Characterization of multijoint finger stiffness: dependence on finger posture and force direction

Characterization of Human Shoulder Joint Stiffness Across 3D Arm Postures and Its Sex Differences

Understanding the characteristics of shoulder joint stiffness can offer insights into how the shoulder joint contributes to arm stability and assists in various arm postures and movements. This study aims to characterize posture-dependent shoulder stiffness in a three-dimensional (3D) space and investigate its potential sex differences. A multi-degree-of-freedom, parallel-actuated shoulder exoskeleton robot was used' to perturb the participant's shoulder joint and measure the resulting torque responses while participants relaxed their shoulder muscles. The group average results of 40 healthy individuals (20 males and 20 females) revealed that arm postures significantly affect shoulder stiffness, particularly in postures involving shoulder flexion/extension and horizontal flexion/extension. Shoulder stiffness consistently increased as the shoulder flexion angle decreased and the shoulder horizontal flexion/extension approached the limit of its range of motion. The comparative group results between males and females indicated that shoulder stiffness in males was greater than that in females across all 15 arm postures measured in this study. Even after normalizing the data by subject body mass, the female group showed significantly lower stiffness than the male group in 12 out of the 15 arm postures. The results highlight that 3D arm postures and sex significantly affect shoulder stiffness even under relaxed muscles. This study provides valuable foundations for future studies aimed at characterizing shoulder stiffness in the context of active muscles and dynamic movement tasks, evaluating changes in shoulder stiffness following neuromuscular injuries, and formulating rehabilitative training protocols for individuals suffering from shoulder problems.

A Biorealistic Computational Model Unfolds Human-Like Compliant Properties for Control of Hand Prosthesis

Objective: Human neuromuscular reflex control provides a biological model for a compliant hand prosthesis. Here we present a computational approach to understanding the emerging human-like compliance, force and position control, and stiffness adaptation in a prosthetic hand with a replica of human neuromuscular reflex. Methods: A virtual twin of prosthetic hand was constructed in the MuJoCo environment with a tendon-driven anthropomorphic hand structure. Biorealistic mathematic models of muscle, spindle, spiking-neurons and monosynaptic reflex were implemented in neuromorphic chips to drive the virtual hand for real-time control. Results: Simulation showed that the virtual hand acquired human-like ability to control fingertip position, force and stiffness for grasp, as well as the capacity to interact with soft objects by adaptively adjusting hand stiffness. Conclusion: The biorealistic neuromorphic reflex model restores human-like neuromuscular properties for hand prosthesis to interact with soft objects.

Human-like Endtip Stiffness Modulation Inspires Dexterous Manipulation with Robotic Hands

We present a novel method for biomechanically inspired mechanical and control design by quantifying stable manipulation regions in 3D space for tendon-driven systems. Using this method, we present an analysis of the stiffness properties for a human-like index finger and thumb. Although some studies have previously evaluated biomechanical stiffness for grasping and manipulation, no prior works have evaluated the effect of anatomical stiffness parameters throughout the reachable workspace of the index finger or thumb. The passive stiffness model of biomechanically accurate tendon-driven human-like fingers enables analysis of conservatively passive stable regions. The passive stiffness model of the index finger shows that the greatest stiffness ellipsoid volume is aligned to efficiently oppose the anatomical thumb. The thumb model reveals that the greatest stiffness aligns with abduction/adduction near the index finger and shifts to align with the flexion axes for more efficient opposition of the ring or little fingers. Based on these models, biomechanically inspired stiffness controllers that efficiently utilize the underlying stiffness properties while maximizing task criteria can be developed. Trajectory tracking tasks are experimentally tested on the index finger to show the effect of stiffness and stability boundaries on performance.

An Open-Source Robotic Tool for the Simulation of Quasi-Static Finger Pressing on Stationary and Vibrating Surfaces

The Bogus Finger is a remote-controllable tool for simulating vertical pressing forces of various magnitude as exerted by a human finger. Its main application is the characterization of haptic devices under realistic active touch conditions. The device is released as an open-source hardware and software DIY project that can be easily built using off-the-shelf components. We report the characterization of the quasi-static properties of the device, and validate its dynamic response to pressing on a vibrating surface by comparison with human fingers. The present prototype configuration accurately reproduces the mechanical impedance of the human finger in the frequency range 200-400 Hz.

Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator

Stroke has been the leading cause of disability due to the induced spasticity in the upper extremity. The constant flexion of spastic fingers following stroke has not been well described. Accurate measurements for joint stiffness help clinicians have a better access to the level of impairment after stroke. Previously, we conducted a method for quantifying the passive finger joint stiffness based on the pressure-angle relationship between the spastic fingers and the soft-elastic composite actuator (SECA). However, it lacks a ground-truth to demonstrate the compatibility between the SECA-facilitated stiffness estimation and standard joint stiffness quantification procedure. In this study, we compare the passive metacarpophalangeal (MCP) joint stiffness measured using the SECA with the results from our designed standalone mechatronics device, which measures the passive metacarpophalangeal joint torque and angle during passive finger rotation. Results obtained from the fitting model that concludes the stiffness characteristic are further compared with the results obtained from SECA-Finger model, as well as the clinical score of Modified Ashworth Scale (MAS) for grading spasticity. These findings suggest the possibility of passive MCP joint stiffness quantification using the soft robotic actuator during the performance of different tasks in hand rehabilitation.

An approach to object-level stiffness regulation of hand-arm systems subject to under-actuation constraints

When using a tool with a robotic hand-arm system, the stiffness at the grasped object plays a key role in the interaction with the environment, allowing the successful execution of the task. However, the rapidly increasing use of under-actuated hands in robotic systems due to their robustness and simplicity of control, pose limitations to the achievable object-level stiffness. Indeed, due to the serial coupling of the hand and the arm, the resulting object-level stiffness is determined by the most compliant of both elements. To address this problem, we propose a novel controller that takes into account the limited achievable geometry of the object stiffness ellipsoid given by a hand with under-actuation constraints, and exploits the contribution of the robotic arm in reshaping the final stiffness towards the desired profile. The under-actuation is illustrated by a coordinated stiffening of the hand fingers. The proposed method is experimentally validated by a hand-arm system performing a peg-in-hole task.

Modulation of finger muscle activation patterns across postures is coordinated across all muscle groups

Successful grasp requires that grip forces be properly directed between the fingertips and the held object. Changes in digit posture significantly affect the mapping between muscle force and fingertip force. Joint torques must subsequently be altered to maintain the desired force direction at the fingertips. Our current understanding of the roles of hand muscles in force production remains incomplete, as past studies focused on a limited set of postures or force directions. To thoroughly examine how hand muscles adapt to changing external (force direction) and internal (posture) conditions, activation patterns of six index finger muscles were examined with intramuscular electrodes in 10 healthy subjects. Participants produced submaximal isometric forces in each of six orthogonal directions at nine different finger postures. Across force directions, participants significantly altered activation patterns to accommodate postural changes in the interphalangeal joint angles but not changes in the metacarpophalangeal joint angles. Modulation of activation levels of the extrinsic hand muscles, particularly the extensors, were as great as those of intrinsic muscles, suggesting that both extrinsic and intrinsic muscles were involved in creating the desired forces. Despite considerable between-subject variation in the absolute activation patterns, principal component analysis revealed that participants used similar strategies to accommodate the postural changes. The changes in muscle coordination also helped increase joint impedance in order to stabilize the end-point force direction. This effect counteracts the increased signal-dependent motor noise that arises with greater magnitude of muscle activation as interphalangeal joint flexion is increased. These results highlight the role of the extrinsic muscles in controlling fingertip force direction across finger postures.NEW & NOTEWORTHY We examined how hand muscles adapt to changing external (force direction) and internal (posture) conditions. Muscle activations, particularly of the extrinsic extensors, were significantly affected by postural changes of the interphalangeal, but not metacarpophalangeal, joints. Joint impedance was modulated so that the effects of the signal-dependent motor noise on the force output were reduced. Comparisons with theoretical solutions showed that the chosen activation patterns occupied a small portion of the possible solution space, minimizing the maximum activation of any one muscle.

