Age-related changes in finger coordination in static prehension tasks.

We studied age-related changes in the performance of maximal and accurate submaximal force and moment production tasks. Elderly and young subjects pressed on six dimensional force sensors affixed to a handle with a T-shaped attachment. The weight of the whole system was counterbalanced with another load. During tasks that required the production of maximal force or maximal moment by all of the digits, young subjects were stronger than elderly. A greater age-related deficit was seen in the maximal moment production tests. During maximal force production tests, elderly subjects showed larger relative involvement of the index and middle fingers; they moved the point of thumb force application upward (toward the index and middle fingers), whereas the young subjects rolled the thumb downward. During accurate force/moment production trials, elderly persons were less accurate in the production of both total moment and total force. They produced higher antagonistic moments, i.e., moment by fingers that acted against the required direction of the total moment. Both young and elderly subjects showed negative covariation of finger forces across repetitions of a ramp force production task. In accurate moment production tasks, both groups showed negative covariation of two components of the total moment: those produced by the normal forces and those produced by the tangential forces. However, elderly persons showed lower values of the indexes of both finger force covariation and moment covariation. We conclude that age is associated with an impaired ability to produce both high moments and accurate time profiles of moments. This impairment goes beyond the well-documented deficits in finger and hand force production by elderly persons. It involves worse coordination of individual digit forces and of components of the total moment. Some atypical characteristics of finger forces may be viewed as adaptive to the increased variability in the force production with age.     

Anticipatory synergy adjustments in preparation to self-triggered perturbations in elderly individuals

We tested the ability of healthy elderly persons to use anticipatory synergy adjustments (ASAs) prior to a self-triggered perturbation of one of the fingers during a multifinger force production task. An index of a force-stabilizing synergy was computed reflecting covariation of commands to fingers. The subjects produced constant force by pressing with the four fingers of the dominant hand on force sensors against constant upwardly directed forces. The middle finger could be unloaded either by the subject pressing the trigger or unexpectedly by the experimenter. In the former condition, the synergy index showed a drop (interpreted as ASA) prior to the time of unloading. This drop started later and was smaller in magnitude as compared with ASAs reported in an earlier study of younger subjects. At the new steady state, a new sharing pattern of the force was reached. We conclude that aging is associated with a preserved ability to explore the flexibility of the mechanically redundant multifinger system but a decreased ability to use feedforward adjustments to self-triggered perturbations. These changes may contribute to the documented drop in manual dexterity with age.     

Understanding finger coordination through analysis of the structure of force variability

 Most common motor acts involve highly redundant effector systems. Understanding how such systems are controlled by the nervous system is a long-standing scientific challenge. Most proposals for solving this problem are based on the assumption that a particular solution, which optimizes additional constraints, is selected by the nervous system out of the many possible solutions. This study attempts to address this question in the context of coordinating individual finger forces to produce a controlled total force oscillation between 5% and 35% of each subject's maximum force of voluntary contraction, under two different combinations of four fingers. The structure of variability of individual finger forces was evaluated with respect to hypotheses that, at each instance in time, subjects attempt to: (1) stabilize the value of total force and (2) stabilize the total moment created by the fingers about the long axis passing through the forearm and midline of the hand. The results provide evidence that a range of goal-equivalent finger force combinations is generated to stabilize the values of total force and the total moment. The control of total force was specified explicitly by the task. However, it was stabilized only near the time of peak force. In contrast, the total moment was stabilized throughout most of the force cycle. The results lead to the suggestion that successful task performance is achieved, not by selecting a single optimal solution, but by discovering an appropriate control law that selectively stabilizes certain combinations of degrees of freedom relevant to the task while releasing from control other combinations. Received: 2 February 2001 / Accepted in revised form: 21 June 2001     

A central back-coupling hypothesis on the organization of motor synergies: a physical metaphor and a neural model

We offer a hypothesis on the organization of multi-effector motor synergies and illustrate it with the task of force production with a set of fingers. A physical metaphor, a leaking bucket, is analyzed to demonstrate that an inanimate structure can show apparent error compensation among its elements. A neural model is developed using tunable back-coupling loops as means of assuring error compensation in a task-specific way. The model demonstrates non-trivial features of multi-finger interaction such as delayed emergence of force stabilizing synergies and simultaneous stabilization of the total force and total moment produced by the fingers. The hypothesis suggests that neurophysiological structures involving short-latency feedback may play a central role in the formation of motor synergies.     

