Quantitative analysis of finger motion coordination in hand manipulative and gestic acts

Morphological integration and shape covariation between the trapezium and first metacarpal among extant hominids

OBJECTIVES

The shape of the trapezium and first metacarpal (Mc1) markedly influence thumb mobility, strength, and the manual abilities of extant hominids. Previous research has typically focused solely on trapezium-Mc1 joint shape. Here we investigate how morphological integration and shape covariation between the entire trapezium (articular and non-articular surfaces) and the entire Mc1 reflect known differences in thumb use in extant hominids.

MATERIALS AND METHODS

We analyzed shape covariation in associated trapezia and Mc1s across a large, diverse sample of Homo sapiens (n = 40 individuals) and other extant hominids (Pan troglodytes, n = 16; Pan paniscus, n = 13; Gorilla gorilla gorilla, n = 27; Gorilla beringei, n = 6; Pongo pygmaeus, n = 14; Pongo abelii, n = 9) using a 3D geometric morphometric approach. We tested for interspecific significant differences in degree of morphological integration and patterns of shape covariation between the entire trapezium and Mc1, as well as within the trapezium-Mc1 joint specifically.

RESULTS

Significant morphological integration was only found in the trapezium-Mc1 joint of H. sapiens and G. g. gorilla. Each genus showed a specific pattern of shape covariation between the entire trapezium and Mc1 that was consistent with different intercarpal and carpometacarpal joint postures.

DISCUSSION

Our results are consistent with known differences in habitual thumb use, including a more abducted thumb during forceful precision grips in H. sapiens and a more adducted thumb in other hominids used for diverse grips. These results will help to infer thumb use in fossil hominins.

Finger Kinematics during Human Hand Grip and Release

A bionic robotic hand can perform many movements similar to a human hand. However, there is still a significant gap in manipulation between robot and human hands. It is necessary to understand the finger kinematics and motion patterns of human hands to improve the performance of robotic hands. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hands of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a larger dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Additionally, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by the PIP joint. Regarding the finger sequence, the thumb started to move before the four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided a kinematic reference for the design of robotic hands and thus contributes to its development.

Dribble Accuracy and Arm Coordination Pattern According to Motor Expertise and Tempo

Skilled movements in motor learning result from efficiently controlling the many degrees of freedom in human movement. To acquire motor skills, harmonious coordination of body segments in time and space is crucial for accurate and consistent performance. The purpose of this study was to compare dribbling accuracy, consistency, and coordination patterns of body segments according to motor expertise and tempo. To achieve this, we had eight basketball experts and eight beginners perform static dribbling at three different speeds for 20 s. Force plates measured radial error while motion capture equipment measured the angular data of the right arm's fingers, wrist, and elbow. The measurements obtained from the force plate were used to analyze the participants' dribbling performance, including accuracy, consistency, and coordination patterns. The research results showed that there was no significant difference in dribbling accuracy according to skill level, but skilled players showed higher consistency in the anterior-posterior (AP) direction (p < 0.001). In the comparative analysis of coordination patterns, skilled players showed an in-phase structure, whereas beginners showed an anti-phase structure (elbow-wrist: p < 0.05; wrist-finger: p < 0.001; elbow-finger: p < 0.001). This study suggests that achieving proficiency in basketball dribbling requires a strategy that involves coordination of movements with an in-phase pattern for stability in performance.

Humanlike spontaneous motion coordination of robotic fingers through spatial multi-input spike signal multiplexing

With advances in robotic technology, the complexity of control of robot has been increasing owing to fundamental signal bottlenecks and limited expressible logic state of the von Neumann architecture. Here, we demonstrate coordinated movement by a fully parallel-processable synaptic array with reduced control complexity. The synaptic array was fabricated by connecting eight ion-gel-based synaptic transistors to an ion gel dielectric. Parallel signal processing and multi-actuation control could be achieved by modulating the ionic movement. Through the integration of the synaptic array and a robotic hand, coordinated movement of the fingers was achieved with reduced control complexity by exploiting the advantages of parallel multiplexing and analog logic. The proposed synaptic control system provides considerable scope for the advancement of robotic control systems.

Development of a revolute-type kinematic model for human upper limb using a matrix approach

A mathematical model is proposed for a revolute joint mechanism with an n-degree of freedom (DOF). The matrix approach is used for finding the relation between two consecutive links to determine desired link parameters such as position, velocity and acceleration using the forward kinematic approach. The matrix approach was confirmed for a proposed 10 DOF revolute type (R-type) human upper limb model with servo motors at each joint. Two DOFs are considered each at shoulder, elbow and wrist joint, followed by four DOF for the fingers. Two DOFs were considered for metacarpophalangeal (mcp) and one DOF each for proximal interphalangeal (pip) and distal interphalangeal (dip) joints. MATLAB script function was used to evaluate the mathematical model for determining kinematic parameters for all the proposed human upper limb model joints. The simplified method for kinematic analysis proposed in this paper will further simplify the dynamic modeling of any mechanism for determining joint torques and hence, easy to design control system for joint movements.

Hand Kinematics Characterization While Performing Activities of Daily Living Through Kinematics Reduction

Improving the understanding of hand kinematics during the performance of activities of daily living may help improve the control of hand prostheses and hand function assessment. This work identifies sparse synergies (each degree of freedom is present mainly in only one synergy), representative of the global population, with emphasis in unveiling the coordination of joints with small range of motion (palmar arching and fingers abduction). The study is the most complete study described in the literature till now, involving 22 healthy subjects and 26 representative day-to-day life activities. Principal component analysis was used to reduce the original 16 angles recorded with an instrumented glove. Five synergies explained 75% of total variance: closeness (coordinated flexion and abduction of metacarpophalangeal finger joints), digit arching (flexion of proximal interphalangeal joints), palmar-thumb coordination (coordination of palmar arching and thumb carpometacarpal flexion), thumb opposition, and thumb arch. The temporal evolution of these synergies is provided during reaching per intended grasp and during manipulation per specific task, which could be used as normative patterns for the global population. Reaching has been observed to require the modulation of closeness, digit arch and thumb opposition synergies, with different control patterns per grasp. All the synergies are very important during manipulation and need to be modulated for all the tasks. Finally, groups of tasks with similar kinematic requirements in terms of synergies have been identified, which could benefit the selection of tasks for rehabilitation and hand function assessments.

