Factors influencing the force control during precision grip

Summary A small object was gripped between the tips of the index finger and thumb and held stationary in space. Its weight and surface structure could be changed between consecutive lifting trials, without changing its visual appearance. The grip force and the vertical lifting force acting on the object, as well as the vertical position of the object were continuously recorded. Likewise, the minimal grip force necessary to prevent slipping, was measured. The difference between this minimal force and the employed grip force, was defined as the safety margin to prevent slipping.It was found that the applied grip force was critically balanced to optimize the motor behaviour so that slipping between the skin and the gripped object did not occur and the grip force did not reach exeedingly high values. To achieve this motor control, the nervous system relied on a mechanism that measured the frictional condition between the surface structure of the object and the fingers. Experiments with local anaesthesia indicated that this mechanism used information from receptors in the fingers, most likely skin mechanoreceptors. In addition to friction, the control of the grip force was heavily influenced by the weight of the object and by a safety margin factor related to the individual subject. The frictional conditions during the previous trial could also, to some extent, influence the grip force.     

Effect of human grip strategy on force control in precision tasks

Alternate grip strategies are often used for object manipulation in individuals with sensorimotor deficits. To determine the effect of grip type on force control, ten healthy adult subjects were asked to grip and lift a small manipulandum using a traditional precision grip (lateral pinch), a pinch grip with the fingers oriented downwards (downward pinch) and a key grip between the thumb and the side of the index finger. The sequence of grip type and hand used was varied randomly after every ten lifts. Each of the three grips resulted in different levels of force, with the key grip strategy resulting in the greatest grip force and the downward pinch grip using the least amount of grip force to lift the device. Cross-correlation analysis revealed that the ability to scale accurately the rate of grip force and load force changes was lowest in the downward pinch grip. This was also associated with a more variable time-shift between the two forces, indicating that the precise anticipatory control when lifting an object is diminished in this grip strategy. There was a difference between hands across all grips, with the left non-dominant hand using greater grip force during the lift but not the hold phase. Further, in contrast with the right hand, the left hand did not reduce grip force during the lift or the hold phase over the ten lifts, suggesting that the non-dominant hand did not quickly learn to optimise grip force. These findings suggest that the alternate grip strategies used by patients with limited fine motor control, such as following stroke, may partly explain the disruption of force control during object manipulation.     

The effects of digital anesthesia on force control using a precision grip

A total of 20 right-handed subjects were asked to perform a grasp-lift-and-hold task using a precision grip. The grasped object was a one-degree-of-freedom manipuladum consisting of a vertically mounted linear motor capable of generating resistive forces to simulate a range of object weights. In the initial study, seven subjects (6 women, 1 man; ages 24-56 yr) were first asked to lift and hold the object stationary for 4 s. The object presented a metal tab with two different surface textures and offered one of four resistive forces (0.5, 1.0, 1.5, and 2.0 N). The lifts were performed both with and without visual feedback. Next, the subjects were asked to perform the same grasping sequence again after ring block anesthesia of the thumb and index finger with mepivacaine. The objective was to determine the degree to which an internal model obtained through prior familiarity might compensate for the loss of cutaneous sensation. In agreement with previous studies, it was found that all subjects applied significantly greater grip force after digital anesthesia, and the coordination between grip and load forces was disrupted. It appears from these data, that the internal model alone is insufficient to completely compensate for the loss of cutaneous sensation. Moreover, the results suggest that the internal model must have either continuous tonic excitation from cutaneous receptors or at least frequent intermittent reiteration to function optimally. A subsequent study performed with 10 additional subjects (9 women, 1 man; ages 24-49 yr) indicated that with unimpaired cutaneous feedback, the grasping and lifting forces were applied together with negligible forces and torques in other directions. In contrast, after digital anesthesia, significant additional linear and torsional forces appeared, particularly in the horizontal and frontal planes. These torques were thought to arise partially from the application of excessive grip force and partially from a misalignment of the two grasping fingers. These torques were further increased by an imbalance in the pressure exerted by the two opposing fingers. Vision of the grasping hand did not significantly correct the finger misalignment after digital anesthesia. Taken together, these results suggest that mechanoreceptors in the fingertips signal the source and direction of pressure applied to the skin. The nervous system uses this information to adjust the fingers and direct the pinch forces optimally for grasping and object manipulation.     