Coordinated force production in multi-finger tasks: finger interaction and neural network modeling

During maximal voluntary contraction (MVC) with several fingers, the following three phenomena are observed: (1) the total force produced by all the involved fingers is shared among the fingers in a specific manner (sharing); (2) the force produced by a given finger in a multi-finger task is smaller than the force generated by this finger in a single-finger task (force deficit); (3) the fingers that are not required to produce any force by instruction are involuntary activated (enslaving). We studied involuntary force production by individual fingers (enslaving effects, EE) during tasks when (an)other finger(s) of the hand generated maximal voluntary pressing force in isometric conditions. The subjects (n = 10) were instructed to press as hard as possible on the force sensors with one, two, three and four fingers acting in parallel in all possible combinations. The EE were (A) large, the slave fingers always producing a force ranging from 10.9% to 54.7% of the maximal force produced by the finger in the single-finger task; (B) nearly symmetrical; (C) larger for the neighboring fingers; and (D) non-additive. In most cases, the EE from two or three fingers were smaller than the EE from at least one finger (this phenomenon was coined occlusion). The occlusion cannot be explained only by anatomical musculo-tendinous connections. Therefore, neural factors contribute substantially to the EE. A neural network model that accounts for all the three effects has been developed. The model consists of three layers: the input layer that models a central neural drive; the hidden layer modeling transformation of the central drive into an input signal to the muscles serving several fingers simultaneously (multi-digit muscles); and the output layer representing finger force output. The output of the hidden layer is set inversely proportional to the number of fingers involved. In addition, direct connections between the input and output layers represent signals to the hand muscles serving individual fingers (uni-digit muscles). The network was validated using three different training sets. Single digit muscles contributed from 25% to 50% of the total finger force. The master matrix and the enslaving matrix were computed; they characterize the ability of a given finger to enslave other fingers and its ability to be enslaved. Overall, the neural network modeling suggests that no direct correspondence exists between neural command to an individual finger and finger force. To produce a desired finger force, a command sent to an intended finger should be scaled in accordance with the commands sent to the other fingers. Received: 17 October 1997 / Accepted in revised form: 12 May 1998     

Effects of age and gender on finger coordination in MVC and submaximal force-matching tasks.

The objective of the study is to examine the effects of age and gender on finger coordination. Twelve young (24 +/- 8 yr; 6 men and 6 women) and 12 elderly (75 +/- 5 yr; 6 men and 6 women) subjects performed single-finger maximal contraction [maximal voluntary contraction (MVC)], four-finger MVC, and four-finger ramp force production tasks by pressing on individual force transducers. A drop in the force of individual fingers during four-finger MVC tasks compared with single-finger MVC tasks (force deficit) was larger, whereas unintended force production by other fingers during single-finger MVC tasks (enslaving) was smaller, in elderly than in young subjects and in women than in men. Force deficit was smaller and enslaving was larger in subjects with higher peak force. During the ramp task, the difference between the variance of total force and the sum of variances of individual forces showed a logarithmic relation to the level of total force, across all subject groups. These findings suggest that indexes of finger coordination scale with force-generating capabilities across gender and age groups.     