Soft Rehabilitation Actuator With Integrated Post-stroke Finger Spasticity Evaluation

Strokes cause severe impairment of hand function because of the spasticity in the affected upper extremities. Proper spasticity evaluation is critical to facilitate neural plasticity for rehabilitation after stroke. However, existing methods for measuring spasticity, e.g. Modified Ashworth Scale (MAS), highly depends on clinicians' experiences, which are subjective and lacks quantitative details. Here, we introduce the first rehabilitation actuator that objectively reflects the condition of post-stroke finger spasticity. The actuator is 3D printed with soft materials. By considering the finger and the actuator together, the spasticity, i.e. stiffness, in finger is obtained from the pressure-angle relationship. The method is validated by simulations using finite element analysis (FEA) and experiments on mannequin fingers. Furthermore, it is examined on four stroke subjects and four healthy subjects. Results show the finger stiffness increases significantly from healthy subjects to stroke subjects, particularly those with high MAS score. For patients with the same MAS score, stiffness variation can be a few times. With this soft actuator, a hand rehabilitation robot that may tell the therapeutic progress during the rehabilitation training is readily available.

Design and Characterization of a Robotic Device for the Assessment of Hand Proprioceptive, Motor, and Sensorimotor Impairments

Hand function is often impaired after neurological injuries such as stroke. In order to design patient-specific rehabilitation, it is essential to quantitatively assess those deficits. Current clinical scores cannot provide the required level of detail, and most assessment devices have been developed for the proximal joints of the upper limb. This paper presents a new robotic platform for the assessment of proprioceptive, motor, and sensorimotor hand impairments. A detailed technical evaluation demonstrated the capabilities to render different haptic environments required for a comprehensive assessment battery, and showed that the device is suitable for human interaction due to its ergonomic design. A preliminary study on proprioceptive assessment using a gauge position matching task with one healthy, one stroke, and one multiple sclerosis subject showed that the robotic system is able to rapidly and sensitively quantify proprioceptive deficits, and has the potential to be integrated into the clinical settings.

A Bio-inspired Grasp Stiffness Control for Robotic Hands

This work presents a bio-inspired grasp stiffness control for robotic hands based on the concepts of Common Mode Stiffness (CMS) and Configuration Dependent Stiffness (CDS). Using an ellipsoid representation of the desired grasp stiffness, the algorithm focuses on achieving its geometrical features. Based on preliminary knowledge of the fingers workspace, the method starts by exploring the possible hand poses that maintain the grasp contacts on the object. This outputs a first selection of feasible grasp configurations providing the base for the CDS control. Then, an optimization is performed to find the minimum joint stiffness (CMS control) that would stabilize these grasps. This joint stiffness can be increased afterwards depending on the task requirements. The algorithm finally chooses among all the found stable configurations the one that results in a better approximation of the desired grasp stiffness geometry (CDS). The proposed method results in a reduction of the control complexity, needing to independently regulate the joint positions, but requiring only one input to produce the desired joint stiffness. Moreover, the usage of the fingers pose to attain the desired grasp stiffness results in a more energy-efficient configuration than only relying on the joint stiffness (i.e., joint torques) modifications. The control strategy is evaluated using the fully actuated Allegro Hand while grasping a wide variety of objects. Different desired grasp stiffness profiles are selected to exemplify several stiffness geometries.

Impact of Targeted Assistance of Multiarticular Finger Musculotendons on the Coordination of Finger Muscles During Isometric Force Production

Neurological injuries often cause degraded motor control. While rehabilitation efforts typically focus on movement kinematics, abnormal muscle activation patterns are often the primary source of impairment. Muscle-based therapies are likely more effective than joint-based therapy. In this paper, we examined the feasibility of biomimetic input mimicking the action of human musculotendons in altering hand muscle coordination. Twelve healthy subjects produced a submaximal isometric dorsal fingertip force, while a custom actuator provided assistance mirroring the actions of either the extrinsic extensor or the intrinsic muscles of the index finger. The biomimetic inputs reduced the activation level of all task-related muscles, but the degree of change was different across the muscles, resulting in significant changes in their coordination (co-contraction ratios) and force-electromyography correlations. Each biomimetic assistance particularly increased the neural coupling between its targeted muscle and the antagonist muscle. Subjects appeared to fully take advantage of the assistance, as they provided minimal level of effort to achieve the task goal. The targeted biomimetic assistance may be used to retrain activation patterns post-stroke by effectively modulating connectivity between the muscles in the functional context and could be beneficial to restore hand function and reduce disability.