Geometry-based finger kinematic models for joint rotation configuration and parameter estimation

In this work, geometry-based finger kinematic models for joint rotation configuration are proposed. The purpose of the work is to provide an effective means of describing an individual-specific finger motion during flexion or extension movements as precisely as possible. Based on the finger’s geometric postures that are observed when fingers naturally grasp a cylindrical object with a circular cross-section, its geometric relation between each phalanx of a finger and the object is extracted, and forms of contact between them are taken into consideration to secure more degrees of freedom for representing finger motions and are parameterized in the model development. A parameter identification approach is adopted to find model parameters that can be used to describe an individual-specific grasping style. For the validation of the proposed models, a set of optical motion capture experiments is performed. From the simulation study, one can see that the models provide one of the feasible and viable solutions to imitate the human finger’s flexion and/or extension movements.

Fully Wearable Actuated Soft Exoskeleton for Grasping Assistance in Everyday Activities

Worldwide, over 50 million people suffer from persistent hand impairments after stroke or spinal cord injury (SCI). This results in major loss of independence and quality of life. Robotic hand exoskeletons can compensate for lost motor function and assist in grasping tasks performed in everyday activities. Several recent prototypes can partially provide this assistance. However, it remains challenging to integrate the dexterity required for daily tasks in a safe and user-friendly design that is acceptable for daily use in subjects with neuromotor hand impairments. We present the design of RELab tenoexo; a fully wearable assistive soft hand exoskeleton for daily activities. We present sleek mechanisms for a hand module that generates the four most frequently used grasp types, employing a remote actuation system that reduces weight on the hand. For optimal assistance and highest adaptability, we present various design and control options to customize the modular device, along with an automated tailoring algorithm that allows automatically generated hand modules for individual users. Mechanical evaluation shows that RELab tenoexo covers the range of motion and the fingertip forces required to assist users in up to 80% of all grasping activities. In user tests, we find that the low weight, unintrusive size, high wearing comfort, and appealing appearance are beneficial for user acceptance and usability in daily life. Finally, we demonstrate that RELab tenoexo leads to an immediate improvement of the functional grasping ability in a subject with SCI.

On Primitives in Motor Control

The concept of primitives has been used in motor control both as a theoretical construct and as a means of describing the results of experimental studies involving multiple moving elements. This concept is close to Bernstein’s notion of engrams and level of synergies. Performance primitives have been explored in spaces of peripheral variables but interpreted in terms of neural control primitives. Performance primitives reflect a variety of mechanisms ranging from body mechanics to spinal mechanisms and to supraspinal circuitry. This review suggests that primitives originate at the task level as preferred time functions of spatial referent coordinates or at mappings from higher level referent coordinates to lower level, frequently abundant, referent coordinate sets. Different patterns of performance primitives can emerge depending, in particular, on the external force field.

Reorganization of finger covariation patterns represented in the corticospinal system by learning of a novel movement irrelevant to common daily movements

How dexterous finger movements are acquired by the nervous system is a fundamental question in the neuroscience field. Previous studies have demonstrated that finger movements can be decomposed into finger covariation patterns, and these patterns are represented in the corticospinal system. However, it remains unclear how such covariation patterns represented in the corticospinal system develop during the acquisition of novel finger movements. In this study, each subject learned to perform a novel finger movement, which was mapped to a region outside the movement subspace spanned by common finger movements seen in daily life, through a custom task. After subjects practiced the task, we detected changes in the finger covariation patterns derived from artificially (transcranial magnetic stimulation) evoked finger joint movements. The artificially evoked movement-derived patterns seen after the training period were associated with both the novel and common finger movements. Regarding the patterns extracted from the artificially evoked movements, the number required to explain most of the variance in the data was unchanged after the training period. Our results indicate that novel finger movements are acquired through the reorganization of preexisting finger covariation patterns represented in the corticospinal system rather than the development of new patterns. These findings might have implications for the basic mechanism responsible for the development of movement repertories in the nervous system.NEW & NOTEWORTHY Various types of finger movements involve common finger covariation patterns, and these patterns are represented in the corticospinal system. Here we examined how a novel finger covariation pattern is acquired in that system through training of a novel finger movement that is irrelevant to common finger movements. Using transcranial magnetic stimulation, we found that the preexisting patterns that contribute to finer control of finger movements are rapidly reorganized to encode the novel pattern through the training.

Kinematic synergies of hand grasps: a comprehensive study on a large publicly available dataset

Background

Hand grasp patterns require complex coordination. The reduction of the kinematic dimensionality is a key process to study the patterns underlying hand usage and grasping. It allows to define metrics for motor assessment and rehabilitation, to develop assistive devices and prosthesis control methods. Several studies were presented in this field but most of them targeted a limited number of subjects, they focused on postures rather than entire grasping movements and they did not perform separate analysis for the tasks and subjects, which can limit the impact on rehabilitation and assistive applications. This paper provides a comprehensive mapping of synergies from hand grasps targeting activities of daily living. It clarifies several current limits of the field and fosters the development of applications in rehabilitation and assistive robotics.

Methods

In this work, hand kinematic data of 77 subjects, performing up to 20 hand grasps, were acquired with a data glove (a 22-sensor CyberGlove II data glove) and analyzed. Principal Component Analysis (PCA) and hierarchical cluster analysis were used to extract and group kinematic synergies that summarize the coordination patterns available for hand grasps.

Results

Twelve synergies were found to account for > 80% of the overall variation. The first three synergies accounted for more than 50% of the total amount of variance and consisted of: the flexion and adduction of the Metacarpophalangeal joint (MCP) of fingers 3 to 5 (synergy #1), palmar arching and flexion of the wrist (synergy #2) and opposition of the thumb (synergy #3). Further synergies refine movements and have higher variability among subjects.

Conclusion

Kinematic synergies are extracted from a large number of subjects (77) and grasps related to activities of daily living (20). The number of motor modules required to perform the motor tasks is higher than what previously described. Twelve synergies are responsible for most of the variation in hand grasping. The first three are used as primary synergies, while the remaining ones target finer movements (e.g. independence of thumb and index finger). The results generalize the description of hand kinematics, better clarifying several limits of the field and fostering the development of applications in rehabilitation and assistive robotics.

