Hand function: peripheral and central constraints on performance.

The hand is one of the most fascinating and sophisticated biological motor systems. The complex biomechanical and neural architecture of the hand poses challenging questions for understanding the control strategies that underlie the coordination of finger movements and forces required for a wide variety of behavioral tasks, ranging from multidigit grasping to the individuated movements of single digits. Hence, a number of experimental approaches, from studies of finger movement kinematics to the recording of electromyographic and cortical activities, have been used to extend our knowledge of neural control of the hand. Experimental evidence indicates that the simultaneous motion and force of the fingers are characterized by coordination patterns that reduce the number of independent degrees of freedom to be controlled. Peripheral and central constraints in the neuromuscular apparatus have been identified that may in part underlie these coordination patterns, simplifying the control of multi-digit grasping while placing certain limitations on individuation of finger movements. We review this evidence, with a particular emphasis on how these constraints extend through the neuromuscular system from the behavioral aspects of finger movements and forces to the control of the hand from the motor cortex.     

Bio-inspired grasp control in a robotic hand with massive sensorial input

The capability of grasping and lifting an object in a suitable, stable and controlled way is an outstanding feature for a robot, and thus far, one of the major problems to be solved in robotics. No robotic tools able to perform an advanced control of the grasp as, for instance, the human hand does, have been demonstrated to date. Due to its capital importance in science and in many applications, namely from biomedics to manufacturing, the issue has been matter of deep scientific investigations in both the field of neurophysiology and robotics. While the former is contributing with a profound understanding of the dynamics of real-time control of the slippage and grasp force in the human hand, the latter tries more and more to reproduce, or take inspiration by, the nature’s approach, by means of hardware and software technology. On this regard, one of the major constraints robotics has to overcome is the real-time processing of a large amounts of data generated by the tactile sensors while grasping, which poses serious problems to the available computational power. In this paper a bio-inspired approach to tactile data processing has been followed in order to design and test a hardware–software robotic architecture that works on the parallel processing of a large amount of tactile sensing signals. The working principle of the architecture bases on the cellular nonlinear/neural network (CNN) paradigm, while using both hand shape and spatial–temporal features obtained from an array of microfabricated force sensors, in order to control the sensory-motor coordination of the robotic system. Prototypical grasping tasks were selected to measure the system performances applied to a computer-interfaced robotic hand. Successful grasps of several objects, completely unknown to the robot, e.g. soft and deformable objects like plastic bottles, soft balls, and Japanese tofu, have been demonstrated.     

Design of a cybernetic hand for perception and action

Strong motivation for developing new prosthetic hand devices is provided by the fact that low functionality and controllability—in addition to poor cosmetic appearance—are the most important reasons why amputees do not regularly use their prosthetic hands. This paper presents the design of the CyberHand, a cybernetic anthropomorphic hand intended to provide amputees with functional hand replacement. Its design was bio-inspired in terms of its modular architecture, its physical appearance, kinematics, sensorization, and actuation, and its multilevel control system. Its underactuated mechanisms allow separate control of each digit as well as thumb–finger opposition and, accordingly, can generate a multitude of grasps. Its sensory system was designed to provide proprioceptive information as well as to emulate fundamental functional properties of human tactile mechanoreceptors of specific importance for grasp-and-hold tasks. The CyberHand control system presumes just a few efferent and afferent channels and was divided in two main layers: a high-level control that interprets the user’s intention (grasp selection and required force level) and can provide pertinent sensory feedback and a low-level control responsible for actuating specific grasps and applying the desired total force by taking advantage of the intelligent mechanics. The grasps made available by the high-level controller include those fundamental for activities of daily living: cylindrical, spherical, tridigital (tripod), and lateral grasps. The modular and flexible design of the CyberHand makes it suitable for incremental development of sensorization, interfacing, and control strategies and, as such, it will be a useful tool not only for clinical research but also for addressing neuroscientific hypotheses regarding sensorimotor control.     