The accuracy of perception of a pinch grip force in older adults

The fact that humans can execute accurate movements and generate precise muscle forces is very important for hand function. Target-tracking tasks or target-matching tasks are often executed under combined visual and somatosensory feedback. When visual feedback is removed, subjects have to depend on their perception of force. The objective of the present study was to estimate the effects of aging on the perception of a pinch force produced by the thumb and index finger. In a first set of trials, young (n = 12, age = 25.3 +/- 2.4 years) and elderly (n = 12, age = 71.5 +/- 3.3 years) healthy individuals were asked to reproduce pinch forces which were equivalent to 5%, 20%, and 40% of their maximal pinch force (MPF). Prior to the execution of these trials, the subjects were familiarized with the force levels by matching targets displayed on a screen. They were then asked to reproduce each of these forces without any visual or verbal feedback. The results showed a larger error in the reproduced force for the elderly subjects when compared with the young adults. However, this larger error was mainly due to an initial overshoot in the force to be reproduced, followed by a gradual decrease towards the appropriate force. This transient overshoot was rarely seen in the performance of the younger subjects. In a second set of trials, the same subjects were asked to produce a pinch force of 5%, 20%, and 40% of MPF with 1 hand using visual feedback. They were also instructed to simultaneously apply a comparable pinch force with the other hand (without any feedback). For both young and older adults, the pinch forces produced by the 2 hands were the same. In addition, in both blocks of trials, hand dominance had no effects on the performance for all subjects. These results suggest that normal aging affects the production of force based on sensorimotor memory rather more than it affects comparative outputs from central descending commands.     

Age effects on force produced by intrinsic and extrinsic hand muscles and finger interaction during MVC tasks.

Finger-pressing forces are produced by activation of the intrinsic hand muscles, which are finger specific, and the extrinsic muscles that connect to multiple fingers. We tested a hypothesis of greater weakening of intrinsic hand muscles with age and quantified associated indexes of finger interaction such as enslaving (force production by unintended fingers) and force deficit (loss of finger force in multifinger tasks compared with single-finger tasks). Twelve young (23-35 yr old) and 12 elderly (70-95 yr old) men and women performed single-finger and four-finger maximal pressing tasks, in which force was applied at the proximal phalanges (PP, the intrinsic muscles are major focal force generators) and at the distal phalanges (DP, the extrinsic muscles are focal force generators). The decline in the peak force with age was greater at PP (30%) than at DP (19%). Larger indexes of finger interaction were observed at PP (enslaving = 17.2 +/- 9.4%, force deficit = 36.1 +/- 11.1%) than at DP (enslaving = 14.9 +/- 8.8%, force deficit = 27.7 +/- 10.8%) across ages and genders. We conclude that intrinsic hand muscles show disproportionate weakening with age. The greater indexes of finger interaction in PP tests with greater involvement of intrinsic hand muscles suggest that the finger interactions are predominantly of a central origin across ages and genders.     

Evidence of muscle synergies during human grasping

Motor synergies have been investigated since the 1980s as a simplifying representation of motor control by the nervous system. This way of representing finger positional data is in particular useful to represent the kinematics of the human hand. Whereas, so far, the focus has been on kinematic synergies, that is common patterns in the motion of the hand and fingers, we hereby also investigate their force aspects, evaluated through surface electromyography (sEMG). We especially show that force-related motor synergies exist, i.e. that muscle activation during grasping, as described by the sEMG signal, can be grouped synergistically; that these synergies are largely comparable to one another across human subjects notwithstanding the disturbances and inaccuracies typical of sEMG; and that they are physiologically feasible representations of muscular activity during grasping. Potential applications of this work include force control of mechanical hands, especially when many degrees of freedom must be simultaneously controlled.     