EMG activation patterns during force production in precision grip

Electromyographic (EMG) activity was analyzed for the occurrence of synergistic patterns during the steady hold periods of force in the precision grip. To establish the presence of muscle synergies in the amplitude (spatial) domain, the EMG activation levels of pairs of simultaneously active muscles were linearly correlated. Cross-correlations of EMG activity were computed to quantify muscle synergies in the spatiotemporal domain (synchronization). A muscle pair was defined to be synergistically coupled or synchronously activated when the correlation (amplitude domain) or cross-correlation (time domain) was significant for at least two of the three steady state force levels. Muscle synergies in the amplitude domain were found in one-third of the 213 muscle pairs tested, distributed among 47 of the 82 tested muscle combinations. Coactivation was the predominant synergistic pattern, whereas trade-off comprised not more than 23% of the synergies. Cross-correlation peak size varied between 5 and 39% of the autocorrelation size, with delays in the range of ±8 ms and base width between 12 and 20 ms. Synchronization was found in one-fourth of the 213 muscle pairs tested and among 35 of the 82 muscle combinations, i.e., less frequently than covariation of EMG activity levels. However, the interindividual prevalence was higher for synchronization than for synergies in the amplitude domain, since, for the synergistic muscle combinations, almost twice as many muscle pairs were found to be synchronized than coupled in the amplitude domain. Synergies in the two domains occurred independently in some pairs and concurrently in other cases, and were observed between muscles moving the thumb, the index finger, or both digits. Synchronization was more frequent in pairs of muscles supplied by branches of the same peripheral nerve (46%) than in those innervated by different nerves (18%). Synergies in the amplitude domain were distributed in similar proportions across intrinsic, extrinsic, and combinations of both types of muscles, whereas synchronization mainly occurred in pairs of intrinsic muscles. When the task was repeated with slightly lower target forces, there were fewer synergies in the amplitude domain (in 52 of the 213 pairs, distributed among 35 of 82 muscle combinations) and their distribution changed, indicating a flexible, force-dependent mechanism. In conclusion, no strictly coherent interindividual pattern of synergies in the spatial domain could be established.     

Development of human precision grip I: Basic coordination of force

Summary The coordination of manipulative forces was examined while children and adults repeatedly lifted a small object between the thumb and index finger. Grip force, load force (vertical lifting force), grip force rate and the vertical position of the test object were continuously measured. In adults, the force generation was highly automatized and was nearly invariant between trials. After a preload phase in which the grip was established, the grip and load forces increased in parallel under isometric conditions until the load force overcame the force of gravity and the object started to move. During this loading phase, the force rate profiles were essentially bell shaped and single peaked, suggesting that the force increases were programmed as one coordinated event. Children below the age of two exhibited a prolonged preload phase and a loading phase during which the grip and load forces did not increase in parallel. A major increase in grip force preceded the increase in load force, and at the start of the loading phase, the grip force was usually several Newtons (N). The force rate profiles were multi peaked with step-wise force increases most likely allowing peripheral feedback to play an important role in the control of the forces. After the age of two, the grip force increased less during the preload phase. The loading phase was more regularly characterized by a parallel increase of the grip force and load force and the duration of the various phases decreased. The older children programmed the forces in one force rate pulse indicating the emergence of an anticipatory strategy. Yet, the mature coordination of forces was not fully developed until several years later. It was concluded that the development of the precision grip was based upon the formation of a lift synergy coupling grip and load force generating circuits and that it seems to involve a transition from feedback control to feedforward control.     

Precision in isometric precision grip force is reduced in middle-aged adults

We investigated age related changes in the control of precision grip in 29 healthy adults spanning early adulthood to middle age (21–67 years). Subjects performed a visually guided, isometric precision grip ramp-and-hold force-tracking task. Target force levels were 3, 6, and 9 N. Precision and performance of force regulation was quantified. Larger errors were made during the ramp than during the hold phase. Age correlated positively with the amount of error at the lowest (3 N) force level in both phases. Force onsets were systematically earlier in middle-aged subjects and the average slope of the force during the ramp decreased with increasing age. The results show that precision during low grip force control decreases already during middle age and those subjects may modify their force generation strategies to compensate for early and subtle degenerative changes in the motor system before decline in grip strength is apparent.     