Manual Function in Cebus apella. Digital Mobility,Preshaping, and Endurance in Repetitive Grasping

Manual dexterity varies across species of primates in accord with hand morphology and degree of fine motor control of the digits. Platyrrhine monkeys achieve less direct opposition between thumb and index finger than that of catarrhine primates, and many of them typically whole-hand grip. However, tufted capuchins (Cebus apella), exhibit a degree of independent control of the digits and effective thumb–forefinger opposition. We report how capuchins prehended small objects, with particular attention to the form of sequential fine movements of the fingers, choice of hand, and differences between the two hands in the temporal properties of reaching and grasping. We compare these actions across tasks with differing demands for fine motor control. For tasks that required all the digits to flex in synchrony, capuchins displayed smooth, fast, and efficient reach-to-grasp movements and a higher endurance than for tasks requiring more complex digital coordination. These latter tasks induced a slightly differentiated preshaping of the hand when approaching the objects, indicating preparation for grasping in advance of contact with the object. A right-hand preponderance for complex digital coordination was evident. The monkeys coordinated their fingers rather poorly at the substrate, and they took longer to achieve control of the objects when complex coordination was required than when simultaneous flexion was sufficient. We conclude that precise finger coordination is more effortful and less well coordinated, and the coordination is less lateralized, in capuchins than in catarrhine primates.     

Virtual human hand: model and kinematics

The human hand plays an important role in daily life. It is the interface between the human and the exterior world by positioning, orienting, touching and grasping objects. The human hand has multiple degrees of freedom (DOFs) to enable mobility and dexterity. A virtual human hand model can be inserted into CAD (Computer Aided Design) models to assess the manipulation capabilities in the early design stage to reduce design time and cost. Joystick assessment is one of the important design cases. This study is a first step towards a comprehensive hand simulation tool to simulate the manipulation and grasping of objects. This paper presents a novel 25 DOFs' hand skeletal model based on hand anatomy and hand kinematics: (1) joint range of motion, (2) Denavit–Hartenberg method to define the joint relationship and (3) finger workspace determination. Novelty for this hand model includes arching the palm with the four DOFs added in the carpometacarpal and wrist joints for the ring and small fingers.     

Prediction of fingers posture using artificial neural networks

Predicting the hand and fingers posture during grasping tasks is an important issue in the frame of biomechanics. In this paper, a technique based on neural networks is proposed to learn the inverse kinematics mapping between the fingertip 3D position and the corresponding joint angles. Finger movements are obtained by an instrumented glove and are mapped to a multichain model of the hand. From the fingertip desired position, the neural networks allow predicting the corresponding finger joint angles keeping the specific subject coordination patterns. Two sets of movements are considered in this study. The first one, the training set, consisting of free fingers movements is used to construct the mapping between fingertip position and joint angles. The second one, constructed for testing purposes, is composed of a sequence of grasping tasks of everyday-life objects. The maximal mean error between fingertip measured position and fingertip position obtained from simulated joint angles and forward kinematics is 0.99+/-0.76mm for the training set and 1.49+/-1.62mm for the test set. Also, the maximal RMS error of joint angles prediction is 2.85 degrees and 5.10 degrees for the training and test sets respectively, while the maximal mean joint angles prediction error is -0.11+/-4.34 degrees and -2.52+/-6.71 degrees for the training and test sets, respectively. Results relative to the learning and generalization capabilities of this architecture are also presented and discussed.     