Introducing Whole Finger Effects in Surface Haptics: An Extended Stick-Slip Model Incorporating Finger Stiffness

The kinematic serial chain configuration of a finger modulates the frictional properties during tactile exploration tasks. This paper analyzes and subsequently models the effects of the entire finger during sliding operations on a surface. Qualitative and quantitative study of finger movement patterns with postures, sliding directions, and contact angles first indicate the effect of finger stiffness on contact mechanics. A "stiffness ellipse" is subsequently modeled to incorporate finger pose effects, and then coupled with the lumped mass-spring-damper model of the finger pad to estimate resultant contact forces. The performance of the proposed model is verified by comparing with experimental results obtained from ten subjects. The proposed model could estimate the general tendencies of contact forces with change in postures (Extended and Flexed), sliding directions (proximal and distal), and contact angles (20°, 40° and 60°). The experimental results indicate that finger stiffness significantly modulates the contact forces, stick-slip frequency, preloading duration and initial spike during sliding. Introduction of finger posture effects could explain the change in finger normal force during tactile exploration tasks. The proposed haptic rendering model can be used to give a more natural user feedback in virtual fingertip-surface interactions.

Multidigit force control during unconstrained grasping in response to object perturbations

Because of the complex anatomy of the human hand, in the absence of external constraints, a large number of postures and force combinations can be used to attain a stable grasp. Motor synergies provide a viable strategy to solve this problem of motor redundancy. In this study, we exploited the technical advantages of an innovative sensorized object to study unconstrained hand grasping within the theoretical framework of motor synergies. Participants were required to grasp, lift, and hold the sensorized object. During the holding phase, we repetitively applied external disturbance forces and torques and recorded the spatiotemporal distribution of grip forces produced by each digit. We found that the time to reach the maximum grip force during each perturbation was roughly equal across fingers, consistent with a synchronous, synergistic stiffening across digits. We further evaluated this hypothesis by comparing the force distribution of human grasping vs. robotic grasping, where the control strategy was set by the experimenter. We controlled the global hand stiffness of the robotic hand and found that this control algorithm produced a force pattern qualitatively similar to human grasping performance. Our results suggest that the nervous system uses a default whole hand synergistic control to maintain a stable grasp regardless of the number of digits involved in the task, their position on the objects, and the type and frequency of external perturbations.NEW & NOTEWORTHY We studied hand grasping using a sensorized object allowing unconstrained finger placement. During object perturbation, the time to reach the peak force was roughly equal across fingers, consistently with a synergistic stiffening across fingers. Force distribution of a robotic grasping hand, where the control algorithm is based on global hand stiffness, was qualitatively similar to human grasping. This suggests that the central nervous system uses a default whole hand synergistic control to maintain a stable grasp.

Strategy switching in the stabilization of unstable dynamics

In order to understand mechanisms of strategy switching in the stabilization of unstable dynamics, this work investigates how human subjects learn to become skilled users of an underactuated bimanual tool in an unstable environment. The tool, which consists of a mass and two hand-held non-linear springs, is affected by a saddle-like force-field. The non-linearity of the springs allows the users to determine size and orientation of the tool stiffness ellipse, by using different patterns of bimanual coordination: minimal stiffness occurs when the two spring terminals are aligned and stiffness size grows by stretching them apart. Tool parameters were set such that minimal stiffness is insufficient to provide stable equilibrium whereas asymptotic stability can be achieved with sufficient stretching, although at the expense of greater effort. As a consequence, tool users have two possible strategies for stabilizing the mass in different regions of the workspace: 1) high stiffness feedforward strategy, aiming at asymptotic stability and 2) low stiffness positional feedback strategy aiming at bounded stability. The tool was simulated by a bimanual haptic robot with direct torque control of the motors. In a previous study we analyzed the behavior of naïve users and we found that they spontaneously clustered into two groups of approximately equal size. In this study we trained subjects to become expert users of both strategies in a discrete reaching task. Then we tested generalization capabilities and mechanism of strategy-switching by means of stabilization tasks which consist of tracking moving targets in the workspace. The uniqueness of the experimental setup is that it addresses the general problem of strategy-switching in an unstable environment, suggesting that complex behaviors cannot be explained in terms of a global optimization criterion but rather require the ability to switch between different sub-optimal mechanisms.

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

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

Constraint Study for a Hand Exoskeleton: Human Hand Kinematics and Dynamics

In the last few years, the number of projects studying the human hand from the robotic point of view has increased rapidly, due to the growing interest in academic and industrial applications. Nevertheless, the complexity of the human hand given its large number of degrees of freedom (DoF) within a significantly reduced space requires an exhaustive analysis, before proposing any applications. The aim of this paper is to provide a complete summary of the kinematic and dynamic characteristics of the human hand as a preliminary step towards the development of hand devices such as prosthetic/robotic hands and exoskeletons imitating the human hand shape and functionality. A collection of data and constraints relevant to hand movements is presented, and the direct and inverse kinematics are solved for all the fingers as well as the dynamics; anthropometric data and dynamics equations allow performing simulations to understand the behavior of the finger.