Measurement of Flexion Angle of the Finger Joint during Cylinder Gripping Using a Three-Dimensional Bone Model Built by X-Ray Computed Tomography

Motion analysis of the thumb and the four fingers during human gripping of a cylindrical object is a prerequisite for designing motion mechanisms in electronic arm prostheses and robotic hands. Conventional measurement methods include the use of angle sensors or multiple video recording of markers. In the present study, we performed X-ray computed tomography (CT) imaging on fingers gripping cylinders of three different diameters (10, 60, and 120 mm) and constructed a bone model based on these CT images to directly measure the flexion angle of each finger joint. We then compared the results with the flexion angles of joints measured using other methods. The subjects comprised 10 Japanese men with no hand injuries or diseases. Our results showed that smaller cylinder diameters were associated with significant increases in the flexion angle of all the joints of the four fingers. When focusing on the distal interphalangeal joint (DIP), there was no significant difference between any of the fingers for each of the cylinders, except between the index and middle fingers for the 10 mm-diameter cylinder. When focusing on the 10 mm-diameter cylinder, the flexion angle of the proximal interphalangeal joint (PIP) of each finger was significantly larger than that of the DIP and metacarpophalangeal joint (MP). However, no such significant difference was noted for the 120 mm-diameter cylinder. The coupling ratio (CR), which is the ratio of the flexion angles of the DIP and PIP, was significantly smaller for the 10 mm-diameter cylinder than for the 60 mm-diameter cylinder. However, there were no significant differences in CR between any of the fingers. A comparison of our study results with those derived using other methods indicated quantitative consistency for the DIP and PIP. However, for the MP, we noted differences that may be explained by the difficulty in determining the longitudinal axis of the metacarpal using other methods.

Towards Finger Motion Capture System Using FBG Sensors

This paper introduces a novel finger motion capture system using FBG (fiber Bragg grating) optical sensors. We develop two types of sensors to seamlessly reconstruct finger motion from strains induced in the FBGs. First, the shape sensor incorporates three optical fibers with multiple FBGs to reconstruct the position and orientation of a finger joint in 3D. In addition, the angle sensor is designed to measure the high curvature of bending on the finger joints. By deploying the two types of sensors on the fingers, we can reconstruct various finger motion in real time without drift over time. The accuracies of the fabricated FBG sensors are evaluated, resulting in an average error of 1.49 mm for the shape sensor at the distal tip (1.9% for the full length of the sensor) and 0.21° error for the angle sensor. We finally demonstrate finger motion tracking with the FBG sensors in real time, while measuring the multi-DOF motion at the carpometacarpal joint of the thumb and also the high curvatures of bending motion at the metacarpophalangeal and interphalangeal joints of the thumb and the index finger.

A novel experimental design for the measurement of metacarpal bone loading and deformation and fingertip force

Background

Musculoskeletal and finite element modelling are often used to predict joint loading and bone strength within the human hand, but there is a lack of in vitro evidence of the force and strain experienced by hand bones.

Methods

This study presents a novel experimental setup that allows the positioning of a cadaveric digit in a variety of postures with the measurement of force and strain experienced by the third metacarpal. The setup allows for the measurement of fingertip force as well. We tested this experimental setup using three cadaveric human third digits in which the flexor tendons were loaded in two tendon pathways: (1) parallel to the metacarpal bone shaft, with bowstringing; (2) a semi-physiological condition in which the tendons were positioned closer to the bone shaft.

Results

There is substantial variation in metacarpal net force, metacarpal strain and fingertip force between the two tendon pathways. The net force acting on the metacarpal bone is oriented palmarly in the parallel tendon condition, causing tension along the dorsum of the metacarpal shaft, while the force increases and is oriented dorsally in the semi-physiological condition, causing compression of the dorsal metacarpal shaft. Fingertip force is also greater in the semi-physiological condition, implying a more efficient grip function. Inter-individual variation is observed in the radioulnar orientation of the force experienced by the metacarpal bone, the fingertip force, and the strain patterns on the metacarpal shaft.

Conclusion

This study demonstrates a new method for measuring force and strain experienced by the metacarpal, and fingertip force in cadaveric digits that can, in turn, inform computation models. Inter-individual variation in loads experienced by the third digit suggest that there are differences in joint contact and/or internal bone structure across individuals that are important to consider in clinical and evolutionary contexts.

Assessing Wrist Movement With Robotic Devices

Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor function after neurological injury. Complementing this application, exoskeletons can augment traditional clinical assessments through precise, repeatable measurements of joint angles and movement quality. These measures assume that exoskeletons are making accurate joint measurements with a negligible effect on movement. For the coupled and coordinated joints of the wrist and hand, the validity of these two assumptions cannot be established by characterizing the device in isolation. To examine these assumptions, we conducted three user-in-the-loop experiments with able-bodied participants. First, we compared robotic measurements to an accepted modality to determine the validity of joint- and trajectory-level measurements. Then, we compared those movements to movements without the device to investigate the effects of device dynamic properties on wrist movement characteristics. Last, we investigated the effect of the device on coordination with a redundant, coordinated pointing task with the wrist and hand. For all experiments, smoothness characteristics were preserved in the robotic kinematic measurement and only marginally impacted by robot dynamics, validating the exoskeletons for use as assessment devices. Stemming from these results, we propose design guidelines for exoskeletal assessment devices.

Differences in EMG Burst Patterns During Grasping Dexterity Tests and Activities of Daily Living

The aim of this study was to characterize the muscle activation patterns which underlie the performance of two commonly used grasping patterns and compare the characteristics of such patterns during dexterity tests and activities of daily living. EMG of flexor digitorum and extensor digitorum were monitored from 6 healthy participants as they performed three tasks related to activities of daily living (picking up a coin, drinking from a cup, feeding with a spoon) and three dexterity tests (Variable Dexterity Test-Precision, Variable Dexterity Test-Cylinder, Purdue Pegboard Test). A ten-camera motion capture system was used to simultaneously acquire kinematics of index and middle fingers. Spatiotemporal aspects of the EMG signals were analyzed and compared to metacarpophalangeal joint angle of index and middle fingers. The work has shown that a common rehabilitation test such as the Purdue Pegboard test is a poor representation of the muscle activation patterns for activities of daily living. EMG and joint angle patterns from the Variable Dexterity Tests which has been designed to more accurately reflect a range of ADl's were consistently comparable with tasks requiring precision and cylinder grip, reaffirming the importance of object size and shape when attempting to accurately assess hand function.

