Finger joint impedance during tapping on a computer keyswitch

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

Biomechanical Analysis of the Human Finger Extensor Mechanism during Isometric Pressing

This study investigated the effects of the finger extensor mechanism on the bone-to-bone contact forces at the interphalangeal and metacarpal joints and also on the forces in the intrinsic and extrinsic muscles during finger pressing. This was done with finger postures ranging from very flexed to fully extended. The role of the finger extensor mechanism was investigated by using two alternative finger models, one which omitted the extensor mechanism and another which included it. A six-camera three-dimensional motion analysis system was used to capture the finger posture during maximum voluntary isometric pressing. The fingertip loads were recorded simultaneously using a force plate system. Two three-dimensional biomechanical finger models, a minimal model without extensor mechanism and a full model with extensor mechanism (tendon network), were used to calculate the joint bone-to-bone contact forces and the extrinsic and intrinsic muscle forces. If the full model is assumed to be realistic, then the results suggest some useful biomechanical advantages provided by the tendon network of the extensor mechanism. It was found that the forces in the intrinsic muscles (interosseus group and lumbrical) are significantly reduced by 22% to 61% due to the action of the extensor mechanism, with the greatest reductions in more flexed postures. The bone-to-bone contact force at the MCP joint is reduced by 10% to 41%. This suggests that the extensor mechanism may help to reduce the risk of injury at the finger joints and also to moderate the forces in intrinsic muscles. These apparent biomechanical advantages may be a result of the extensor mechanism''s distinctive interconnected fibrous structure, through which the contraction of the intrinsic muscles as flexors of the MCP joint can generate extensions at the DIP and PIP joints.     

Extrinsic flexor muscles generate concurrent flexion of all three finger joints

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

The contribution of the wrist, elbow and shoulder joints to single-finger tapping

We aimed to determine the role of the wrist, elbow and shoulder joints to single-finger tapping. Six human subjects tapped with their index finger at a rate of 3 taps/s on a keyswitch across five conditions, one freestyle (FS) and four instructed tapping strategies. The four instructed conditions were to tap on a keyswitch using the finger joint only (FO), the wrist joint only (WO), the elbow joint only (EO), and the shoulder joint only (SO). A single-axis force plate measured the fingertip force. An infra-red active-marker three-dimensional motion analysis system measured the movement of the fingertip, hand, forearm, upper arm and trunk. Inverse dynamics estimated joint torques for the metacarpal-phalangeal (MCP), wrist, elbow, and shoulder joints. For FS tapping 27%, 56%, and 18% of the vertical fingertip movement were a result of flexion of the MCP joint and wrist joint and extension of the elbow joint, respectively. During the FS movements the net joint powers between the MCP, wrist and elbow were positively correlated (correlation coefficients between 0.46 and 0.76) suggesting synergistic efforts. For the instructed tapping strategies (FO, WO, EO, and SO), correlations decreased to values below 0.35 suggesting relatively independent control of the different joints. For FS tapping, the kinematic and kinetic data indicate that the wrist and elbow contribute significantly, working in synergy with the finger joints to create the fingertip tapping task.     

The effect of finger extensor mechanism on the flexor force during isometric tasks.

The role of the intrinsic finger flexor muscles was investigated during finger flexion tasks. A suspension system was used to measure isometric finger forces when the point of force application varied along fingers in a distal-proximal direction. Two biomechanical models, with consideration of extensor mechanism Extensor Mechanism Model (EMM) and without consideration of extensor mechanism Flexor Model (FM), were used to calculate forces of extrinsic and intrinsic finger flexors. When the point of force application was at the distal phalanx, the extrinsic flexor muscles flexor digitorum profundus, FDP, and flexor digitorum superficialis, FDS, accounted for over 80% of the summed force of all flexors, and therefore were the major contributors to the joint flexion at the distal interphalangeal (DIP), proximal interphalangeal (PIP), and metacarpophalangeal (MCP) joints. When the point of force application was at the DIP joint, the FDS accounted for more than 70% of the total force of all flexors, and was the major contributor to the PIP and MCP joint flexion. When the force of application was at the PIP joint, the intrinsic muscle group was the major contributor for MCP flexion, accounting for more than 70% of the combined force of all flexors. The results suggest that the effects of the extensor mechanism on the flexors are relatively small when the location of force application is distal to the PIP joint. When the external force is applied proximally to the PIP joint, the extensor mechanism has large influence on force production of all flexors. The current study provides an experimental protocol and biomechanical models that allow estimation of the effects of extensor mechanism on both the extrinsic and intrinsic flexors in various loading conditions, as well as differentiating the contribution of the intrinsic and extrinsic finger flexors during isometric flexion.     

Intrinsic and extrinsic contributions to the passive moment at the metacarpophalangeal joint

The purpose of this investigation was to determine whether the passive range of motion at the finger joints is restricted more by intrinsic tissues (cross a single joint) or by extrinsic tissues (cross multiple joints). The passive moment at the metacarpophalangeal (MP) joint of the index finger was modeled as the sum of intrinsic and extrinsic components. The intrinsic component was modeled only as a function of MP joint angle. The extrinsic component was modeled as a function of MP joint angle and wrist angle. With the wrist fixed in seven different positions the passive moment at the MP joint of eight subjects was recorded as the finger was rotated through its range at a constant rate. The moment-angle data were fit by the model and the extrinsic and intrinsic components were calculated for a range of MP joint angles and wrist positions. With the MP joint near its extension limit, the median percent extrinsic contribution was 94% with the wrist extended 60° and 14% with the wrist flexed 60°. These percentages were 40 and 88%, respectively, with the MP joint near its flexion limit. Our findings indicate that at most wrist angles the extrinsic tissues offer greater restraint at the limits of MP joint extension and flexion than the intrinsic tissues. The intrinsic tissues predominate when the wrist is flexed or extended enough to slacken the extrinsic tissues. Additional characteristics of intrinsic and extrinsic tissues can be deduced by examining the parameter values calculated by the model.     

