Finger Kinematic Modeling and Real-Time Hand Motion Estimation

Stretchable glove for accurate and robust hand pose reconstruction based on comprehensive motion data

We propose a compact wearable glove capable of estimating both the finger bone lengths and the joint angles of the wearer with a simple stretch-based sensing mechanism. The soft sensing glove is designed to easily stretch and to be one-size-fits-all, both measuring the size of the hand and estimating the finger joint motions of the thumb, index, and middle fingers. The system was calibrated and evaluated using comprehensive hand motion data that reflect the extensive range of natural human hand motions and various anatomical structures. The data were collected with a custom motion-capture setup and transformed into the joint angles through our post-processing method. The glove system is capable of reconstructing arbitrary and even unconventional hand poses with accuracy and robustness, confirmed by evaluations on the estimation of bone lengths (mean error: 2.1 mm), joint angles (mean error: 4.16°), and fingertip positions (mean 3D error: 4.02 mm), and on overall hand pose reconstructions in various applications. The proposed glove allows us to take advantage of the dexterity of the human hand with potential applications, including but not limited to teleoperation of anthropomorphic robot hands or surgical robots, virtual and augmented reality, and collection of human motion data.

Upper extremity kinematics: development of a quantitative measure of impairment severity and dissimilarity after stroke

Background

Strokes are a leading cause of disability worldwide, with many survivors experiencing difficulty in recovering upper extremity movement, particularly hand function and grasping ability. There is currently no objective measure of movement quality, and without it, rehabilitative interventions remain at best informed estimations of the underlying neural structures' response to produce movement. In this article, we utilize a novel modification to Procrustean distance to quantify curve dissimilarity and propose the Reach Severity and Dissimilarity Index (RSDI) as an objective measure of motor deficits.

Methods

All experiments took place at the Medstar National Rehabilitation Hospital; persons with stroke were recruited from the hospital patient population. Using Fugl-Meyer (FM) scores and reach capacities, stroke survivors were placed in either mild or severe impairment groups. Individuals completed sets of reach-to-target tasks to extrapolate kinematic metrics describing motor performance. The Procrustes method of statistical shape analysis was modified to identify reaching sub-movements that were congruous to able-bodied sub-movements.

Findings

Movement initiation proceeds comparably to the reference curve in both two- and three-dimensional representations of mild impairment movement. There were significant effects of the location of congruent segments between subject and reference curves, mean velocities, peak roll angle, and target error. These metrics were used to calculate a preliminary RSDI score with severity and dissimilarity sub-scores, and subjects were reclassified in terms of rehabilitation goals as Speed Emphasis, Strength Emphasis, and Combined Emphasis.

Interpretation

The modified Procrustes method shows promise in identifying disruptions in movement and monitoring recovery without adding to patient or clinician burden. The proposed RSDI score can be adapted and expanded to other functional movements and used as an objective clinical tool. By reducing the impact of stroke on disability, there is a significant potential to improve quality of life through individualized rehabilitation.

The influence of proximal motor strategies on pianists' upper-limb movement variability

Repetitive movements are considered a risk factor for developing practice-related musculoskeletal disorders. Intra-participant kinematic variability might help musicians reduce the risk of injury during repetitive tasks. No research has studied the effects of proximal motion (i.e., trunk and shoulder movement) on upper-limb movement variability in pianists. The first objective was to determine the effect of proximal movement strategies and performance tempo on both intra-participant joint angle variability of upper-limb joints and endpoint variability. The second objective was to compare joint angle variability between pianist's upper-limb joints. As secondary objectives, we assessed the relationship between intra-participant joint angle variability and task range of motion (ROM) and documented inter-participant joint angle variability. The upper body kinematics of 9 expert pianists were recorded using an optoelectronic system. Participants continuously performed two right-hand chords (lateral leap motions) while changing movements based on trunk motion (with and without) and shoulder motion (counter-clockwise, back-and-forth, and clockwise) at two tempi (slow and fast). Trunk and shoulder movement strategies collectively influenced variability at the shoulder, elbow and, to a lesser extent, the wrist. Slow tempi led to greater variability at wrist and elbow flexion/extension compared to fast tempi. Endpoint variability was influenced only along the anteroposterior axis. When the trunk was static, the shoulder had the lowest joint angle variability. When trunk motion was used, elbow and shoulder variability increased, and became comparable to wrist variability. ROM was correlated with intra-participant joint angle variability, suggesting that increased task ROM might result in increased movement variability during practice. Inter-participant variability was approximately six times greater than intra-participant variability. Pianists should consider incorporating trunk motion and a variety of shoulder movements as performance strategies while performing leap motions at the piano, as they might reduce exposure to risks of injury.