Sub-millimetre accurate human hand kinematics: from surface to skeleton

A highly accurate human hand kinematics model and identification are proposed. The model includes the five digits and the palm arc based on mapping function between surface landmarks and estimated joint centres of rotation. Model identification was experimentally performed using a motion tracking system. The evaluation of the marker position estimation error, which is on sub-millimetre level across all digits, underlines model quality and accuracy. Noticeably, with the development of this model, we were able to improve various modelling assumptions from literature and found a basic linear relationship between surface and skeleton rotational angles.

An overview of robotic/mechanical devices for post-stroke thumb rehabilitation

PURPOSE

This article aims to clarify the current state-of-the-art of robotic/mechanical devices for post-stroke thumb rehabilitation as well as the anatomical characteristics and motions of the thumb that are crucial for the development of any device that aims to support its motion.

METHODS

A systematic literature search was conducted to identify robotic/mechanical devices for post-stroke thumb rehabilitation. Specific electronic databases and well-defined search terms and inclusion/exclusion criteria were used for such purpose. A reasoning model was devised to support the structured abstraction of relevant data from the literature of interest.

RESULTS

Following the main search and after removing duplicated and other non-relevant studies, 68 articles (corresponding to 32 devices) were left for further examination. These articles were analyzed to extract data relative to (i) the motions assisted/permitted - either actively or passively - by the device per anatomical joint of the thumb and (ii) mechanical-related aspects (i.e., architecture, connections to thumb, other fingers supported, adjustability to different hand sizes, actuators - type, quantity, location, power transmission and motion trajectory).

CONCLUSIONS

Most articles describe preliminary design and testing of prototypes, rather than the thorough evaluation of commercially ready devices. Defining appropriate kinematic models of the thumb upon which to design such devices still remains a challenging and unresolved task. Further research is needed before these devices can actually be implemented in clinical environments to serve their intended purpose of complementing the labour of therapists by facilitating intensive treatment with precise and repeatable exercises. Implications for Rehabilitation Post-stroke functional disability of the hand, and particularly of the thumb, significantly affects the capability to perform activities of daily living, threatening the independence and quality of life of the stroke survivors. The latest studies show that a high-dose intensive therapy (in terms of frequency, duration and intensity/effort) is the key to effectively modify neural organization and recover the motor skills that were lost after a stroke. Conventional therapy based on manual interaction with physical therapists makes the procedure labour intensive and increases the costs. Robotic/mechanical devices hold promise for complementing conventional post-stroke therapy. Specifically, these devices can provide reliable and accurate therapy for long periods of time without the associated fatigue. Also, they can be used as a means to assess patients? performance and progress in an objective and consistent manner. The full potential of robot-assisted therapy is still to be unveiled. Further exploration will surely lead to devices that can be well accepted equally by therapists and patients and that can be useful both in clinical and home-based rehabilitation practice such that motor recovery of the hand becomes a common outcome in stroke survivors. This overview provides the reader, possibly a designer of such a device, with a complete overview of the state-of-the-art of robotic/mechanical devices consisting of or including features for the rehabilitation of the thumb. Also, we clarify the anatomical characteristics and motions of the thumb that are crucial for the development of any device that aims to support its motion. Hopefully, this?combined with the outlined opportunities for further research?leads to the improvement of current devices and the development of new technology and knowledge in the field.

Analyzing finger interdependencies during the Purdue Pegboard Test and comparative activities of daily living

STUDY DESIGN

Bench and cross-sectional study.

INTRODUCTION

Information obtained from dexterity tests is an important component of a comprehensive examination of the hand.

PURPOSE OF THE STUDY

To analyze and compare finger interdependencies during the performance of the Purdue Pegboard Test (PBT) and comparative daily tasks.

METHODS

A method based on the optoelectronic kinematic analysis of the precision grip style and on the calculation of cross-correlation coefficients between relevant joint angles, which provided measures of the degree of finger coordination, was conducted on 10 healthy participants performing the PBT and 2 comparative daily living tasks.

RESULTS

Daily tasks showed identifiable interdependencies patterns between the metacarpophalangeal joints of the fingers involved in the grip. Tasks related to activities of daily living resulted in significantly higher cross-correlation coefficients across subjects and movements during the formation and manipulation phases of the tasks (0.7-0.9), whereas the release stage produced significantly lower movement correlation values (0.3-0.7). Contrarily, the formation and manipulation stages of the PBT showed low finger correlation across most subjects (0.2-0.6), whereas the release stage resulted in the highest values for all relevant movements (0.65-0.9).

DISCUSSION

Interdependencies patterns were consistent for the activities of daily living but differ from the patterns observed from the PBT.

CONCLUSIONS

The PBT does not compare well with the whole range of finger movements that account for hand performance during daily tasks.

LEVEL OF EVIDENCE

Not applicable.

Change in the temporal coordination of the finger joints with ulnar nerve block during different power grips analyzed with a sensor glove

Ulnar nerve injuries can cause deficient hand movement patterns. Their assessment is important for diagnosis and rehabilitation in hand surgery cases. The purpose of this study was to quantify the changes in temporal coordination of the finger joints during different power grips with an ulnar nerve block by means of a sensor glove. In 21 healthy subjects, the onset and end of the active flexion of the 14 finger joints when gripping objects of different diameters was recorded by a sensor glove. The measurement was repeated after an ulnar nerve block was applied in a standardized setting. The change in the temporal coordination of the metacarpophalangeal (MCP), proximal interphalangeal (PIP) and distal interphalangeal (DIP) joints with and without the nerve block was calculated within the same subject. In healthy subjects, the MCP joints started their movement prior to the PIP joints in the middle and ring finger, whereas this occurred in the reverse order at the index and little finger. The DIP joint onset was significantly delayed (P<0.01). With the ulnar nerve block, this coordination shifted towards simultaneous onset of all joints, independent of the grip diameter. The thumb and index finger were affected the least. With an ulnar nerve block, the PIP joints completed their movement prior to the MCP joints when gripping small objects (G1 and G2), whereas the order was reversed with larger objects (G3 and G4). The alterations with ulnar nerve block affected mainly the little finger when gripping small objects. With larger diameter objects, all fingers had a significant delay at the end of the PIP joint movement relative to the MCP and DIP joints, and the PIP and DIP joint sequence was reversed (P<0.01). Based on the significant changes in temporal coordination of finger flexion during different power grips, there are biomechanical effects of loss of function of the intrinsic muscles caused by an ulnar nerve block on the fine motor skills of the hand. This can be important for the diagnosis and rehabilitation of ulnar nerve lesions of the hand.