Contrasting properties of monkey somatosensory and motor cortex neurons activated during the control of force in precision grip

1. Single cell activity was investigated in the precentral motor (MI) and postcentral somatosensory (SI) cortex of the monkey to compare the neuronal activity related to the control of isometric force in the precision grip and to assess the participation of SI in motor control. 2. Three monkeys (Macaca fascicularis) were trained in a visual step-tracking paradigm to generate and precisely maintain force on a transducer held between thumb and index finger. Great care was taken to have the monkeys use only their fingers without moving the wrist or proximal joints. In two monkeys electromyographic (EMG) activity was checked in 23 muscles over several sessions. 3. Five similar classes of task-related firing patterns were found in both SI and MI cortical hand and finger representations, but their relative proportions differed. The majority of the SI neurons were phasically or phasic-tonically active (61%), whereas in MI the neurons that decreased their firing rate with force were most frequent (42%). 4. The timing of activity changes related to the onset of force increase from low to higher levels strongly differed in the two neuronal populations. In SI, only 14% of the task-related neurons increased or decreased their firing rate before the onset of force increase, in contrast to 56% in MI. Only 3% of the SI neurons showed changes before the earliest EMG activation. 5. In both SI and MI neurons with tonic and phasic-tonic, increasing or decreasing discharge patterns disclosed a relationship between neuronal activity and static force. Distinction was made between neurons modulating their activity in a monotonic way and those that were active only at one force level and had a kind of recruitment or deactivation threshold. The latter ones were more frequent in MI than in SI, and in the neuron population with decreasing firing patterns. For the neurons with increases in activity, statistically significant linear correlations between firing rate and force were found more frequently in MI than in SI, where the proportion of nonsignificant correlations was relatively high (35% vs. 15% in MI). In SI the indexes of force sensitivity, calculated from the slopes of the regression lines, covered a wider range than in MI; and their distribution was bimodal, with one mean of 30 Hz/N and the other of 155 Hz/N. In contrast, the mean rate-force slope in MI was 69 Hz/N.(ABSTRACT TRUNCATED AT 400 WORDS)     

Somatosensory control of precision grip during unpredictable pulling loads

Summary In the previous paper regarding the somatosensory control of the human precision grip, we concluded that the elicited automatic grip force adjustments are graded by the amplitude of the imposed loads when restraining an active object subjected to unpredictable pulling forces (Johansson et al. 1992a). Using the same subjects and apparatus, the present study examines the capacity to respond to imposed load forces applied at various rates. Grip and load forces (forces normal and tangential to the grip surfaces) and the position of the object in the pulling direction (distal) were recorded. Trapezoidal load force profiles with plateau amplitudes of 2 N were delivered at the following rates of loading and unloading in an unpredictable sequence: 2 N/s, 4 N/s or 8 N/s. In addition, trials with higher load rate (32 N/s) at a low amplitude (0.7 N) were intermingled. The latencies between the start of the loading and the onset of the grip force response increased with decreasing load force rate. They were 80±9ms, 108 ±13ms, 138 ± 27 ms and 174 ± 39 ms for the 32, 8, 4 and 2 N/s rates, respectively. These data suggested that the grip response was elicited after a given minimum latency once a load amplitude threshold was exceeded. The amplitude of the initial rapid increase of grip force (i.e., the catch-up response) was scaled by the rate of the load force, whereas its time course was similar for all load rates. This response was thus elicited as a unit, but its amplitude was graded by afferent information about the load rate arising very early during the loading. The scaling of the catch-up response was purposeful since it facilitated a rapid reconciliation of the ratio between the grip and load force to prevent slips. In that sense it apparently also compensated for the varying delays between the loading phase and the resultant grip force responses. However, modification of the catch-up response may occur during its course when the loading rate is altered prior to the grip force response or very early during the catch-up response itself. Hence, afferent information may be utilized continuously in updating the response although its motor expression may be confined to certain time contingencies. Moreover, this updating may take place after an extremely short latency (45–50 ms). Our findings support the idea that the initiation as well as ongoing regulation of the motor responses is dependent on supraspinal control, but afferent signals directly processed through fast segmental networks may also contribute in the regulation. The grip force responses to the unloading phases, they were also graded by the load force rate and the response latencies increased with decreasing load force rate. However, the latencies were longer and more variable, and no catch-up responses were observed. Rather, the grip force decline was programmed for the inter-trial grip force level.     