Effects of task dynamics on coordination of the hand muscles and their adaptation to targeted muscle assistance

Dynamic characteristics of a manual task can affect the control of hand muscles due to the difference in biomechanical/physiological characteristics of the muscles and sensory afferents in the hand. We aimed to examine the effects of task dynamics on the coordination of hand muscles, and on the motor adaptation to external assistance. Twenty-four healthy subjects performed one of the two types of a finger extension task, isometric dorsal fingertip force production (static) or isokinetic finger extension (dynamic). Subjects performed the tasks voluntarily without assistance, or with a biomimetic exotendon providing targeted assistance to their extrinsic muscles. In unassisted conditions, significant between-task differences were found in the coordination of the extrinsic and intrinsic hand muscles, while the extrinsic muscle activities were similar between the tasks. Under assistance, while the muscle coordination remained relatively unaffected during the dynamic task, significant changes in the coordination between the extrinsic and intrinsic muscles were observed during the static task. Intermuscular coherence values generally decreased during the static task under assistance, but increased during the dynamic task (all p-values < 0.01). Additionally, a significant change in the task dynamics was induced by assistance only during static task. Our study showed that task type significantly affect coordination between the extrinsic and intrinsic hand muscles. During the static task, a lack of sensory information from musculotendons and joint receptors (more sensitive to changes in length/force) is postulated to have resulted in a neural decoupling between muscles and a consequent isolated modulation of the intrinsic muscle activity.     

Arches of the hand in reach to grasp

Topographically, the hand is described by its anterior (palmar) and posterior (dorsal) surfaces that encompass a hollow cavity that changes its shape during hand preshaping and grasping according to the object to be grasped. The hollow cavity has been described as consisting of three arches that run in different directions: transverse, longitudinal and oblique, spanning the anterior surface of the hand. Although described anatomically, the modulation in the palmar arches has not been investigated kinematically during actual grasping. In this study, we describe and compare biomechanical formulations of the palmar arch, specifically, the distal transverse and the oblique arches. In addition, we introduce another biomechanical formulation of the palmar arch, called the kinematic transverse arch that takes account of the thenar and hypothenar involvement in arch formation. Hand shape modulation during two natural power-grasping tasks was studied in eight healthy adults. Results showed a significant influence of the overall contribution of thenar and hypothenar movement during hand shape modulation. While there was relatively more thenar contribution during transport shaping, more hypothenar contribution was evident during preshaping and contact shaping-the two phases of grasping during which the hand establishes contact with the object. The advantage of the new formulation is that it better described the contributions from thenar and hypothenar movement to palmar arch formation which may be a more accurate depiction of hand preshaping during grasping.     

Order Parameter Dynamics of Body-scaled Hysteresis and Mode Transitions in Grasping Behavior

Several experimental studies have shown that human grasping behavior exhibits a transition from one-handed to two-handed grasping when to-be-grasped objects become larger and larger. The transition point depends on the relative size of objects measured in terms of human body-scales. Most strikingly, the transitions between the two different behavioral ‘modes’ of grasping exhibit hysteresis. That is, one-to-two hand transitions and two-to-one hand transitions occur at different relative object sizes when objects are scaled up or down in size. In our study we approach body-scaled hysteresis and mode transitions in grasping by exploiting the notion that human behavior in general results from self-organization and satisfies appropriately-defined order parameter equations. To this end, grasping transitions and grasping hysteresis are discussed from a theoretical perspective in analogy to cognitive processes defined by Haken’s neural network model for pattern recognition. In doing so, issues such as the exclusivity of grasping modes, biomechanical constraints, mode-mode interactions, single subject behavior and population behavior are explored.     

Muscle as a collagen fiber reinforced composite: a review of force transmission in muscle and whole limb

Even though no direct physiologic evidence proving that myo-tendinous junctions at the end of myofibers are sites of force transmission is available, these locations are accepted to support this function, because its specialized morphology resembles that of load-bearing membranes in structure and location: Its design is fit for force transmission of force exerted by myofibers to tendinous fibrous material. Shearing of the interface between these structures is thought to be stronger than direct tensile transmission. On the basis of morphological studies of 'in-series fibered muscle' and biomechanical modeling it has been argued previously that force could also be transmitted laterally from the tapered ends of myofibers onto in series myofiber via the intramuscular connective tissue component. Shearing of the interfaces between myofibers is hypothesized to be the mechanisms of transmission. The interfaces are made up of basal membranes of both myofibers and their common endomysium. The issue of lateral force transmission from myofibers has not been addressed for whole muscle, in which myofibers are attached at both ends to tendinous aponeuroses, nor is any direct experimental evidence available about possible functional importance of this phenomenon in whole muscle. The primary objective of this presentation is to review available literature on myo-tendinous and myo-fascial force transmission, present evidence from experiments involving tenotomy, fasciatomy and aponeurotomy regarding its importance and consider implications for our thinking about muscle(s) and movement.     