Optimal motor synergy extraction for novel actions and virtual environments

Dimensionality reduction techniques such as factor analysis can be used to identify the smallest number of components (motor synergies) that explain motion. Lambert-Shirzad and Van der Loos (J Neurophysiol 117: 290-302, 2017) compared dimensionality reduction techniques in bimanual hand movements, concluding that nonnegative matrix factorization was the optimal technique for extracting meaningful synergies. Their results provide a useful measure for examining how the motor system deals with novel motor tasks that allow the actor to engage with a virtual environment.

Data sample size needed for analysis of kinematic and muscle synergies in healthy and stroke populations

Multiple studies have suggested the central nervous system (CNS) generates motions by using modular control of muscles and joints (synergies). However, the synergies reported by these studies are task dependent and might not reflect the true control strategies adopted by the CNS. Studying exploratory motions (EMs) can reveal biomechanical constraints and motor control strategies in healthy and clinical populations. The first logical step to consider EMs in study of motor synergies is to determine how much data is required to reliably and fully profile the motion patterns of an individual. Here we present how the quality of motor synergies analysis depends on the amount of EM data included in the analysis. We recruited 10 healthy and 10 post-stroke participants and collected electromyography (EMG) and joint motion data of their arms as they completed a motor exploration task. We compared the effects of clinical status and limb strength/dominance on the amount of data required to identify synergies. Clinical status had a significant elïect on the required amount of data for both datasets. Limb strength had a significant effect only for kinematic data. We determined the upper bound 95% confidence interval to set the amount of data required for synergy analysis in both populations: 235 sec for EMG data and 265 sec for kinematic data. Our results provide an important step toward using motor exploration in the study of healthy motor synergies and how stroke alters them.

Anticipatory postural adjustments and anticipatory synergy adjustments: preparing to a postural perturbation with predictable and unpredictable direction

We explored two aspects of feed-forward postural control, anticipatory postural adjustments (APAs) and anticipatory synergy adjustments (ASAs) seen prior to self-triggered unloading with known and unknown direction of the perturbation. In particular, we tested two main hypotheses predicting contrasting changes in APAs and ASAs. The first hypothesis predicted no major changes in ASAs. The second hypothesis predicted delayed APAs with predominance of co-contraction patterns when perturbation direction was unknown. Healthy subjects stood on the force plate and held a bar with two loads acting in the forward and backward directions. They pressed a trigger that released one of the loads causing a postural perturbation. In different series, the direction of the perturbation was either known (the same load released in all trials) or unknown (the subjects did not know which of the two loads would be released). Surface electromyograms were recorded and used to quantify APAs, synergies stabilizing center of pressure coordinate (within the uncontrolled manifold hypothesis), and ASA. APAs and ASAs were seen in all conditions. APAs were delayed, and predominance of co-contraction patterns was seen under the conditions with unpredictable direction of perturbation. In contrast, no significant changes in synergies and ASAs were seen. Overall, these results show that feed-forward control of vertical posture has two distinct components, reflected in APAs and ASAs, which show qualitatively different adjustments with changes in predictability of the direction of perturbation. These results are interpreted within the recently proposed hierarchical scheme of the synergic control of motor tasks. The observations underscore the complexity of the feed-forward postural control, which involves separate changes in salient performance variables (such as coordinate of the center of pressure) and in their stability properties.

On identifying kinematic and muscle synergies: a comparison of matrix factorization methods using experimental data from the healthy population

Human motor behavior is highly goal directed, requiring the central nervous system to coordinate different aspects of motion generation to achieve the motion goals. The concept of motor synergies provides an approach to quantify the covariation of joint motions and of muscle activations, i.e., elemental variables, during a task. To analyze goal-directed movements, factorization methods can be used to reduce the high dimensionality of these variables while accounting for much of the variance in large data sets. Three factorization methods considered in this paper are principal component analysis (PCA), nonnegative matrix factorization (NNMF), and independent component analysis (ICA). Bilateral human reaching data sets are used to compare the methods, and advantages of each are presented and discussed. PCA and NNMF had a comparable performance on both EMG and joint motion data and both outperformed ICA. However, NNMF's nonnegativity condition for activation of basis vectors is a useful attribute in identifying physiologically meaningful synergies, making it a more appealing method for future studies. A simulated data set is introduced to clarify the approaches and interpretation of the synergy structures returned by the three factorization methods.

NEW & NOTEWORTHY

Literature on comparing factorization methods in identifying motor synergies using numerically generated, simulation, and muscle activation data from animal studies already exists. We present an empirical evaluation of the performance of three of these methods on muscle activation and joint angles data from human reaching motion: principal component analysis, nonnegative matrix factorization, and independent component analysis. Using numerical simulation, we also studied the meaning and differences in the synergy structures returned by each method. The results can be used to unify approaches in identifying and interpreting motor synergies.

Using subject-specific three-dimensional (3D) anthropometry data in digital human modelling: case study in hand motion simulation

Digital human modelling enables ergonomists and designers to consider ergonomic concerns and design alternatives in a timely and cost-efficient manner in the early stages of design. However, the reliability of the simulation could be limited due to the percentile-based approach used in constructing the digital human model. To enhance the accuracy of the size and shape of the models, we proposed a framework to generate digital human models using three-dimensional (3D) anthropometric data. The 3D scan data from specific subjects' hands were segmented based on the estimated centres of rotation. The segments were then driven in forward kinematics to perform several functional postures. The constructed hand models were then verified, thereby validating the feasibility of the framework. The proposed framework helps generate accurate subject-specific digital human models, which can be utilised to guide product design and workspace arrangement. Practitioner Summary: Subject-specific digital human models can be constructed under the proposed framework based on three-dimensional (3D) anthropometry. This approach enables more reliable digital human simulation to guide product design and workspace arrangement.