Dynamic assessment of the upper extremity: a review of available and emerging technologies

The purpose of this review article is to provide an update on the realm of emerging technology available for the assessment of dynamic functional movement of the hand and upper limb. A critical overview of the literature and a conceptual framework for use of such technologies is proposed. The framework explores three broad purpose categories including customization of care, functional surveillance and interventions through biofeedback strategies. State-of-the-art technologies are described, from basic activity monitors to feedback-enabled robotic gloves, along with exemplar trials and clinical applications. The future of technologies innovation in hand pathology is proposed in the context of the current obstacles and opportunities for hand surgeons and therapists.

Analysis of postures for handwriting on touch screens without using tools

The act of handwriting affected the evolutionary development of humans and still impacts the motor cognition of individuals. However, the ubiquitous use of digital technologies has drastically decreased the number of times we really need to pick a pen up and write on paper. Nonetheless, the positive cognitive impact of handwriting is widely recognized, and a possible way to merge the benefits of handwriting and digital writing is to use suitable tools to write over touchscreens or graphics tablets. In this manuscript, we focus on the possibility of using the hand itself as a writing tool. A novel hand posture named FingerPen is introduced, and can be seen as a grasp performed by the hand on the index finger. A comparison with the most common posture that people tend to assume (i.e. index finger-only exploitation) is carried out by means of a biomechanical model. A conducted user study shows that the FingerPen is appreciated by users and leads to accurate writing traits.

A method for measuring in vivo finger kinematics using electromagnetic tracking

Accurate in vivo measurement of finger joint kinematics is important for evaluation of treatment methods, implant designs, and for the development and validation of computer models of the hand. The main objective of this project was to develop a standardized finger kinematic measurement system employing electromagnetic (EM) tracking to measure in vivo finger motion pathways. A landmark digitization protocol was developed and used in vivo, in a biomechanical study using EM trackers secured to the finger segments. In vivo results for finger flexion/extension showed no significant differences between EM and goniometer results, 5°±3°; p = 0.735.

Proximal-to-Distal Sequences of Attack and Release Movements of Expert Pianists during Pressed-Staccato Keystrokes

The aims of this study were to i) evaluate proximal-to-distal sequencing (PDS) in pianists' attack and release movements during pressed-staccato keystrokes, and ii) investigate if trunk motion facilitates PDS of upper-limb movements. Nine expert pianists performed a series of loud pressed-staccato keystrokes. Kinematic data was recorded with a 3 D motion capture system. PDS was assessed by comparing temporal organization of peak velocities from the pelvis to the wrist. Evidence of PDS was found across the kinematic chain. Pianists' use of PDS differed mainly between scapula and shoulder movements. Trunk motion facilitated PDS by increasing anticipatory shoulder movements and by preceding shoulder-girdle attack and release movements. Implications might relate to research on performance optimization and injury prevention strategies.