One Digit Interruption: The Altered Force Patterns during Functionally Cylindrical Grasping Tasks in Patients with Trigger Digits

Most trigger digit (TD) patients complain that they have problems using their hand in daily or occupational tasks due to single or multiple digits being affected. Unfortunately, clinicians do not know much about how this disease affects the subtle force coordination among digits during manipulation. Thus, this study examined the differences in force patterns during cylindrical grasp between TD and healthy subjects. Forty-two TD patients with single digit involvement were included and sorted into four groups based on the involved digits, including thumb, index, middle and ring fingers. Twelve healthy subjects volunteered as healthy controls. Two testing tasks, holding and drinking, were performed by natural grasping with minimal forces. The relations between the force of the thumb and each finger were examined by Pearson correlation coefficients. The force amount and contribution of each digit were compared between healthy controls and each TD group by the independent t test. The results showed all TD groups demonstrated altered correlation patterns of the thumb relative to each finger. Larger forces and higher contributions of the index finger were found during holding by patients with index finger involved, and also during drinking by patients with affected thumb and with affected middle finger. Although no triggering symptom occurred during grasping, the patients showed altered force patterns which may be related to the role of the affected digit in natural grasping function. In conclusion, even if only one digit was affected, the subtle force coordination of all the digits was altered during simple tasks among the TD patients. This study provides the information for the future studies to further comprehend the possible injuries secondary to the altered finger coordination and also to adopt suitable treatment strategies.     

Object Grasping using the Minimum Variance Model

Reaching-to-grasp has generally been classified as the coordination of two separate visuomotor processes: transporting the hand to the target object and performing the grip. An alternative view has recently been formed that grasping can be explained as pointing movements performed by the digits of the hand to target positions on the object. We have previously implemented the minimum variance model of human movement as an optimal control scheme suitable for control of a robot arm reaching to a target. Here, we extend that scheme to perform grasping movements with a hand and arm model. Since the minimum variance model requires that signal-dependent noise be present on the motor commands to the actuators of the movement, our approach is to plan the reach and the grasp separately, in line with the classical view, but using the same computational model for pointing, in line with the alternative view. We show that our model successfully captures some of the key characteristics of human grasping movements, including the observations that maximum grip size increases with object size (with a slope of approximately 0.8) and that this maximum grip occurs at 60–80% of the movement time. We then use our model to analyse contributions to the digit end-point variance from the two components of the grasp (the transport and the grip). We also briefly discuss further areas of investigation that are prompted by our model.     

Quantification and visualization of coordination during non-cyclic upper extremity motion

There are many design challenges in creating at-home tele-monitoring systems that enable quantification and visualization of complex biomechanical behavior. One such challenge is robustly quantifying joint coordination in a way that is intuitive and supports clinical decision-making. This work defines a new measure of coordination called the relative coordination metric (RCM) and its accompanying normalization schemes. RCM enables quantification of coordination during non-constrained discrete motions. Here RCM is applied to a grasping task. Fifteen healthy participants performed a reach, grasp, transport, and release task with a cup and a pen. The measured joint angles were then time-normalized and the RCM time-series were calculated between the shoulder-elbow, shoulder-wrist, and elbow-wrist. RCM was normalized using four differing criteria: the selected joint degree of freedom, angular velocity, angular magnitude, and range of motion. Percent time spent in specified RCM ranges was used as a composite metric and was evaluated for each trial. RCM was found to vary based on: (1) chosen normalization scheme, (2) the stage within the task, (3) the object grasped, and (4) the trajectory of the motion. The RCM addresses some of the limitations of current measures of coordination because it is applicable to discrete motions, does not rely on cyclic repetition, and uses velocity-based measures. Future work will explore clinically relevant differences in the RCM as it is expanded to evaluate different tasks and patient populations.     