Somatosensory control of precision grip during unpredictable pulling loads

In manipulating 'passive' objects, for which the physical properties are stable and therefore predictable, information essential for the adaptation of the motor output to the properties of the current object is principally based on 'anticipatory parameter control' using sensorimotor memories, i.e., an internal representation of the object's properties based on previous manipulative experiences. Somatosensory afferent signals only intervene intermittently according to an 'event driven' control policy. The present study is the first in a series concerning the control of precision grip when manipulating 'active' objects that exert unpredictable forces which cannot be adequately represented in a sensorimotor memory. Consequently, the manipulation may be more reliant on a moment-to-moment sensory control. Subjects who were prevented from seeing the hand used the precision grip to restrain a manipulandum with two parallel grip surfaces attached to a force motor which produced distally directed (pulling) loads tangential to the finger tips. The trapezoidal load profiles consisted of a loading phase (4 N/s), plateau phase and an unloading phase (4 N/s) returning the load force to zero. Three force amplitudes were delivered in an unpredictable sequence; 1 N, 2 N and 4 N. In addition, trials with higher load rate (32 N/s) at a low amplitude (0.7 N), were superimposed on various background loads. The movement of the manipulandum, the load forces and grip forces (normal to the grip surfaces) were recorded at each finger. The grip force automatically changed with the load force during the loading and unloading phases. However, the grip responses were initiated after a brief delay. The response to the loading phase was characterized by an initial fast force increase termed the 'catch-up' response, which apparently compensated for the response delay--the grip force adequately matched the current load demands by the end of the catch-up response. In ramps with longer lasting loading phases (amplitude greater than or equal to 2 N) the catch-up response was followed by a 'tracking' response, during which the grip force increased in parallel with load force and maintained an approximately constant force ratio that prevented frictional slips. The grip force during the hold phase was linearly related to the load force, with an intercept close to the grip force used prior to the loading. Likewise, the grip force responses evoked by the fast loadings superimposed on existing loads followed the same linear relationship.(ABSTRACT TRUNCATED AT 400 WORDS)     

Anticipatory grip force control using a cerebellar model

Grip force modulation has a rich history of research, but the results remain to be integrated as a neurocomputational model and applied in a robotic system. Adaptive grip force control as exhibited by humans would enable robots to handle objects with sufficient yet minimal force, thus minimizing the risk of crushing objects or inadvertently dropping them. We investigated the feasibility of grip force control by means of a biological neural approach to ascertain the possibilities for future application in robotics. As the cerebellum appears crucial for adequate grip force control, we tested a computational model of the olivo-cerebellar system. This model takes into account that the processing of sensory signals introduces a 100 ms delay, and because of this delay, the system needs to learn anticipatory rather than feedback control. For training, we considered three scenarios for feedback information: (1) grip force error estimation, (2) sensory input on deformation of the fingertips, and (3) as a control, noise. The system was trained on a data set consisting of force and acceleration recordings from human test subjects. Our results show that the cerebellar model is capable of learning and performing anticipatory grip force control closely resembling that of human test subjects despite the delay. The system performs best if the delayed feedback signal carries an error estimation, but it can also perform well when sensory data are used instead. Thus, these tests indicate that a cerebellar neural network can indeed serve well in anticipatory grip force control not only in a biological but also in an artificial system.     