Effects of Trunk Motion, Touch, and Articulation on Upper-Limb Velocities and on Joint Contribution to Endpoint Velocities During the Production of Loud Piano Tones

Piano performance involves several levels of motor abundancy. Identification of kinematic strategies that enhance performance and reduce risks of practice-related musculoskeletal disorders (PRMD) represents an important research topic since more than half of professional pianists might suffer from PRMD during their career. Studies in biomechanics have highlighted the benefits of using proximal upper-limb joints to reduce the load on distal segments by effectively creating velocity and force at the finger–key interaction. If scientific research has documented postural and expressive features of pianists’ trunk motion, there is currently a lack of scientific evidence assessing the role of trunk motion in sound production and in injury prevention. We address this gap by integrating motion of the pelvis and thorax in the analysis of both upper-limb linear velocities and joint angular contribution to endpoint velocities. Specifically, this study aims to assess kinematic features of different types of touch and articulation and the impact of trunk motion on these features. Twelve pianists performed repetitive loud and slow-paced keystrokes. They were asked to vary (i) body implication (use of trunk and upper-limb motion or use of only upper-limb motion), (ii) touch (struck touch, initiating the attack with the fingertip at a certain distance from the key surface, or pressed touch, initiating the attack with the fingertip in contact with the key surface), and (iii) articulation (staccato, short finger–key contact time, or tenuto, sustained finger–key contact time). Data were collected using a 3D motion capture system and a sound recording device. Results show that body implication, touch, and articulation modified kinematic features of loud keystrokes, which exhibited not only downward but also important forward segmental velocities (particularly in pressed touch and staccato articulation). Pelvic anterior rotation had a prominent role in the production of loud tones as it effectively contributed to creating forward linear velocities at the upper limb. The reported findings have implications for the performance, teaching, and research domains since they provide evidence of how pianists’ trunk motion can actively contribute to the sound production and might not only be associated with either postural or expressive features.

In Vivo Measurement of Thumb Joint Reaction Forces During Smartphone Manipulation: A Biomechanical Analysis

The relationship between arthritis or repetitive stress injuries (RSIs) in thumbs and rapidly increasing hours of smartphone usage is not fully elucidated. We evaluated axial joint reaction forces (AJRFs) and thumb torques in 19 healthy subjects performing typical smartphone tasks, which included tapping, tap game, and swiping. We measured force and torque when a subject tapped or swiped the panel of the smartphone and analyzed the motions of each joint using surface markers and motion capture systems. We calculated AJRFs and torques on each thumb joint using inverse dynamics. The results were then compared with representative activities such as computer keyboard typing and handwriting. The mean AJRFs/torques at the thumb carpometacarpal joint (CMCJ) while tapping the smartphone and tap gaming were 12.5 N/95.5 N mm and 21.1 N/187.21 N mm, respectively. AJRFs and torques were significantly higher during tap gaming activities than during simple tapping subtasks (p = 0.003 and p < 0.001, respectively). Compared with those during computer keyboard typing, the mean AJRFs and torques at the CMCJ during smartphone tapping was 3 (p = 0.075) and 1.4 times (p = 0.680) larger, respectively. Considering the rapidly increasing dependency on smartphones in our daily lives, long-term exposure of the thumb to repetitive AJRFs and torques may lead to an acceleration of arthritis or aggravation of RSIs in thumbs. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:2437-2444, 2019.

Assessment of hand function during activities of daily living using motion tracking cameras: A systematic review

The human hand is the most frequently used body part in activities of daily living. With its complex anatomical structure and the small size compared to the body, assessing the functional capability is highly challenging. The aim of this review was to provide a systematic overview on currently available 3D motion analysis based on skin markers for the assessment of hand function during activities of daily living. It is focused on methodology rather than results. A systematic review according to the PRISMA guidelines was performed. The systematic search yielded 1349 discrete articles. Of 147 articles included on basis of title, 123 were excluded after abstract review, and 24 were included in the full-text analysis with 13 key articles. There is still limited knowledge about hand and finger kinematics during activities of daily living. A standardization of the task is required in order to overcome the nonrepetitive nature and high variability of upper limb motion and ensure repeatability of task performance. To yield a progress in the analysis of human hand movements, an assessment of human kinematics including fingers, wrist, and thumb and an identification of relevant parameters that characterize a healthy motion pattern during functional tasks are needed.