Contributions of intrinsic visco-elastic torques during planar index finger and wrist movements

Human hand movements have been studied for many decades, yet the role of hand biomechanics in achieving dexterity has not been fully understood. In this paper, we investigate the contributions of the intrinsic passive viscoelastic component in the hand during the coordinated wrist and hand movements. We compare the contributions of stiffness, damping, and dynamics torques under two types of joint phase movements at two speeds. The analysis of the data collected from subject studies demonstrated that the passive visco-elastic component is dominant over dynamic coupling terms. Although the exact contributions of the three torques vary under different speeds and phasic movements, the stiffness torque was the highest (at least 47%) followed by the damping torque, while the dynamics torque was the lowest (less than 11%) in all movement scenarios. Comparisons with studies involving coordinated arm movements illustrate that dominant torques in arm and hand movements are different suggesting that neural control strategies might be distinct as well.

Impedance control is selectively tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make movements in unstable environments with varied directions. When faced with a single direction of instability, humans learn to selectively co-contract their arm muscles tuning the mechanical stiffness of the limb end point to stabilize movements. This study examines, for the first time, subjects simultaneously adapting to two distinct directions of instability, a situation that may typically occur when using tools. Subjects learned to perform reaching movements in two directions, each of which had lateral instability requiring control of impedance. The subjects were able to adapt to these unstable interactions and switch between movements in the two directions; they did so by learning to selectively control the end-point stiffness counteracting the environmental instability without superfluous stiffness in other directions. This finding demonstrates that the central nervous system can simultaneously tune the mechanical impedance of the limbs to multiple movements by learning movement-specific solutions. Furthermore, it suggests that the impedance controller learns as a function of the state of the arm rather than a general strategy.

The manipulative complexity of Lower Paleolithic stone toolmaking

BACKGROUND

Early stone tools provide direct evidence of human cognitive and behavioral evolution that is otherwise unavailable. Proper interpretation of these data requires a robust interpretive framework linking archaeological evidence to specific behavioral and cognitive actions.

METHODOLOGY/PRINCIPAL FINDINGS

Here we employ a data glove to record manual joint angles in a modern experimental toolmaker (the 4(th) author) replicating ancient tool forms in order to characterize and compare the manipulative complexity of two major Lower Paleolithic technologies (Oldowan and Acheulean). To this end we used a principled and general measure of behavioral complexity based on the statistics of joint movements.

CONCLUSIONS/SIGNIFICANCE

This allowed us to confirm that previously observed differences in brain activation associated with Oldowan versus Acheulean technologies reflect higher-level behavior organization rather than lower-level differences in manipulative complexity. This conclusion is consistent with a scenario in which the earliest stages of human technological evolution depended on novel perceptual-motor capacities (such as the control of joint stiffness) whereas later developments increasingly relied on enhanced mechanisms for cognitive control. This further suggests possible links between toolmaking and language evolution.

Prehension synergies and control with referent hand configurations

We used the framework of the equilibrium-point hypothesis (in its updated form based on the notion of referent configuration) to investigate the multi-digit synergies at two levels of a hypothetical hierarchy involved in prehensile actions. Synergies were analyzed at the thumb-virtual finger (VF) level (VF is an imaginary digit with the mechanical action equivalent to that of the four actual fingers) and at the individual finger level. The subjects performed very quick vertical movements of a handle into a target. A load could be attached off-center to provide a pronation or supination torque. In a few trials, the handle was unexpectedly fixed to the table and the digits slipped off the sensors. In such trials, the hand stopped at a higher vertical position and rotated into pronation or supination depending on the expected torque. The aperture showed non-monotonic changes with a large, fast decrease and further increase, ending up with a smaller distance between the thumb and the fingers as compared to unperturbed trials. Multi-digit synergies were quantified using indices of co-variation between digit forces and moments of force across unperturbed trials. Prior to the lifting action, high synergy indices were observed at the individual finger level while modest indices were observed at the thumb-VF level. During the lifting action, the synergies at the individual finger level disappeared while the synergy indices became higher at the thumb-VF level. The results support the basic premise that, within a given task, setting a referent configuration may be described with a few referent values of variables that influence the equilibrium state, to which the system is attracted. Moreover, the referent configuration hypothesis can help interpret the data related to the trade-off between synergies at different hierarchical levels.