Matrix analyses of interaction among fingers in static force production tasks

The fingers on a hand show interactions in force production tasks. The interfinger connection matrices (IFMs) quantify these interactions (Li et al. 2002; Zatsiorsky et al. 2002b; Danion et al. 2003). The goal of the present study was to explore the differences in the IFMs of individual subjects and, in particular, to establish a procedure that may be used in the future for diagnostic purposes. Subjects (n=20) pressed downward maximally with ten different combinations of the four fingers, index (I), middle (M), ring (R), and little (L): I, M, R, L, IM, MR, RL, IMR, MRL, and IMRL. Voluntary activation of a subset of the four fingers was accompanied by an involuntary force production by fingers that were not intentionally activated (enslaving). Interfinger connection matrices were computed for each subject by the artificial neural network. The similarities/dissimilarities (proximities) between the individual matrices were determined. This procedure was performed twice: (a) for nonnormalized IFMs whose elements represented the amount of force (in newtons) exerted by a finger i in response to a unit command to a finger j; and (b) for normalized IFMs, after dividing the elements of each IFM by the total force produced by the four fingers acting together (the elements of the matrix are in percents). The 20×20 matrix of the proximities was subjected to multidimensional scaling (MDS) to reduce the number of dimensions and identify the major ones. To interpret the meaning of the computed dimensions, they were regressed on a set of finger force parameters described in the text. For the nonnormalized IFMs an interpretable dimension was the strength of the subjects. For the normalized IFMs two dimensions were interpreted: (a) the location of the point of resultant force application along the mediolateral axis that is defined by the pattern of force sharing among the fingers and (b) the total contribution of the enslaved forces into the total finger force. We speculate that the similarity of typical everyday tasks across the population promotes the similarity of the IMFs reflecting optimal hand functioning over these tasks. AcknowledgementsThis study was partly supported by NIH grants NS-35032, AR-048563 and AG-18751. The support from the Whittaker Foundation to Dr. Z.M. Li is also acknowledged.     

Force and torque production in static multifinger prehension: biomechanics and control. II. Control

 The coordination of digits during combined force/torque production tasks was further studied using the data presented in the companion paper [Zatsiorsky et al. Biol Cybern this issue, Part I]. Optimization was performed using as criteria the cubic norms of (a) finger forces, (b) finger forces normalized with respect to the maximal forces measured in single-finger tasks, (c) finger forces normalized with respect to the maximal forces measured in a four-finger task, and (d) finger forces normalized with respect to the maximal moments that can be generated by the fingers. All four criteria failed to predict antagonist finger moments when these moments were not imposed by the task mechanics. Reconstruction of neural commands: The vector of neural commands c was reconstructed from the equation c=W ⁻¹ F, where W is the finger interconnection weight matrix and F is the vector of finger forces. The neural commands ranged from zero (no voluntary force production) to one (maximal voluntary contraction). For fingers producing moments counteracting the external torque (`agonist' fingers), the intensity of the neural commands was well correlated with the relative finger forces normalized to the maximal forces in a four-finger task. When fingers produced moments in the direction of the external torque (`antagonist' fingers), the relative finger forces were always larger than those expected from the intensity of the corresponding neural commands. The individual finger forces were decomposed into forces due to `direct' commands and forces induced by enslaving effects. Optimization of the neural commands resulted in the best correspondence between actual and predicted finger forces. The antagonist moments are, at least in part, due to enslaving effects: strong commands to agonist fingers also activated antagonist fingers. Received: 8 August 2001 / Accepted in revised form: 7 February 2002     

Three-dimensional model to predict muscle forces and their relation to motor variances in reaching arm movements

A three-dimensional (3-D) arm movement model is presented to simulate kinematic properties and muscle forces in reaching arm movements. Healthy subjects performed reaching movements repetitively either with or without a load in the hand. Joint coordinates were measured. Muscle moment arms, 3-D angular acceleration, and moment of inertias of arm segments were calculated to determine 3-D joint torques. Variances of hand position, arm configuration, and muscle activities were calculated. Ratios of movement variances observed in the two conditions (load versus without load) showed no differences for hand position and arm configuration variances. Virtual muscle force variances for all muscles except deltoid posterior and EMG variances for four muscles increased significantly by moving with the load. The greatly increased variances in muscle activity did not imply equally high increments in kinematic variances. We conclude that enhanced muscle cooperation through synergies helps to stabilize movement at the kinematic level when a load is added.     