A quantitative taxonomy of human hand grasps

Background

A proper modeling of human grasping and of hand movements is fundamental for robotics, prosthetics, physiology and rehabilitation. The taxonomies of hand grasps that have been proposed in scientific literature so far are based on qualitative analyses of the movements and thus they are usually not quantitatively justified.

Methods

This paper presents to the best of our knowledge the first quantitative taxonomy of hand grasps based on biomedical data measurements. The taxonomy is based on electromyography and kinematic data recorded from 40 healthy subjects performing 20 unique hand grasps. For each subject, a set of hierarchical trees are computed for several signal features. Afterwards, the trees are combined, first into modality-specific (i.e. muscular and kinematic) taxonomies of hand grasps and then into a general quantitative taxonomy of hand movements. The modality-specific taxonomies provide similar results despite describing different parameters of hand movements, one being muscular and the other kinematic.

Results

The general taxonomy merges the kinematic and muscular description into a comprehensive hierarchical structure. The obtained results clarify what has been proposed in the literature so far and they partially confirm the qualitative parameters used to create previous taxonomies of hand grasps. According to the results, hand movements can be divided into five movement categories defined based on the overall grasp shape, finger positioning and muscular activation. Part of the results appears qualitatively in accordance with previous results describing kinematic hand grasping synergies.

Conclusions

The taxonomy of hand grasps proposed in this paper clarifies with quantitative measurements what has been proposed in the field on a qualitative basis, thus having a potential impact on several scientific fields.

Posture similarity index: a method to compare hand postures in synergy space

Background

The human hand can perform a range of manipulation tasks, from holding a pen to holding a hammer. The central nervous system (CNS) uses different strategies in different manipulation tasks based on task requirements. Attempts to compare postures of the hand have been made for use in robotics and animation industries. In this study, we developed an index called the posture similarity index to quantify the similarity between two human hand postures.

Methods

Twelve right-handed volunteers performed 70 postures, and lifted and held 30 objects (total of 100 different postures, each performed five times). A 16-sensor electromagnetic tracking system captured the kinematics of individual finger phalanges (segments). We modeled the hand as a 21-DoF system and computed the corresponding joint angles. We used principal component analysis to extract kinematic synergies from this 21-DoF data. We developed a posture similarity index (PSI), that represents the similarity between posture in the synergy (Principal component) space. First, we tested the performance of this index using a synthetic dataset. After confirming that it performs well with the synthetic dataset, we used it to analyze the experimental data. Further, we used PSI to identify postures that are “representative” in the sense that they have a greater overlap (in synergy space) with a large number of postures.

Results

Our results confirmed that PSI is a relatively accurate index of similarity in synergy space both with synthetic data and real experimental data. Also, more special postures than common postures were found among “representative” postures.

Conclusion

We developed an index for comparing posture similarity in synergy space and demonstrated its utility by using synthetic dataset and experimental dataset. Besides, we found that “special” postures are actually “special” in the sense that there are more of them in the “representative” postures as identified by our posture similarity index.

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.

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.

A Motion Analysis Protocol for Kinematic Assessment of Poly-Articulated Prosthetic Hands With Cosmetic Gloves

To provide upper-limb amputees with devices that best fit their needs and to test innovative solutions, it is necessary to quantitatively appraise a device performance with rigorous measurement methods. The aim of this work was to define an optimal motion analysis protocol, suitable for optoelectronic systems, to measure the kinematics of poly-articulated hands even when covered by a cosmetic glove. This is a fundamental aspect, because gloves can decrease device speed and range of motion and, ultimately, patients' acceptance of the artificial limb. In this work, different mathematical models of the joints and marker-sets for motion analysis were conceived. A regression model to choose a reduced marker-set for studying the hand performance with different cosmetic glove models was developed. The proposed approaches for finger motion analysis were experimentally tested on the index finger of the i-Limb, a commercial myoelectric poly-articulated prosthetic hand, but the results can be easily extended to the whole hand and to other poly-articulated prosthetic hands. The methods proposed for the performance analysis of prosthetic hands points out that the cosmetic gloves imply a reduction of the finger flexion/extension (F/E) angles and of the motion velocity. This draws attention to the need for performing independent cyclic tests on commercial products with various cosmetic solutions to better guide component selection.