Maximal voluntary fingertip force production is not limited by movement speed in combined motion and force tasks

Numerous studies of limbs and fingers propose that force-velocity properties of muscle limit maximal voluntary force production during anisometric tasks, i.e., when muscles are shortening or lengthening. Although this proposition appears logical, our study on the simultaneous production of fingertip motion and force disagrees with this commonly held notion. We asked eight consenting adults to use their dominant index fingertip to maximize voluntary downward force against a horizontal surface at specific postures (static trials), and also during an anisometric "scratching" task of rhythmically moving the fingertip along a 5.8 +/- 0.5 cm target line. The metronome-timed flexion-extension movement speed varied 36-fold from "slow" (1.0 +/- 0.5 cm/s) to "fast" (35.9 +/- 7.8 cm/s). As expected, maximal downward voluntary force diminished (44.8 +/- 15.6%; p = 0.001) when any motion (slow or fast) was added to the task. Surprisingly, however, a 36-fold increase in speed did not affect this reduction in force magnitude. These remarkable results for such an ordinary task challenge the dominant role often attributed to force-velocity properties of muscle and provide insight into neuromechanical interactions. We propose an explanation that the simultaneous enforcement of mechanical constraints for motion and force reduces the set of feasible motor commands sufficiently so that force-velocity properties cease to be the force-limiting factor. While additional work is necessary to reveal the governing mechanisms, the dramatic influence that the simultaneous enforcement of motion and force constraints has on force output begins to explain the vulnerability of dexterous function to development, aging, and even mild neuromuscular pathology.

Task-dependent selection of grasp kinematics and stiffness in human object manipulation

Object manipulation with the hand is a complex task. The task has redundancies at many levels, allowing many possibilities for the selection of grasp points, the orientation and posture of the hand, the forces to be applied at each fingertip and the impedance properties of the hand. Despite this inherent complexity, humans perform object manipulation nearly effortlessly. This article presents experimental findings of how humans grasp and manipulate objects, and examines the compatibility of grasps selected for specific tasks. This is accomplished by looking at the velocity transmission and force transmission ellipsoids, which represent the transmission ratios of the corresponding quantity from the joints to the object, as well as the stiffness ellipsoid which represents the directional stiffness of the grasp. These ellipsoids allow visualization of the grasp Jacobian and grasp stiffness matrices. The results show that the orientation of the ellipsoids can be related to salient task requirements.

Prehension stability: experiments with expanding and contracting handle

We studied adjustments in digit forces and moments during holding a vertically oriented handle under slow, externally imposed changes in the width of the grasp. Subjects (n = 8) grasped a customized motorized handle with five digits and held it statically in the air. The handle width either increased (expanded) or decreased (contracted) at a rate of 1.0, 1.5, or 2.0 mm/s, while the subjects were asked to ignore the handle width changes, and their attention was distracted. External torques of 0.0, 0.25, and 0.5 Nm were applied to the handle in two directions. Forces and moments at the digit tips were measured with six-component sensors. The analysis was performed at the virtual finger (VF) and individual finger (IF) levels (VF is an imagined finger that produces the same wrench, i.e., the force and moment, as several fingers combined). In all the tasks, the normal VF and thumb forces increased with the handle expansion and decreased with the handle contraction. Similar behavior was seen for the thumb tangential force. In contrast, the VF tangential force decreased with the handle expansion and increased with the handle contraction. The changes in the tangential forces assisted the perturbations in the tasks requiring exertion of the supination moments and annulled the perturbation in the pronation effort tasks. In the former tasks, the equilibrium was maintained by the changes of the moments of normal forces, whereas in the latter tasks, the equilibrium was maintained by the changes of the moments of the tangential forces. Analysis at the IF level has shown that the resultant force and moment exerted on the object could arise from dissimilar adjustments of individual fingers to the same handle width change. The complex adjustments of digit forces to handle width change may be viewed as coming from two sources. First, there are local spring-like adjustments of individual digit forces and moments caused by both mechanical properties of the digits and the action of spinal reflexes. These stiffness-like reactions mainly assist in perturbing the rotational equilibrium of the object rather than in maintaining it. Second, there are tilt-preventing adjustments defined by the common task constraints that unite the digits into a task-specific synergy. The "virtual springs theory" developed in robotics literature is insufficient for describing the phenomena observed in human grasping.

