA neurons sensitive to dynamic shear force direction also responded to static shear force but within a narrower range, suggesting that the direction of the shear force may influence the adaptation rate. Other neurons were modulated with shear forces in diametrically opposite directions. The directional sensitivity of S1 cortical neurons is consistent with recordings from cutaneous afferents showing that shear direction, even without slip, is a powerful stimulus to S1 neurons.

The brain adjusts grip forces differently according to gravity and inertia: a parabolic flight experiment

In everyday life, one of the most frequent activities involves accelerating and decelerating an object held in precision grip. In many contexts, humans scale and synchronize their grip force (GF), normal to the finger/object contact, in anticipation of the expected tangential load force (LF), resulting from the combination of the gravitational and the inertial forces. In many contexts, GF and LF are linearly coupled. A few studies have examined how we adjust the parameters–gain and offset–of this linear relationship. However, the question remains open as to how the brain adjusts GF regardless of whether LF is generated by different combinations of weight and inertia. Here, we designed conditions to generate equivalent magnitudes of LF by independently varying mass and movement frequency. In a control experiment, we directly manipulated gravity in parabolic flights, while other factors remained constant. We show with a simple computational approach that, to adjust GF, the brain is sensitive to how LFs are produced at the fingertips. This provides clear evidence that the analysis of the origin of LF is performed centrally, and not only at the periphery.

Muscle activity and acceleration during whole body vibration: effect of frequency and amplitude

BACKGROUND

Whole body vibration may improve muscle and bone strength, power and balance although contradictory findings have been reported. Prolonged exposure may result in adverse effects. We investigated the effects of high (5.5 mm) and low (2.5mm) amplitude whole body vibration at various frequencies (5-30 Hz) on muscle activity and acceleration throughout the body.

METHODS

Surface electromyographic activity was recorded from 6 leg muscles in 12 healthy adults (aged 31.3 (SD 12.4) years). The average rectified acceleration of the toe, ankle, knee, hip and head was recorded from 15 healthy adults (36 (SD 12.1) years) using 3D motion analysis.

FINDINGS

Whole body vibration increased muscle activity 5-50% of maximal voluntary contraction with the greatest increase in the lower leg. Activity was greater with high amplitude at all frequencies, however this was not always significant (P<0.05-0.001). Activation tended to increase linearly with frequency in all muscles except gluteus maximus and biceps femoris. Accelerations throughout the body ranged from approximately 0.2 to 9 g and decreased with distance from the platform. Acceleration at the head was always < 0.33 g. The greatest acceleration of the knee and hip occurred at approximately 15 Hz and thereafter decreased with increasing frequency.

INTERPRETATION

Above the knee at frequencies > 15 Hz acceleration decreased with distance from the platform. This was associated with increased muscle activity, presumably due to postural control and muscle tuning mechanisms. The minimal acceleration at the head reduces the likelihood of adverse reactions. The levels of activation are unlikely to cause hypertrophy in young healthy individuals but may be sufficient in weak and frail people.

Short duration microgravity experiments in physical and life sciences during parabolic flights: the first 30 ESA campaigns

Aircraft parabolic flights provide repetitively up to 20 s of reduced gravity during ballistic flight manoeuvres. Parabolic flights are used to conduct short microgravity investigations in Physical and Life Sciences, to test instrumentation and to train astronauts before a space flight. The European Space Agency (ESA) has organized since 1984 thirty parabolic flight campaigns for microgravity research experiments utilizing six different airplanes. More than 360 experiments were successfully conducted during more than 2800 parabolas, representing a cumulated weightlessness time of 15 h 30 m. This paper presents the short duration microgravity research programme of ESA. The experiments conducted during these campaigns are summarized, and the different airplanes used by ESA are shortly presented. The technical capabilities of the Airbus A300 'Zero-G' are addressed. Some Physical Science, Technology and Life Science experiments performed during the last ESA campaigns with the Airbus A300 are presented to show the interest of this unique microgravity research tool to complement, support and prepare orbital microgravity investigations.