A stochastic algorithm for automatic hand pose and motion estimation

In this paper, a novel, robust, and simple method for automatically estimating the hand pose is proposed and validated. The method uses a multi-camera optoelectronic system and a model-based stochastic algorithm. The approach is marker-based and relies on an Unscented Kalman Filter. A hand kinematic model is introduced for constraining relative marker's positions and improving the algorithm robustness with respect to outliers and possible occlusions. The algorithm outputs are 3D coordinate measures of markers and hand joint angle values. To validate the proposed algorithm, a comparison with ground truths for angular and 3D coordinate measures is carried out. The comparative analysis shows the advantages of using the model-based stochastic algorithm with respect to standard processing software of optoelectronic cameras in terms of implementation simplicity, time consumption, and user effort. The accuracy is remarkable, with a difference of maximum 0.035r a d and 4m m with respect to angular and 3D Cartesian coordinates ground truths, respectively.

Design, control, and testing of a thumb exoskeleton with series elastic actuation

We present an exoskeleton capable of assisting the human thumb through a large range of motion. Our novel thumb exoskeleton has the following unique features: (i) an underlying kinematic mechanism that is optimized to achieve a large range of motion, (ii) a design that actuates four degrees of freedom of the thumb, and (iii) a series elastic actuation based on a Bowden cable, allowing for bidirectional torque control of each thumb joint individually. We present a kinematic model of the coupled thumb exoskeleton system and use it to maximize the range of motion of the thumb. Finally, we carry out tests with the designed device on four subjects to evaluate its workspace and kinematic transparency using a motion capture system and torque control performance. Results show that the device allows for a large workspace with the thumb, is kinematically transparent to natural thumb motion to a high degree, and is capable of accurate torque control.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input.

Evaluation of hand motion capture protocol using static computed tomography images: application to an instrumented glove

There has been a marked increase in the use of hand motion capture protocols in the past 20 yr. However, their absolute accuracies and precisions remain unclear. The purpose of this technical brief was to present a method for evaluating the accuracy and precision of the joint angles determined by a hand motion capture protocol using simultaneously collected static computed tomography (CT) images. The method consists of: (i) recording seven functional postures using both the motion capture protocol and a CT scanner; (ii) obtaining principal axes of the bones in each method; (iii) calculating the flexion angle at each joint for each method as the roll angle of the composite, sequential, roll-pitch-yaw rotations relating the orientation of the distal bone to the proximal bone; and (iv) comparing corresponding joint angle measurements. For demonstration, we applied the method to a Cyberglove protocol. Accuracy and precision of the instrumented-glove protocol were calculated as the mean and standard deviation, respectively, of the differences between the angles determined from the Cyberglove output and the CT images across the seven postures. Implementation in one subject highlighted substantial errors, especially for the distal joints of the fingers. This technical note both clearly demonstrates the need for future work and introduces a solid, technical approach with the potential to improve the current state of such assessments in our field.

Robust identification of three-dimensional thumb and index finger kinematics with a minimal set of markers