Finger joint impedance during tapping on a computer keyswitch

We studied the dynamic behavior of finger joints during the contact period of tapping on a computer keyswitch, to characterize and parameterize joint function with a lumped-parameter impedance model. We tested the hypothesis that the metacarpophalangeal (MCP) and interphalangeal (IP) joints act similarly in terms of kinematics, torque, and energy production when tapping. Fifteen human subjects tapped with the index finger of the right hand on a computer keyswitch mounted on a two-axis force sensor, which measured forces in the vertical and sagittal planes. Miniature fiber-optic goniometers mounted across the dorsal side of each joint measured joint kinematics. Joint torques were calculated from endpoint forces and joint kinematics using an inverse dynamic algorithm. For each joint, a linear spring and damper model was fitted to joint torque, position, and velocity during the contact period of each tap (22 per subject on average). The spring-damper model could account for over 90% of the variance in torque when loading and unloading portions of the contact were separated, with model parameters comparable to those previously measured during isometric loading of the finger. The finger joints functioned differently, as illustrated by energy production during the contact period. During the loading phase of contact the MCP joint flexed and produced energy, whereas the proximal and distal IP joints extended and absorbed energy. These results suggest that the MCP joint does work on the interphalangeal joints as well as on the keyswitch.

Effects of keyswitch design and finger posture on finger joint kinematics and dynamics during tapping on computer keyswitches

OBJECTIVE

To examine the effects of postural and keyswitch characteristics on musculoskeletal tissue loading during tapping on computer keyswitches.

DESIGN

We hypothesized that joint torques, stiffness and work parameters differ across keyswitch designs and finger postures typical of those observed during computer keyboard typing. We experimentally measured joint kinematics and calculated joint torques while tapping on different keyswitches in different postures, and analyzed the data using mechanical impedance models.

METHODS

Sixteen human subjects tapped with the index finger on computer keyswitches mounted on a sensor which measured vertical and horizontal forces. Miniature electro-optical goniometers mounted dorsally across each finger joint measured joint kinematics. Joint torques were calculated from endpoint forces and joint kinematics using an inverse dynamics algorithm. A linear spring-damper impedance model was fitted to joint torque, position, and velocity during the contact period of each tap. Subjects tapped in three postures approximating those employed during tapping on three rows of a computer keyboard, on four different keyswitches, resulting in 12 conditions.

RESULTS

More extended finger posture was associated with greater joint torques, energies, and stiffnesses, despite minimal differences in endpoint forces across posture. Greater keyswitch make forces were associated with increased forces, joint torques and joint stiffnesses, however this relationship was not monotonic.

CONCLUSIONS

Joint torques and stiffness parameters differed across keyswitch designs and finger postures. Estimates of joint impedance and work provided a unique perspective into finger dynamics.

RELEVANCE

Determining the causes of work-related musculoskeletal disorders is facilitated by characterizing workplace task biomechanics, which can be linked to specific injury mechanisms.

Extrinsic flexor muscles generate concurrent flexion of all three finger joints

The role of the forearm (extrinsic) finger flexor muscles in initiating rotation of the metacarpophalangeal (MCP) joint and in coordinating flexion at the MCP, the proximal interphalangeal (PIP), and distal interphalangeal (DIP) joints remains a matter of some debate. To address the biomechanical feasibility of the extrinsic flexors performing these actions, a computer simulation of the index finger was created. The model consisted of a planar open-link chain comprised of three revolute joints and four links, driven by the change in length of the flexor muscles. Passive joint characteristics, included in the model, were obtained from system identification experiments involving the application of angular perturbations to the joint of interest. Simulation results reveal that in the absence of passive joint torque, shortening of the extrinsic flexors results in PIP flexion (80 degrees ), but DIP (8 degrees ) and MCP (7 degrees ) joint extension. The inclusion of normal physiological levels of passive joint torque, however, results in simultaneous flexion of all three joints (63 degrees for DIP, 75 degrees for PIP, and 43 degrees for MCP). Applicability of the simulation results was confirmed by recording finger motion produced by electrical stimulation of the extrinsic flexor muscles for the index finger. These findings support the view that the extrinsic flexor muscles can initiate MCP flexion, and produce simultaneous motion at the MCP, PIP, and DIP joints.