Behavioral and functional strategies during tool use tasks in bonobos

Different primate species have developed extensive capacities for grasping and manipulating objects. However, the manual abilities of primates remain poorly known from a dynamic point of view. The aim of the present study was to quantify the functional and behavioral strategies used by captive bonobos (Pan paniscus) during tool use tasks. The study was conducted on eight captive bonobos which we observed during two tool use tasks: food extraction from a large piece of wood and food recovery from a maze. We focused on grasping postures, in-hand movements, the sequences of grasp postures used that have not been studied in bonobos, and the kind of tools selected. Bonobos used a great variety of grasping postures during both tool use tasks. They were capable of in-hand movement, demonstrated complex sequences of contacts, and showed more dynamic manipulation during the maze task than during the extraction task. They arrived on the location of the task with the tool already modified and used different kinds of tools according to the task. We also observed individual manual strategies. Bonobos were thus able to develop in-hand movements similar to humans and chimpanzees, demonstrated dynamic manipulation, and they responded to task constraints by selecting and modifying tools appropriately, usually before they started the tasks. These results show the necessity to quantify object manipulation in different species to better understand their real manual specificities, which is essential to reconstruct the evolution of primate manual abilities.

Interdependency of the maximum range of flexion-extension of hand metacarpophalangeal joints

Mobility of the fingers metacarpophalangeal (MCP) joints depends on the posture of the adjacent ones. Current Biomechanical hand models consider fixed ranges of movement at joints, regardless of the posture, thus allowing for non-realistic postures, generating wrong results in reach studies and forward dynamic analyses. This study provides data for more realistic hand models. The maximum voluntary extension (MVE) and flexion (MVF) of different combinations of MCP joints were measured covering their range of motion. Dependency of the MVF and MVE on the posture of the adjacent MCP joints was confirmed and mathematical models obtained through regression analyses (RMSE 7.7°).

A cortically-inspired model for inverse kinematics computation of a humanoid finger with mechanically coupled joints

The human hand's versatility allows for robust and flexible grasping. To obtain such efficiency, many robotic hands include human biomechanical features such as fingers having their two last joints mechanically coupled. Although such coupling enables human-like grasping, controlling the inverse kinematics of such mechanical systems is challenging. Here we propose a cortical model for fine motor control of a humanoid finger, having its two last joints coupled, that learns the inverse kinematics of the effector. This neural model functionally mimics the population vector coding as well as sensorimotor prediction processes of the brain's motor/premotor and parietal regions, respectively. After learning, this neural architecture could both overtly (actual execution) and covertly (mental execution or motor imagery) perform accurate, robust and flexible finger movements while reproducing the main human finger kinematic states. This work contributes to developing neuro-mimetic controllers for dexterous humanoid robotic/prosthetic upper-extremities, and has the potential to promote human-robot interactions.

Biomechanical Characteristics of Hand Coordination in Grasping Activities of Daily Living

Hand coordination can allow humans to have dexterous control with many degrees of freedom to perform various tasks in daily living. An important contributing factor to this important ability is the complex biomechanical architecture of the human hand. However, drawing a clear functional link between biomechanical architecture and hand coordination is challenging. It is not understood which biomechanical characteristics are responsible for hand coordination and what specific effect each biomechanical characteristic has. To explore this link, we first inspected the characteristics of hand coordination during daily tasks through a statistical analysis of the kinematic data, which were collected from thirty right-handed subjects during a multitude of grasping tasks. Then, the functional link between biomechanical architecture and hand coordination was drawn by establishing the clear corresponding causality between the tendinous connective characteristics of the human hand and the coordinated characteristics during daily grasping activities. The explicit functional link indicates that the biomechanical characteristic of tendinous connective architecture between muscles and articulations is the proper design by the Creator to perform a multitude of daily tasks in a comfortable way. The clear link between the structure and the function of the human hand also suggests that the design of a multifunctional robotic hand should be able to better imitate such basic architecture.

Joint angles and angular velocities and relevance of eigenvectors during prehension in the monkey

Hand shaping during prehension involves intricate coordination of a complex system of bones, joints, and muscles. It is widely hypothesized that the motor system uses strategies to reduce the degrees of independent control. Both biomechanical constraints that result in coupling of the fingers and joints and neural synergies act to simplify the control problem. Synergies in hand shaping are typically defined using principal component-like analyses to define orthogonal patterns of movement. Although much less examined, joint angle velocities are also important parameters governing prehension. The primary goal of this study was to evaluate joint angles and joint angle velocities during prehension in monkeys. Fourteen joint angles and angular velocities were measured as monkeys reached to and grasped a set of objects designed to systematically vary hand shapes. Hand shaping patterns in joint angles and velocities were examined using singular value decomposition (SVD). Highly correlated patterns of movements were observed in both joint angles and joint angle velocities, but there was little correlation between the two, suggesting that velocities are controlled separately. Joint angles and velocities can be defined by a small number of eigenvectors by SVD. The unresolved question of the functional relevance of higher-order eigenvectors was also evaluated. Results support that higher-order components are not easily distinguished from noise and are likely not of physiological significance.

Analysis of relative displacement between the HX wearable robotic exoskeleton and the user's hand

Background

Advances in technology are allowing for the production of several viable wearable robotic devices to assist with activities of daily living and with rehabilitation. One of the most pressing limitations to user satisfaction is the lack of consistency in motion between the user and the robotic device. The displacement between the robot and the body segment may not correspond because of differences in skin and tissue compliance, mechanical backlash, and/or incorrect fit.

Findings

This report presents the results of an analysis of relative displacement between the user’s hand and a wearable exoskeleton, the HX. HX has been designed to maximize comfort, wearability and user safety, exploiting chains with multiple degrees-of-freedom with a modular architecture. These appealing features may introduce several uncertainties in the kinematic performances, especially when considering the anthropometry, morphology and degree of mobility of the human hand. The small relative displacements between the hand and the exoskeleton were measured with a video-based motion capture system, while the user executed several different grips in different exoskeleton modes.