The relation between force magnitude, force steadiness, and muscle co-contraction in the thumb during precision grip

The aim of this study was to investigate the problem of agonist-antagonist co-contracti during a precision force task performed at different force levels. Using a precision grip, seven young adults performed a constant force matching task (10, 22.5, 35, 47.5, and 60% maximum) as accurately as possible (10 trials per force level). Muscle co-contraction in the thumb was monitored by the surface EMG activity of the extensor pollicis longus (EPL) and the flexor pollicis brevis (FPB), and the ratio between those EMG activities (EPL/FPB). Results showed that both EMG activities increased as grip force increased, but the EPL/FPB ratio decreased over the range of force investigated. Force steadiness (as expressed by the coefficient of variation, CV) appeared as a U-shape function of the force level (with maximal steadiness at 22.5%). Separate analyses at each force level showed no correlation between CV and EMG indices. In addition, the contrast between trials with high and low CV revealed no significant difference in terms of our EMG indices. We conclude that muscle co-contraction and grip force steadiness depend on grip force magnitude, but grip force steadiness does not depend on muscle co-contraction.     

The intermanual transfer of anticipatory force control in precision grip lifting is not influenced by the perception of weight

Passing objects from one hand to the other occurs frequently in our daily life. What kind of information about the weight of the object is transferred between the holding and lifting hand? To examine this, we asked people to hold (and heft) an object in one hand and then pick it up with the other. The objects were presented in the context of a size–weight illusion: that is, two objects of different sizes but the same weight were used. One group of participants held one of the objects in their left hand and then picked it up with their right. Another group of participants simply picked up the objects from a table. Thus, the former group had on-line information about the weight of the object, whereas the latter did not. Both groups showed a strong and equivalent size–weight illusion throughout the experiment. At the same time, the group that lifted the objects from the hefting hand applied equal grip force to the small and large object right from the start; in contrast, the group lifting the objects from the table, initially applied more grip force to the large than to the small object before eventually applying the same force to both. In two additional groups, a delay period was imposed between the lifting of the first and the second hands. The force parameters employed by these last two groups were virtually identical to those used by the group that lifted the object directly from the other hand. These results suggest that the initial calibration of grip force uses veridical information about the weight of the object provided by the other hand. This veridical information about weight is available on-line and is retained in memory for later access. The perceived weight of the object is basically ignored in forming grasping forces.     

Differential fronto-parietal activation depending on force used in a precision grip task: an fMRI study

Recent functional magnetic resonance imaging (fMRI) studies suggest that the control of fingertip forces between the index finger and the thumb (precision grips) is dependent on bilateral frontal and parietal regions in addition to the primary motor cortex contralateral to the grasping hand. Here we use fMRI to examine the hypothesis that some of the areas of the brain associated with precision grips are more strongly engaged when subjects generate small grip forces than when they employ large grip forces. Subjects grasped a stationary object using a precision grip and employed a small force (3.8 N) that was representative of the forces that are typically used when manipulating small objects with precision grips in everyday situations or a large force (16.6 N) that represents a somewhat excessive force compared with normal everyday usage. Both force conditions involved the generation of time-variant static and dynamic grip forces under isometric conditions guided by auditory and tactile cues. The main finding was that we observed stronger activity in the bilateral cortex lining the inferior part of the precentral sulcus (area 44/ventral premotor cortex), the rostral cingulate motor area, and the right intraparietal cortex when subjects applied a small force in comparison to when they generated a larger force. This observation suggests that secondary sensorimotor related areas in the frontal and parietal lobes play an important role in the control of fine precision grip forces in the range typically used for the manipulation of small objects.     

The relation between force and movement when grasping an object with a precision grip

When reaching out for objects, the digits’ paths curve so that they approach their positions of contact moving more or less perpendicularly to the local surface orientation. This increases the accuracy of positioning the digits and ensures that any forces exerted at contact are nearly perpendicular to the surface, so that friction will prevent the digits from slipping along the surface. When lifting the object a similar force perpendicular to the surface is needed to prevent the object from slipping from one’s fingers. In order to determine whether these two issues are dealt with simultaneously we let subjects pick up a cube from three different starting positions and measured the digits’ movements and forces from before contact until the moment the cube started moving. The impact force was low. After impact, the digits spent about 200 ms in contact with the surface of the cube before the latter started to move. The digits first decelerated, and then they gradually built up the grip- and lift forces to move the cube upwards. We found no direct relationship between the control of the reaching movement towards the object and the force applied at the surface of the object to pick it up. We conclude that the reaching and lifting movements are quite independent.     