This study presents a methodology to determine thumb and index finger kinematics while utilizing a minimal set of markers. The motion capture of skin-surface markers presents inherent challenges for the accurate and comprehensive measurement of digit kinematics. As such, it is desirable to utilize robust methods for assessing digit kinematics with fewer markers. The approach presented in this study involved coordinate system alignment, locating joint centers of rotation, and a solution model to estimate three-dimensional (3-D) digit kinematics. The solution model for each digit was based on assumptions of rigid-body interactions, specific degrees of freedom (DOFs) at each located joint, and the aligned coordinate system definitions. Techniques of inverse kinematics and optimization were applied to calculate the 3-D position and orientation of digit segments during pinching between the thumb and index finger. The 3-D joint center locations were reliably fitted with mean coefficients of variation below 5%. A parameterized form of the solution model yielded feasible solutions that met specified tolerance and convergence criteria for over 85% of the test points. The solution results were intuitive to the pinching function. The thumb was measured to be rotated about the CMC joint to bring it into opposition to the index finger and larger rotational excursions (&gt;10 deg) were observed in flexion/extension compared to abduction/adduction and axial rotation for all joints. While the solution model produced results similar to those computed from a full marker set, the model facilitated the usage of fewer markers, which inherently lessened the effects of passive motion error and reduced the post-experimental effort required for marker processing.

Validity of a simple videogrammetric method to measure the movement of all hand segments for clinical purposes

Hand movement measurement is important in clinical, ergonomics and biomechanical fields. Videogrammetric techniques allow the measurement of hand movement without interfering with the natural hand behaviour. However, an accurate measurement of the hand movement requires the use of a high number of markers, which limits its applicability for the clinical practice (60 markers would be needed for hand and wrist). In this work, a simple method that uses a reduced number of markers (29), based on a simplified kinematic model of the hand, is proposed and evaluated. A set of experiments have been performed to evaluate the errors associated with the kinematic simplification, together with the evaluation of its accuracy, repeatability and reproducibility. The global error attributed to the kinematic simplification was 6.68°. The method has small errors in repeatability and reproducibility (3.43° and 4.23°, respectively) and shows no statistically significant difference with the use of electronic goniometers. The relevance of the work lies in the ability of measuring all degrees of freedom of the hand with a reduced number of markers without interfering with the natural hand behaviour, which makes it suitable for its use in clinical applications, as well as for ergonomic and biomechanical purposes.

Human Hand Motion Analysis and Synthesis of Optimal Power Grasps for a Robotic Hand

Biologically inspired robotic systems can find important applications in biomedical robotics, since studying and replicating human behaviour can provide new insights into motor recovery, functional substitution and human-robot interaction. The analysis of human hand motion is essential for collecting information about human hand movements useful for generalizing reaching and grasping actions on a robotic system. This paper focuses on the definition and extraction of quantitative indicators for describing optimal hand grasping postures and replicating them on an anthropomorphic robotic hand. A motion analysis has been carried out on six healthy human subjects performing a transverse volar grasp. The extracted indicators point to invariant grasping behaviours between the involved subjects, thus providing some constraints for identifying the optimal grasping configuration. Hence, an optimization algorithm based on the Nelder-Mead simplex method has been developed for determining the optimal grasp configuration of a robotic hand, grounded on the aforementioned constraints. It is characterized by a reduced computational cost. The grasp stability has been tested by introducing a quality index that satisfies the form-closure property. The grasping strategy has been validated by means of simulation tests and experimental trials on an arm-hand robotic system. The obtained results have shown the effectiveness of the extracted indicators to reduce the non-linear optimization problem complexity and lead to the synthesis of a grasping posture able to replicate the human behaviour while ensuring grasp stability. The experimental results have also highlighted the limitations of the adopted robotic platform (mainly due to the mechanical structure) to achieve the optimal grasp configuration.

Effects of substituting anthropometric joints with revolute joints in humanoid robots and robotic hands: a case study

In the human body there are many joints whose functions are very similar to revolute joints. To avoid the complexity of these joints, they are usually substituted by revolute joints in many humanoid robots. Revolute joints have purely rotational motion along their fixed axis, while real joints in the human body have Instantaneous Rotational Axis (IRA) due to their configuration. Substitution of this kind of human joints with revolute (hinge) joints in robots changes the kinematics of joints. Knowing the exact characteristics of the moving axis of rotation in human joints is a prerequisite for the kinematic study of a joint. Here the main geometrical difference between these kinds of joints in humans and their simplified (hinge-like) models in robots is described. Then, as a case study, the mechanism of the three joints of the index finger are compared with their hinge-like model using a multi-body code to understand when revolute joints can be substituted for anthropometric joints in hand exoskeletons and robotic hands. Furthermore, the position of IRA and its distance from the center of the condyle of the joint are presented. The concept and the results can be extended for other fingers and all similar joints, and can be used in humanoid robots, hand exoskeletons and robotic hands.