The cutaneous contribution to adaptive precision grip

Only after injury, or perhaps prolonged exposure to cold that is sufficient to numb the fingers, do we suddenly appreciate the complex neural mechanisms that underlie our effortless dexterity in manipulating objects. The nervous system is capable of adapting grip forces to a wide range of object shapes, weights and frictional properties, to provide optimal and secure handling in a variety of potentially perturbing environments. The dynamic interplay between sensory information and motor commands provides the basis for this flexibility, and recent studies supply somewhat unexpected evidence of the essential role played by cutaneous feedback in maintaining and acquiring predictive grip force control. These examples also offer new insights into the adaptive control of other voluntary movements.

Control strategies correcting inaccurately programmed fingertip forces: model predictions derived from human behavior

When picking up a familiar object between the index finger and the thumb, the motor commands are predetermined by the CNS to correspond to the frictional demand of the finger-object contact area. If the friction is less than expected, the object will start to slip out of the hand, giving rise to unexpected sensory information. Here we study the correction strategies of the motor system in response to an unexpected frictional demand. The motor commands to the mononeuron pool are estimated by a novel technique combining behavioral recordings and neuromuscular modelling. We first propose a mathematical model incorporating muscles, hand mechanics, and the action of lifting an object. A simple control system sends motor commands to and receives sensory signals from the model. We identify three factors influencing the efficiency of the correction: the time development of the motor command, the delay between the onset of the grip and load forces (GF-LF-delay), and how fast the lift is performed. A sensitivity analysis describes how these factors affect the ability to prevent or stop slipping and suggests an efficient control strategy that prepares and corrects for an altered frictional condition. We then analyzed fingertip grip and load forces (GF and LF) and position data from 200 lifts made by five healthy subjects. The friction was occasionally reduced, forcing an increase of the GF to prevent the object being dropped. The data were then analyzed by feeding it through the inverted model. This provided an estimate of the motor commands to the motoneuron pool. As suggested by the sensitivity analysis the GF-LF-delay was indeed used by the subjects to prevent slip. In agreement with recordings from neurons in the primary motor cortex of the monkey, a sharp burst in the estimated GF motor command (NGF) efficiently arrested any slip. The estimated motor commands indicate a control system that uses a small set of corrective commands, which together with the GF-LF-delay form efficient correction strategies. The selection of a strategy depends on the amount of tactile information reporting unexpected friction and how long it takes to arrive. We believe that this technique of estimating the motor commands behind the fingertip forces during a precision grip lift can provide a powerful tool for the investigation of the central control of the motor system.

Age-related changes in grip force and dynamics of hand movement

The authors investigated whether older adults (n = 16; mean age = 65 years) increased grip force to compensate for load force fluctuations during up and down movements more than young adults did (n = 16; mean age = 24 years) and whether older and young adults exhibited similar adaptation of grip force to alterations in friction associated with changes in object surface texture. As previously reported, older adults used a higher level of grip force than young adults during static holding. Increased grip force was observed in the older group during movement. The increase was appropriate to the lower coefficient of friction estimated for the older group. In both groups, grip force was greater with a smooth than with a rough surface (the latter having the higher coefficient of friction) during static holding and during movement. Moreover, grip force modulation was equally well synchronized with load force fluctuation during movement in the two groups. The authors concluded that changes in organization of grip force with age are well adapted to change in hand-object interface properties. Elevated grip force in older adults does not necessarily signify a fundamental change in synchronizing grip force modulation with load force fluctuation.

Prediction precedes control in motor learning

Skilled motor behavior relies on the brain learning both to control the body and predict the consequences of this control. Prediction turns motor commands into expected sensory consequences, whereas control turns desired consequences into motor commands. To capture this symmetry, the neural processes underlying prediction and control are termed the forward and inverse internal models, respectively. Here, we investigate how these two fundamental processes are related during motor learning. We used an object manipulation task in which subjects learned to move a hand-held object with novel dynamic properties along a prescribed path. We independently and simultaneously measured subjects' ability to control their actions and to predict their consequences. We found different time courses for predictor and controller learning, with prediction being learned far more rapidly than control. In early stages of manipulating the object, subjects could predict the consequences of their actions, as measured by the grip force they used to grasp the object, but could not generate appropriate actions for control, as measured by their hand trajectory. As predicted by several recent theoretical models of sensorimotor control, our results indicate that people can learn to predict the consequences of their actions before they can learn to control their actions.