A comparison of prehension force control in young and elderly individuals

Age-related changes were investigated in the control of precision grip force during the lifting and holding of objects with slippery (silk) and nonslippery (sandpaper) surface textures. Two groups of active elderly adults comprising individuals aged 69–79 years (n = 10), and 80–93 years (n = 10) together with a group of young adults aged 18–32 years (n = 10) participated in the study. Each subject lifted a free weight (3N) during which time gripping and lifting forces were monitored. The elderly subjects, especially the individuals in the 81–93 year group, had a larger number of fluctuations in the grip force rate curve and longer force application time than the younger subjects during lifting. The effect of prior experience with one surface on the following different surface was more pronounced in the younger subjects than the elderly subjects. These results suggest a decline in programmed force production capacity with increased age. The fingers of the elderly subjects were more slippery and they exhibited a greater safety margin of the grip force while holding the object than the younger adults. The overall results demonstrated that precision grip force control capacity declines with advancing age. It is suggested that this decline is due mainly to age-related changes in skin properties, and cutaneous sensibility functions, and in part to central nervous system function.     

Force and torque production in static multifinger prehension: biomechanics and control. I. Biomechanics

 We studied the coordinated action of fingers during static tasks involving exertion of force and torque on a handheld object. Subjects were asked to keep a handle with an attachment that allowed for independent change of the suspended load (0.5–2.0 kg) and external torque (0.375–1.5 N m) in a vertical position while applying minimal effort. Normal and shear forces were measured from the thumb; normal forces only were measured from the four fingers. Experimental results: (1) the thumb shear force increased during supination efforts and decreased during pronation efforts; (2) the total moment of the normal finger forces only counterbalanced approximately 50% of the external torque, hence shear forces accounted for approximately one-half of the total torque exerted on the object; (3) the total normal force increased with external torque, and the total force magnitude did not depend on the torque direction; (4) the forces of the `peripheral' (index and little) fingers depended mainly on the torque while the forces exerted by the `central' (middle and ring) fingers depended both on the load and torque; (5) there was a monotonic relationship between the mechanical advantage of a finger (i.e., its moment arm during torque production) and the force produced by that finger; and (6) antagonist finger moments acting opposite to the intended direction of the total moment were always observed – at low torques the antagonist moments were as high as 40–60% of the agonist moments. Modeling: A three-zone model of coordinated finger action is suggested. In the first zone of load/torque combinations, activation of antagonist fingers (i.e., fingers that generate antagonist moments) is necessary to prevent slipping. In the second zone, the activity of agonist fingers is sufficient for preventing slips. In the third zone, the performer has freedom to choose between either activating the antagonist fingers or redistributing activities amongst the agonist fingers. The findings of this study provide the foundation for neural network and optimization modeling described in the companion paper [Zatsiorsky et al. (2002) Biol Cybern DOI 10.1007/s00422-002-0320-7]. Received: 8 August 2001 / Accepted in revised form: 7 February 2002     

Prehension synergy: use of mechanical advantage during multifinger torque production on mechanically fixed and free objects

The aim of this study was to test the mechanical advantage (MA) hypothesis in multifinger torque production tasks in humans: fingers with longer moment arms produce greater force magnitudes during torque production tasks. There were eight experimental conditions: two prehension types determined by different mechanical constraints (i.e., fixed- and free-object prehension) with two torque directions (supination and pronation) and two torque magnitudes (0.24 and 0.48 N·m). The subjects were asked to produce prescribed torques during the fixed-object prehension or to maintain constant position of the free hand-held object against external torques. The index of MA was calculated for agonist and antagonist fingers, which produce torques in the same and opposite directions to the target torques, respectively. Within agonist fingers, the fingers with longer moment arms produced greater grasping forces while within antagonist fingers, the fingers with shorter moment arms produced greater forces. The MA index was greater in the fixed-object condition as compared with the free-object condition. The MA index was greater in the pronation condition than in the supination condition. This study supports the idea that the CNS utilizes the MA of agonist fingers, but not of antagonist fingers, during torque production in both fixed- and free-object conditions.     