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.

Human hand modelling: kinematics, dynamics, applications

An overview of mathematical modelling of the human hand is given. We consider hand models from a specific background: rather than studying hands for surgical or similar goals, we target at providing a set of tools with which human grasping and manipulation capabilities can be studied, and hand functionality can be described. We do this by investigating the human hand at various levels: (1) at the level of kinematics, focussing on the movement of the bones of the hand, not taking corresponding forces into account; (2) at the musculotendon structure, i.e. by looking at the part of the hand generating the forces and thus inducing the motion; and (3) at the combination of the two, resulting in hand dynamics as well as the underlying neurocontrol. Our purpose is to not only provide the reader with an overview of current human hand modelling approaches but also to fill the gaps with recent results and data, thus allowing for an encompassing picture.

Reducing musculoskeletal disorders among computer operators: comparison between ergonomics interventions at the workplace

Typing is associated with musculoskeletal disorders (MSDs) caused by multiple risk factors. This control study aimed to evaluate the efficacy of a workplace intervention for reducing MSDs among computer workers. Sixty-six subjects with and without MSD were assigned consecutively to one of three groups: ergonomics intervention (work site and body posture adjustments, muscle activity training and exercises) accompanied with biofeedback training, the same ergonomics intervention without biofeedback and a control group. Evaluation of MSDs, body posture, psychosocial status, upper extremity (UE) kinematics and muscle surface electromyography were carried out before and after the intervention in the workplace and the motion lab. Our main hypothesis that significant differences in the reduction of MSDs will exist between subjects in the study groups and controls was confirmed (χ(2) = 13.3; p = 0.001). Significant changes were found in UE kinematics and posture as well. Both ergonomics interventions effectively reduced MSD and improved body posture.

PRACTITIONER SUMMARY

This study aimed to test the efficacy of an individual workplace intervention programme among computer workers by evaluating musculoskeletal disorders (MSDs), body posture, upper extremity kinematics, muscle activity and psychosocial factors were tested. The proposed ergonomics interventions effectively reduced MSDs and improved body posture.

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.

Range of motion of the metacarpophalangeal joint in rheumatoid patients, with and without a flexible joint replacement prosthesis, compared with normal subjects

BACKGROUND

The metacarpophalangeal is commonly affected by rheumatoid arthritis. This may lead to joint replacement with a flexible prosthesis. The aims of this study were to determine the effects of rheumatoid arthritis on joint motion and to determine whether joint replacement needs to restore the full range of motion.

METHODS

Three-dimensional motion analysis was used to measure the range of motion of the metacarpophalangeal joint in rheumatoid patients with and without a flexible silicone arthroplasty, when performing pinch and key grips, when making a fist and when spreading the fingers. The results were compared with those from younger and older normal subjects.

FINDINGS

There appeared to be a trend for a decrease in range of motion from younger normal to older normal to rheumatoid (no prosthesis) to rheumatoid (with prosthesis) subject groups. However, statistically different (p<0.05) results were only observed for some movements (mostly involved in making a fist), in some fingers and between some subject groups. The only exception to this apparent trend was in flexion/extension when spreading the fingers into abduction.

INTERPRETATION

Making a fist is the most sensitive simple measure of range of motion in the metacarpophalangeal joint. Successful replacement of the metacarpophalangeal joint in patients with rheumatoid arthritis need not restore the normal range of motion.