Development of an Anthropomorphic Robotic Arm and Hand for Interactive Humanoids

Humanoid robots are designed and built to mimic human form and movement.Ultimately,they are meant to resemble the size and physical abilities of a human in order to function in human-oriented environments and to work autonomously but to pose no physical threat to humans.Here,a humanoid robot that resembles a human in appearance and movement is built using powerful actuators paired with gear trains,joint mechanisms,and motor drivers that are all encased in a package no larger than that of the human physique.In this paper,we propose the construction of a humanoid-applicable anthropomorphic 7-DoF arm complete with an 8-DoF hand.The novel mechanical design of this humanoid arm makes it sufficiently compact to be compatible with currently available narrating-model humanoids,and to be sufficiently powerful and flexible to be functional; the number of degrees of freedom endowed in this robotic arm is sufficient for executing a wide range of tasks,including dexterous hand movements.The developed humanoid arm and hand are capable of sensing and interpreting incoming external force using the motor in each joint current without conventional torque sensors.The humanoid arm adopts an algorithm to avoid obstacles and the dexterous hand is capable of grasping objects.The developed robotic arm is suitable for use in an interactive humanoid robot.     

Simulation modifies prehension: evidence for a conjoined representation of the graspable features of an object and the action of grasping it

Movement formulas, engrams, kinesthetic images and internal models of the body in action are notions derived mostly from clinical observations of brain-damaged subjects. They also suggest that the prehensile geometry of an object is integrated in the neural circuits and includes the object's graspable characteristics as well as its semantic properties. In order to determine whether there is a conjoined representation of the graspable characteristics of an object in relation to the actual grasping, it is necessary to separate the graspable (low-level) from the semantic (high-level) properties of the object. Right-handed subjects were asked to grasp and lift a smooth 300-g cylinder with one hand, before and after judging the level of difficulty of a "grasping for pouring" action, involving a smaller cylinder and using the opposite hand. The results showed that simulated grasps with the right hand exert a direct influence on actual motor acts with the left hand. These observations add to the evidence that there is a conjoined representation of the graspable characteristics of the object and the biomechanical constraints of the arm.     

Mechanical properties of tendon and aponeurosis of human gastrocnemius muscle in vivo.

Load-strain characteristics of tendinous tissues (Achilles tendon and aponeurosis) were determined in vivo for human medial gastrocnemius (MG) muscle. Seven male subjects exerted isometric plantar flexion torque while the elongation of tendinous tissues of MG was determined from the tendinous movements by using ultrasonography. The maximal strain of the Achilles tendon and aponeurosis, estimated separately from the elongation data, was 5.1 +/- 1.1 and 5.9 +/- 1.6%, respectively. There was no significant difference in strain between the Achilles tendon and aponeurosis. In addition, no significant difference in strain was observed between the proximal and distal regions of the aponeurosis. The results indicate that tendinous tissues of the MG are homogeneously stretched along their lengths by muscle contraction, which has functional implications for the operation of the human MG muscle-tendon unit in vivo.     

A novel approach to modelling and simulating the contact behaviour between a human hand model and a deformable object

A deeper understanding of biomechanical behaviour of human hands becomes fundamental for any human hand-operated activities. The integration of biomechanical knowledge of human hands into product design process starts to play an increasingly important role in developing an ergonomic product-to-user interface for products and systems requiring high level of comfortable and responsive interactions. Generation of such precise and dynamic models can provide scientific evaluation tools to support product and system development through simulation. This type of support is urgently required in many applications such as hand skill training for surgical operations, ergonomic study of a product or system developed and so forth. The aim of this work is to study the contact behaviour between the operators' hand and a hand-held tool or other similar contacts, by developing a novel and precise nonlinear 3D finite element model of the hand and by investigating the contact behaviour through simulation. The contact behaviour is externalised by solving the problem using the bi-potential method. The human body's biomechanical characteristics, such as hand deformity and structural behaviour, have been fully modelled by implementing anisotropic hyperelastic laws. A case study is given to illustrate the effectiveness of the approach.     