Conclusions

The analysis furnished quantitative results about the device performance, differentiated among device modules and test conditions. In general, the global relative displacement for the distal part of the device was in the range 0.5–1.5 mm, while within 3 mm (worse but still acceptable) for displacements nearest to the hand dorsum. Conclusions over the HX design principles have been drawn, as well as guidelines for future developments.

Electronic supplementary material

The online version of this article (doi:10.1186/1743-0003-11-147) contains supplementary material, which is available to authorized users.

Integration of marker and force data to compute three-dimensional joint moments of the thumb and index finger digits during pinch

This study presents methodology to determine joint moments of the digits of the hand during pinch function. This methodology incorporates steps to identify marker-based kinematic data defining aligned coordinate systems for individual digit segments and joint centre locations. The kinematic data are then transformed to a common reference frame along with the force data collected at pinch contact of a customised apparatus in three dimensions. These methods were demonstrated with a pilot investigation to examine the static joint moments occurring during two-digit oppositional precision pinch at a particular end point force level applied at the digit pads. Notable abduction joint moments at the proximal joints of both digits were observed, which implicate the role of respective intrinsic and extrinsic muscles in maintaining pinch grasp. Examining differences in joint moment results when substituting selected steps of this methodological approach suggested greater relative importance for joint centre identification and segment coordinate system alignment.

Identification of three movement phases of the hand during lateral and pulp pinches using video motion capture

BACKGROUND

Hand injuries affect a person's ability to engage successfully in activities of daily living (ADLs). Video motion capture (VMC) facilitates measurement of dynamic movement. No study to date has used VMC as a means of quantifying the simultaneous movement patterns of all joints of all digits of the hand during active purposeful movement.

METHOD

The purpose of this study was to analyze all joints of all five digits during active completion of the lateral and pulp pinches. VMC data were collected from four participants during completion of two pinches. Joint angles were plotted to facilitate identification of movement patterns.

RESULTS

Range of motion recorded in all joints with VMC, excluding flexion of the thumb carpometacarpal of both pinches, coincided with the normative goniometric data. Three phases were observed: initiation, preshaping, and pinch phases. Patterns of movement in all digits were identified for the two pinches.

CONCLUSION

VMC is a feasible and valid method for objectively quantifying dynamic movement of multiple joints simultaneously. The results provide new insight to the dynamics of hand movement as well as a basis for subsequent evaluations of movement patterns performed in ADLs and instrumental ADLs.

Neural bases of hand synergies

The human hand has so many degrees of freedom that it may seem impossible to control. A potential solution to this problem is “synergy control” which combines dimensionality reduction with great flexibility. With applicability to a wide range of tasks, this has become a very popular concept. In this review, we describe the evolution of the modern concept using studies of kinematic and force synergies in human hand control, neurophysiology of cortical and spinal neurons, and electromyographic (EMG) activity of hand muscles. We go beyond the often purely descriptive usage of synergy by reviewing the organization of the underlying neuronal circuitry in order to propose mechanistic explanations for various observed synergy phenomena. Finally, we propose a theoretical framework to reconcile important and still debated concepts such as the definitions of “fixed” vs. “flexible” synergies and mechanisms underlying the combination of synergies for hand control.

The force synergy of human digits in static and dynamic cylindrical grasps

This study explores the force synergy of human digits in both static and dynamic cylindrical grasping conditions. The patterns of digit force distribution, error compensation, and the relationships among digit forces are examined to quantify the synergetic patterns and coordination of multi-finger movements. This study recruited 24 healthy participants to perform cylindrical grasps using a glass simulator under normal grasping and one-finger restricted conditions. Parameters such as the grasping force, patterns of digit force distribution, and the force coefficient of variation are determined. Correlation coefficients and principal component analysis (PCA) are used to estimate the synergy strength under the dynamic grasping condition. Specific distribution patterns of digit forces are identified for various conditions. The compensation of adjacent fingers for the force in the normal direction of an absent finger agrees with the principle of error compensation. For digit forces in anti-gravity directions, the distribution patterns vary significantly by participant. The forces exerted by the thumb are closely related to those exerted by other fingers under all conditions. The index-middle and middle-ring finger pairs demonstrate a significant relationship. The PCA results show that the normal forces of digits are highly coordinated. This study reveals that normal force synergy exists under both static and dynamic cylindrical grasping conditions.

Dynamic aspects during the cylinder grip--flexion sequence of the finger joints analyzed using a sensor glove

The purpose of this study was to assess whether there is a universal pattern of movement of the finger joints while performing a cylinder grip. A sensor glove was used to record the finger joint motion of 48 participants. Our observations showed that when examining the fingers, flexion motion began either at the metacarpophalangeal (MP) or proximal interphalangeal (PIP) joints, with the distal interphalangeal (DIP) joints always last to move (p = 0.0052). The sequence of the joints at the end of the gripping motion was different than at the beginning. Here, the only statistically significant observation was that the DIP joints fully flexed only once the MP joints had flexed fully. Apart from that, it was completely variable which joint reached its final position first or last. The analysis also revealed that synchronization of four identical joints (i.e. the four PIP joints) was significantly higher than synchronization of the 12 finger joints. Although synchronization was already high at the beginning of the flexion motion, it increased significantly by the time the joints completed their movement.

A digit alignment device for kinematic analysis of the thumb and index finger

Kinematic analysis of the digits using optical motion capture systems relies on defining accurate coordinate systems for the individual segments. Limitations of previous digit kinematic protocols include marker placement errors, marker occlusion and superimposition, and skin movement artifact. The purpose of this study was to develop a protocol utilizing a digit alignment device (DAD) and nail marker clusters to overcome these limitations. Ten subjects underwent 10 static calibration trials for validation. The orientation of the thumb distal phalange relative to the index finger distal phalange was described using Euler angles of pitch(x), yaw(y'), and roll(z''). The digit calibration protocol demonstrated high accuracy (0.5°, 1.9° and 2.2° for x, y', z'') and precision (1.4°, 2.3° and 3.1° for x, y', z''). The developed protocol provided convenient identification of transformations that determine anatomically relevant coordinate systems for the distal phalanges of the digits. The potential of utilizing this protocol as a standardized tool for digit kinematics was demonstrated using a dynamic task of precision pinching.