A three-dimensional analysis of finger and bow string movements during the release in archery

The aim of this paper was to examine finger and bow string movements during archery by investigating a top Austrian athlete (FITA score = 1233) under laboratory conditions. Maximum lateral bow string deflection and angular displacements for index, third, and ring fingers between the full draw position and the end of the release were quantified using a motion tracking system. Stepwise multiple regression analyses were used to determine whether bow string deflection and finger movements are predictive for scoring. Joint ranges of motion during the shot itself were large in the proximal and distal interphalangeal joints, and much smaller in the metacarpophalangeal joints. Contrary to our expectations, greater deflection leads to higher scores (R2 = .18, p < .001) and the distal interphalangeal joint of the third finger weakly predicts the deflection (R2 = .11, p < .014). More variability in the joint angles of the third finger was found in bad shots than in good shots. Findings in this study let presume that maximum lateral bow string deflection does not adversely affect the archer's performance.

Modified kinematic technique for measuring pathological hyperextension and hypermobility of the interphalangeal joints

Dynamic finger joint motion is difficult to measure using optical motion analysis techniques due to the limited surface area allowed for adequate marker placement. This paper describes an extension of a previously validated kinematic measurement technique using a reduced surface marker set and outlines the required calculations based on a specific surface marker placement to calculate flexion/extension and hyperextension of the metacarpophalangeal, proximal interphalangeal, and distal interphalangeal joints. The modified technique has been assessed for accuracy using a series of static reference frames (absolute residual error = ±3.7°, cross correlation between new method and reference frames; r=0.99). The method was then applied to a small group of participants with rheumatoid arthritis (seven females, one male; mean age = 62.8 years ± 12.04) and illustrated congruent strategies of movement for a participant and a large range of finger joint movement over the sample (5.8-71.1°, smallest to largest active range of motion). This method used alongside the previous paper provides a comprehensive, validated method for calculating 3-D wrist, hand, fingers, and thumb kinematics to date and provides a valuable measurement tool for clinical research.

Tracking whole hand kinematics using extended Kalman filter

This paper describes the general procedure, model construction, and experimental results of tracking whole hand kinematics using extended Kalman filter (EKF) based on data recorded from active surface markers. We used a hand model with 29 degrees of freedom that consists of hand global posture, wrist, and digits. The marker protocol had 4 markers on the distal forearm and 20 markers on the dorsal surface of the joints of the digits. To reduce computational load, we divided the state space into four sub-spaces, each of which were estimated with an EKF in a specific order. We tested our framework and found reasonably accurate results (2-4 mm tip position error) when sampling tip to tip pinch at 120 Hz.

In vivo validation of a realistic kinematic model for the trapezio-metacarpal joint using an optoelectronic system

This article analyzes a realistic kinematic model of the trapezio-metacarpal (TM) joint in the human thumb that involves two non-orthogonal and non-intersecting rotation axes. The estimation of the model parameters, i.e. the position and orientation of the two axes with respect to an anatomical coordinate system, was carried out by processing the motion of nine retroreflective markers, externally attached to the hand surface, surveyed by a video motion capture system. In order to compute the model parameters, prototypical circumduction movements were processed within an evolutionary optimization approach. Quality and reproducibility in assessing the parameters were demonstrated across multiple testing sessions on 10 healthy subjects (both left and right thumbs), involving the complete removal of all markers and then retesting. Maximum errors of less than 5 mm in the axis position and less than 6 degrees in the orientation were found, respectively. The inter-subject mean distance between the two axes was 4.16 and 4.71 mm for right and left TM joints, respectively. The inter-subject mean relative orientation between the two axes was about 106 and 113 degrees for right and left TM joints, respectively. Generalization properties of the model were evaluated quantitatively on opposition movements in terms of distance between measured and predicted marker positions (maximum error less than 5 mm). The performance of the proposed model compared favorably with the one (maximum error in the range of 7-8 mm) obtained by applying a universal joint model (orthogonal and intersecting axes). The ability of in vivo estimating the parameters of the proposed kinematic model represents a significant improvement for the biomechanical analysis of the hand motion.