The effect of finger spreading on drag of the hand in human swimming

The effect of finger spread on overall drag on a swimmer’s hand is relatively small, but could be relevant for elite swimmers. There are many sensitivities in measuring this effect. A comparison between numerical simulations, experiments and theory is urgently required to observe whether the effect is significant. In this study, the beneficial effect of a small finger spread in swimming is confirmed using three different but complementary methods. For the first time numerical simulations and laboratory experiments are conducted on the exact same 3D model of the hand with attached forearm. The virtual version of the hand with forearm was implemented in a numerical code by means of an immersed boundary method and the 3D printed physical version was studied in a wind tunnel experiment. An enhancement of the drag coefficient of 2% and 5% compared to the case with closed fingers was found for the numerical simulation and experiment, respectively. A 5% and 8% favorable effect on the (dimensionless) force moment at an optimal finger spreading of 10° was found, which indicates that the difference is more outspoken in the force moment. Moreover, an analytical model is proposed, using scaling arguments similar to the Betz actuator disk model, to explain the drag coefficient as a function of finger spacing.     

Indices of nonlinearity in finger force interaction

Experiments with force production by subsets of fingers within the human hand have shown that finger interaction may be significantly nonlinear. In particular, this nonlinearity is reflected in the phenomenon of force deficit, a drop of the peak force of a finger when several fingers act simultaneously. We describe nonlinear effects in force relations within finger pairs, triplets, etc. Finger forces are represented as the sums of components resulting from force interactions within all subsets of the explicitly involved (master) fingers. The values of these components computed at extreme values of control signals, zero and unity, are taken as indices of such elementary force interactions. Indices of the first order reflect purposeful force production by a single master finger and its effects on forces produced by other fingers (enslaving). Indices of the second order reflect additional influences from pairs of simultaneously recruited master fingers, etc. Force interaction indices were computed based on finger forces measured in earlier experiments. Signs of indices alternated with their order, being positive for the indices of the first order (enslaving), negative for the indices of the second order (force deficit), positive for the indices of the third order, and mostly negative for the indices of the fourth order. Indices of the third and fourth orders reflect phenomena of force interaction not reported earlier. The study emphasizes the importance of nonlinear interactions among finger forces and introduces a set of independent indices that can be used to quantify such interactions in different subpopulations and their possible changes with practice and/or rehabilitation of the hand function.     

On the analysis of hand synergies during grasping in weightlessness

The aim of this paper was to analyse how the strategies implemented by the Central Nervous System to control the hand during grasping are modified under microgravity conditions. Two right-handed subjects carried out simple grasping tasks during parabolic flights. The trajectories of the fingers of the hand were recorded using a sensorised glove and processed in order to extract a variable (here indicated as K) which can indicated the degree of synergies existing among the fingers. The results showed that K was quite small during the trial at 1g while becoming significantly greater than 1 during the first parabolas. Then, the value k decreased to the values at 1 g after some parabolas. These results suggested a possible adaptation process of the manipulation abilities during the permanence at 0g conditions. Future extensive trials will be performed in order to confirm these preliminary results.     

Tactile feedback plays a critical role in maximum finger force production

This study investigates the role of cutaneous feedback on maximum voluntary force (MVF), finger force deficit (FD) and finger independence (FI). FD was calculated as the difference between the sum of maximal individual finger forces during single-finger pressing tasks and the maximal force produced by those fingers during an all-finger pressing task. FI was calculated as the average non-task finger forces normalized by the task-finger forces and subtracted from 100 percent. Twenty young healthy right-handed males participated in the study. Cutaneous feedback was removed by administering ring block digital anesthesia on the 2nd, 3rd, 4th and 5th digits of the right hands. Subjects were asked to press force sensors with maximal effort using individual digits as well as all four digits together, with and without cutaneous feedback. Results from the study showed a 25% decrease in MVF for the individual fingers as well as all the four fingers pressing together after the removal of cutaneous feedback. Additionally, more than 100% increase in FD after the removal of cutaneous feedback was observed in the middle and ring fingers. No changes in FI values were observed between the two conditions. Results of this study suggest that the central nervous system utilizes cutaneous feedback and the feedback mechanism plays a critical role in maximal voluntary force production by the hand digits.