Multi-finger coordination in healthy subjects and stroke patients: a mathematical modelling approach

Background

Approximately 60% of stroke survivors experience hand dysfunction limiting execution of daily activities. Several methods have been proposed to objectively quantify fingers' joints range of motion (ROM), while few studies exist about multi-finger coordination during hand movements. The present work analysed this aspect, by providing a complete characterization of spatial and temporal aspects of hand movement, through the mathematical modelling of multi-joint finger motion in healthy subjects and stroke patients.

Methods

Hand opening and closing movements were examined in 12 healthy volunteers and 14 hemiplegic stroke survivors by means of optoelectronic kinematic analysis. The flexion/extension angles of metacarpophalangeal (MCPJ) and proximal interphalangeal joints (IPJ) of all fingers were computed and mathematically characterized by a four-parameter hyperbolic tangent function. Accuracy of the selected model was analysed by means of coefficient of determination (R²) and root mean square error (RMSE). Test-retest reliability was quantified by intraclass correlation coefficient (ICC) and test-retest errors. Comparison between performances of healthy controls and stroke subjects were performed by analysing possible differences in parameters describing angular and temporal aspects of hand kinematics and inter-joint, inter-digit coordination.

Results

The angular profiles of hand opening and closing were accurately characterized by the selected model, both in healthy controls and in stroke subjects (R² > 0.973, RMSE < 2.0°). Test-retest reliability was found to be excellent, with ICC > 0.75 and remarking errors comparable to those obtained with other methods. Comparison with healthy controls revealed that hemiparetic hand movement was impaired not only in joints ROM but also in the temporal aspects of motion: peak velocities were significantly decreased, inter-digit coordination was reduced of more than 50% and inter-joint coordination patterns were highly disrupted. In particular, the stereotypical proximal-to-distal opening sequence (reversed during hand closing) found in healthy subjects, was altered in stroke subjects who showed abnormally high delay between IPJ and MCPJ movement or reversed moving sequences.

Conclusions

The proposed method has proven to be a promising tool for a complete objective characterization of spatial and temporal aspects of hand movement in stroke, providing further information for a more targeted planning of the rehabilitation treatment to each specific patient and for a quantitative assessment of therapy's outcome.

A probabilistic finger biodynamic model better depicts the roles of the flexors during unloaded flexion

Previous deterministic finger biomechanical models predicted that the flexor digitorum superficialis (FDS) was silent and the flexor digitorum profundus (FDP) was the only active flexor during finger flexion. Experimental studies in vivo, however, recorded activities of both flexors. In this study, in an attempt to elucidate the roles of the flexors, a probabilistic biodynamic model of the index finger was constructed to estimate the muscle-tendon forces during an experimentally measured index finger flexion movement. A Monte-Carlo simulation was performed with four model parameters, including moment arms, physiological cross sectional areas (PCSA), passive torques, and anthropometric measures as independent random variables. The muscle-tendon forces at each time point were determined using a nonlinear optimization technique. The model predicted that both FDS and FDP contributed to sustaining the movement and the FDS was not necessarily silent. The two distinct force patterns observed in vivo in experimental studies were also corroborated by the simulation. These findings, contrary to previous deterministic models' predictions but in agreement with experimental measurements, explained the observed coactivation of FDS and FDP, and resolved the controversy regarding the roles of the flexors in finger movement dynamics.

Principal components analysis based control of a multi-DoF underactuated prosthetic hand

BACKGROUND

Functionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG). Driving a multi degrees of freedom (DoF) hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user.

METHODS

A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoFs underactuated prosthetic hand prototype (called CyberHand) with a two dimensional control input, in order to perform the three prehensile forms mostly used in Activities of Daily Living (ADLs). Such Principal Components set has been derived directly from the artificial hand by collecting its sensory data while performing 50 different grasps, and subsequently used for control.

RESULTS

Trials have shown that two independent input signals can be successfully used to control the posture of a real robotic hand and that correct grasps (in terms of involved fingers, stability and posture) may be achieved.

CONCLUSIONS

This work demonstrates the effectiveness of a bio-inspired system successfully conjugating the advantages of an underactuated, anthropomorphic hand with a PCA-based control strategy, and opens up promising possibilities for the development of an intuitively controllable hand prosthesis.

Motion pattern analysis of gait in horseback riding by means of Principal Component Analysis

As a consequence of the three interacting systems of horse, saddle, and rider, horseback riding is a very complex movement that is difficult to characterize by a limited number of biomechanical parameters or characteristic curves. Principal Component Analysis (PCA) is a technique for reducing multidimensional datasets to a minimal (i.e., optimally economic) set of dimensions. To apply PCA to horseback riding data, a "pattern vector" composed of the horizontal velocities of a set of body markers was determined. PCA was used to identify the major dynamic constituents of the three natural gaits of the horse: walk, trot, and canter. It was found that the trot is characterized by only one major component accounting for about 90% of the data's variance. Based on a study involving 13 horses with the same rider, additional phase plane analyses of the order parameter dynamics revealed a potential influence of the saddle type on movement coordination for the majority of horses.

Development and validation of a biodynamic model for predicting multi-finger movements in cylinder-grasping tasks

This article describes the development and validation of a model for predicting multi-finger movements in grasping activities. The model builds upon a newly proposed approach that incorporates forward dynamics and a system identification procedure, and is amenable to empirical tests. A database of multi-fingered grasping movements performed by 28 subjects was established and divided into four sets, one for model development and three for model validation. In the development phase, model parameter values were estimated by the iterative system identification procedure through a physics-based heuristic algorithm. The estimated parameter values were then statistically synthesised and integrated into the prediction model. In the validation phase, the model was applied to three novel datasets containing different grasping movements involving objects of varied sizes and different subjects. The results demonstrated the model's ability to predict hand prehensile movements with error magnitudes comparable to the inter-person variability in performing such movements. New insights into the control of multi-fingered hand prehensile movements at the systems and joint levels emerged from the model development and validation process. The current study contributes to building a foundation for long-term development of realistic biodynamic simulation of multi-finger hand movements. Such simulation capabilities will aid in design of hand-operated tools, devices or hand-intensive work for proactive ergonomics and in evaluation as well as treatment of functional impairment of the hand.