Elaborate force coordination of precision grip could be generalized to bimanual grasping techniques

Exceptional coordination of grip (G; the normal force that prevents slippage of the grasped object) and load force (L; the tangential force originating from the object's weight and inertia) has been interpreted as a part of evidence that both the anatomy and neural control of human hands have been predominantly designed for manipulation tasks. In the present study, we tested the hypothesis that the precision grasp (uses only the tips of fingers and the thumb of one hand) provides better indices of G and L coordination in static manipulation tasks than two bimanual grasps (palm-palm and fingers-thumb; both using opposing segments of two hands). However, in addition to a subtle difference in relative timing of G and L between the precision and two bimanual grasps, we only found that the fingers-thumb grasp is characterized with higher G/L ratio and somewhat higher modulation of G than not only the precision, but also the bimanual palm-palm grasp. However, all remaining data including the correlation coefficients between G and L demonstrated no difference among three evaluated grasping techniques. Therefore, we concluded that the elaborate G and L coordination associated with uni-manual grasps could be partly generalized to a variety of manipulation tasks including those based on bimanual grasping techniques. Taking into account the importance of manipulation tasks in both everyday life and clinical evaluation, future studies should extend the present research to both other grasping techniques and dynamic manipulation conditions.     

Nondigital afferent input in reactive control of fingertip forces during precision grip

Sensory inputs from the digits are important in initiating and scaling automatic reactive grip responses that help prevent frictional slips when grasped objects are subjected to destabilizing load forces. In the present study we analyzed the contribution to grip-force control from mechanoreceptors located proximal to the digits when subjects held a small manipulandum between the tips of the thumb and index finger. Loads of various controlled amplitudes and rates were delivered tangential to the grip surfaces at unpredictable times. Grip forces (normal to the grip surfaces) and the position of the manipulandum were recorded. In addition, movements of hand and arm segments were assessed by recording the position of markers placed at critical points. Subjects performed test series during normal digital sensibility and during local anesthesia of the index finger and thumb. To grade the size of movements of tissues proximal to the digits caused by the loadings, three different conditions of arm and hand support were used; (1) in the hand-support condition the subjects used the three ulnar fingers to grasp a vertical dowel support and the forearm was supported in a vacuum cast; (2) in the forearm-support condition only the forearm was supported; finally, (3) in the no-support condition the arm was free. With normal digital sensibility the size of the movements proximal to the digits had small effects on the grip-force control. In contrast, the grip control was markedly influenced by the extent of such movements during digital anesthesia. The poorest control was observed in the hand-support condition, allowing essentially only digital movements. The grip responses were either absent or attenuated, with greatly prolonged onset latencies. In the forearm and no-support conditions, when marked wrist movements took place, both the frequency and the strength of grip-force responses were higher, and the grip response latencies were shorter. However, the performance never approached normal. It is concluded that sensory inputs from the digits are dominant in reactive grip control. However, nondigital sensory input may be used for some grip control during impaired digital sensibility. Furthermore, the quality of the control during impaired sensibility depends on the extent of movements evoked by the load in the distal, unanesthetized parts of the arm. The origin of these useful sensory signals is discussed.     

The effects of muscimol inactivation of small regions of motor and somatosensory cortex on independent finger movements and force control in the precision grip