Effects of reversible inactivation of the supplementary motor area (SMA) on unimanual grasp and bimanual pull and grasp performance in monkeys

Abstract The supplementary motor area (SMA) was reversibly inactivated by muscimol microinfusion in two monkeys while they were performing two motor tasks: (1) a delayed conditional bimanual drawer pulling and grasping sequence which was initiated on a self-paced basis; (2) a unimanual reach and grasp task (modified Kluver board task). Unilateral or bilateral inactivation of the SMA induced a prominent deficit in trial initiation of bimanual sequential movements, affecting the hand contralateral to the inactivated side or both hands, respectively. The deficit was a long lasting (10-15 min or more) inability of the monkey to place its hand (s) in the ready position on start touch-sensitive pads, a condition required to initiate the drawer task. However, if after such a deficit period, the experimenter put his hand on the start touch-sensitive pad to initiate the trial, then the monkey executed the drawer task without obvious motor deficit. SMA inactivation did not affect unimanual reaching and grasping movements in the board task. In contrast to the SMA, inactivation of other motor areas (primary, premotor dorsal, anterior intraparietal area) did not affect the initiation of movement sequences in the drawer task. These data thus indicate that the SMA plays a crucial and specific role in initiation of self-paced movement sequences. However, SMA inactivation did not prevent the monkeys to perform coordinated movements of the two forelimbs and hands, indicating that SMA is not necessary for bimanual coordination.     

Hand preference in a captive island group of chimpanzees (Pan troglodytes)

Morphological cerebral asymmetries in chimpanzee brains, similar to those found in humans, in whom they are associated with speech and handedness, suggest the possibility of functional lateralization in the chimpanzee. This possibility was investigated by examining hand preferences in an island group of five chimpanzees on a series of unimanual and bimanual tasks that are diagnostic of human hand and cerebral dominance. Each subject was tested in a double compartment cage on three unimanual nonsequential, three unimanual sequential, and three bimanual coordination tasks. One of the three unimanual sequential tasks was a bar-press task that is analogous to the commonly used human finger-tapping task. For the unimanual tasks, exclusive of the bar-press, the chimpanzees showed a highly individualistic pattern of hand preference that did not change as a function of task complexity. On the bar-press task, four of five subjects produced higher rates with one hand compared to the other; however, relative hand performance on this task was unrelated to hand preference on the other unimanual tasks. For the group of subjects, performance rates did not differ between the left and right hands; however, a practice effect was observed for the right hand in all subjects. The bimanual tasks also revealed a complex pattern of individual handedness, with no trends apparent for the group as a whole. Consistent with previous findings, the results from these tests on this group of five chimpanzees suggest that cerebral morphological asymmetries in the chimpanzee are not associated with motor dominance as reflected in handedness.     

Grasp modelling with a biomechanical model of the hand

The use of a biomechanical model for human grasp modelling is presented. A previously validated biomechanical model of the hand has been used. The equilibrium of the grasped object was added to the model through the consideration of a soft contact model. A grasping posture generation algorithm was also incorporated into the model. All the geometry was represented using a spherical extension of polytopes (s-topes) for efficient collision detection. The model was used to simulate an experiment in which a subject was asked to grasp two cylinders of different diameters and weights. Different objective functions were checked to solve the indeterminate problem. The normal finger forces estimated by the model were compared to those experimentally measured. The popular objective function sum of the squared muscle stresses was shown not suitable for the grasping simulation, requiring at least being complemented by task-dependent grasp quality measures.