This study investigated the effects of inactivating small regions of the primary somatosensory (SI) and motor (MI) cortex on the control of finger forces in a precision grip. A monkey was trained to grasp and lift a computer-controlled object between the thumb and index finger and to hold it stationary within a narrow position window for 2 s. The grip force applied perpendicular to the object surface, the lifting or load force applied tangentially in the vertical direction, and the vertical displacement were sampled at 100 Hz. Also, the ability of the monkey to extract small pieces of food from narrow wells of a Klüver board was analyzed from video-tape. Preliminary single-unit recordings and microstimulation studies were used to map the extent of the thumb and index-finger representation within SI and MI. Two local injections of 1 μl each (5 μg/μl) of the GABA_A-agonist muscimol were used to inactivate the thumb and index region of either the pre- or post-central gyrus. The precision grip was differently affected by muscimol injection into either SI or MI. MI injections produced a deficit in the monkey’s ability to perform independent finger movements and a general weakness in the finger muscles. Whole-hand grasping movements were inappropriately performed in an attempt to grasp either the instrumented object or morsels of food. Although the effect seemed strongest on intrinsic hand muscles, a clear deficit in digit extension was also noted. As a result, the monkey was unable to lift and maintain the object within the position window for the required 2 s, and, over time, the grip force decreased progressively until the animal stopped working. Following SI injections, the most obvious effect was a loss of finger coordination. In grasping, the placement of the fingers on the object was often abnormal and the monkey seemed unable to control the application of prehensile and lifting forces. However, the detailed analysis of forces revealed that a substantial increase in the grip force occurred well before any deficit in the coordination of finger movements was noted. This observation suggests that cutaneous feedback to SI is essential for the fine control of grip forces. Received: 05 October 1998 / Accepted: 30 March 1999     

Threshold position control of arm movement with anticipatory increase in grip force

The grip force holding an object between fingers usually increases before or simultaneously with arm movement thus preventing the object from sliding. We experimentally analyzed and simulated this anticipatory behavior based on the following notions. (1) To move the arm to a new position, the nervous system shifts the threshold position at which arm muscles begin to be recruited. Deviated from their activation thresholds, arm muscles generate activity and forces that tend to minimize this deviation by bringing the arm to a new position. (2) To produce a grip force, with or without arm motion, the nervous system changes the threshold configuration of the hand. This process defines a threshold (referent) aperture (R_a) of appropriate fingers. The actual aperture (Q_a) is constrained by the size of the object held between the fingers whereas, in referent position R_a, the fingers virtually penetrate the object. Deviated by the object from their thresholds of activation, hand muscles generate activity and grip forces in proportion to the gap between the Q_a and R_a. Thus, grip force emerges since the object prevents the fingers from reaching the referent position. (3) From previous experiences, the system knows that objects tend to slide off the fingers when arm movements are made and, to prevent sliding, it starts narrowing the referent aperture simultaneously with or somewhat before the onset of changes in the referent arm position. (4) The interaction between the fingers and the object is accomplished via the elastic pads on the tips of fingers. The pads are compressed not only due to the grip force but also due to the tangential inertial force (“load”) acting from the object on the pads along the arm trajectory. Compressed by the load force, the pads move back and forth in the gap between the finger bones and object, thus inevitably changing the normal component of the grip force, in synchrony with and in proportion to the load force. Based on these notions, we simulated experimental elbow movements and grip forces when subjects rapidly changed the elbow angle while holding an object between the index finger and the thumb. It is concluded that the anticipatory increase in the grip force with or without correlation with the tangential load during arm motion can be explained in neurophysiological and biomechanical terms without relying on programming of grip force based on an internal model.     

Aging reduces the ability to change grip force and balance control simultaneously

The purpose of this study was to investigate the change in the fingertip forces and balance control of young adults and older adults. The subjects lifted an object of constant weight (i.e., 1500 g) using their right hand, first in a seated position and then in a standing position. We quantified the ability of the participants to adjust their fingertip forces across trials by comparing the percentage of change in the peak grip force, peak load force and the ratio between peak grip force and peak load force. Moreover, we quantified their ability to stabilize their balance following the lifting of the object in the standing condition. The results showed that in both conditions young adults reduced their peak grip force much more than older adults across trials. In the seated condition, young adults increased slightly their peak load force, across trials, while older adults reduced it. In the standing condition, both groups showed similar change in peak load force across trials. Remarkably, older adults improved their balance stability similarly to young adults in the standing condition. This observation suggests that the ability of the older adults to modulate grip force applied to an object while standing is diminished probably to dedicate more attention to the balance control task rather than fine-tuning the grip force. Reducing balance instability following repetitive lifting is certainly more beneficial as the consequences of a fall could be more dramatic than dropping a cup of coffee.