Estimation of the effective static moment arms of the tendons in the index finger extensor mechanism

A novel technique to estimate the contribution of finger extensor tendons to joint moment generation was proposed. Effective static moment arms (ESMAs), which represent the net effects of the tendon force on joint moments in static finger postures, were estimated for the 4 degrees of freedom (DOFs) in the index finger. Specifically, the ESMAs for the five tendons contributing to the finger extensor apparatus were estimated by directly correlating the applied tendon force to the measured resultant joint moments in cadaveric hand specimens. Repeated measures analysis of variance revealed that the finger posture, specifically interphalangeal joint angles, had significant effects on the measured ESMA values in 7 out of 20 conditions (four DOFs for each of the five muscles). Extensor digitorum communis and extensor indicis proprius tendons were found to have greater MCP ESMA values when IP joints are flexed, whereas abduction ESMAs of all muscles except extensor digitorum profundus were mainly affected by MCP flexion. The ESMAs were generally smaller than the moment arms estimated in previous studies that employed kinematic measurement techniques. Tendon force distribution within the extensor hood and dissipation into adjacent structures are believed to contribute to the joint moment reductions, which result in smaller ESMA values.     

Temporal Control and Hand Movement Efficiency in Skilled Music Performance

Skilled piano performance requires considerable movement control to accomplish the high levels of timing and force precision common among professional musicians, who acquire piano technique over decades of practice. Finger movement efficiency in particular is an important factor when pianists perform at very fast tempi. We document the finger movement kinematics of highly skilled pianists as they performed a five-finger melody at very fast tempi. A three-dimensional motion-capture system tracked the movements of finger joints, the hand, and the forearm of twelve pianists who performed on a digital piano at successively faster tempi (7–16 tones/s) until they decided to stop. Joint angle trajectories computed for all adjacent finger phalanges, the hand, and the forearm (wrist angle) indicated that the metacarpophalangeal joint contributed most to the vertical fingertip motion while the proximal and distal interphalangeal joints moved slightly opposite to the movement goal (finger extension). An efficiency measure of the combined finger joint angles corresponded to the temporal accuracy and precision of the pianists’ performances: Pianists with more efficient keystroke movements showed higher precision in timing and force measures. Keystroke efficiency and individual joint contributions remained stable across tempo conditions. Individual differences among pianists supported the view that keystroke efficiency is required for successful fast performance.     

Coordination of thumb joints during opposition

Thumb opposition plays a vital role in hand function. Kinematically, thumb opposition results from composite movements from multiple joints moving in multiple directions. The purpose of this study was to examine the coordination of thumb joints during opposition tasks. A total of 15 female subjects with asymptomatic hands were studied. Three-dimensional angular kinematics of the carpometacarpal (CMC), metacarpophalangeal (MCP) and interphalangeal (IP) joints were obtained by a marker-based motion analysis system. Thumb opposition revealed coordination among joints in a specific direction (inter-joint coordination) and among different directions within a joint (intra-joint coordination). In particular, linear couplings existed between the flexion and pronation at the CMC joint, and between the flexion of the CMC joint and flexion of the MCP joint. Principal component analysis showed that only two principal components adequately represented the thumb opposition data of seven movement directions. A term functional degrees of freedom by virtue of principal component analysis was proposed to uncover the extent of movement coordination in functional tasks.     

Computer keyswitch force–displacement characteristics affect muscle activity patterns during index finger tapping

This study examined the effect of computer keyboard keyswitch design on muscle activity patterns during finger tapping. In a repeated-measures laboratory experiment, six participants tapped with their index fingers on five isolated keyswitch designs with varying force–displacement characteristics that provided pairwise comparisons for the design factors of (1) activation force (0.31 N vs. 0.59 N; 0.55 N vs. 0.93 N), (2) key travel (2.5 mm vs. 3.5 mm), and (3) shape of the force–displacement curve as realized through buckling-spring vs. rubber-dome switch designs. A load cell underneath the keyswitch measured vertical fingertip forces, and intramuscular fine wire EMG electrodes measured muscle activity patterns of two intrinsic (first lumbricalis, first dorsal interossei) and three extrinsic (flexor digitorum superficialis, flexor digitorum profundus, and extensor digitorum communis) index finger muscles. The amplitude of muscle activity for the first dorsal interossei increased 25.9% with larger activation forces, but not for the extrinsic muscles. The amplitude of muscle activity for the first lumbricalis and the duration of muscle activities for the first dorsal interossei and both extrinsic flexor muscles decreased up to 40.4% with longer key travel. The amplitude of muscle activity in the first dorsal interossei increased 36.6% and the duration of muscle activity for all muscles, except flexor digitorum profundus, decreased up to 49.1% with the buckling-spring design relative to the rubber-dome design. These findings suggest that simply changing the force–displacement characteristics of a keyswitch changes the dynamic loading of the muscles, especially in the intrinsic muscles, during keyboard work.     

Kinematic evaluation of the finger’s interphalangeal joints coupling mechanism—variability,flexion–extension differences,triggers, locking swanneck deformities,anthropometric correlations

The human finger contains tendon/ligament mechanisms essential for proper control. One mechanism couples the movements of the interphalangeal joints when the (unloaded) finger is flexed with active deep flexor. This study’s aim was to accurately determine in a large finger sample the kinematics and variability of the coupled interphalangeal joint motions, for potential clinical and finger model validation applications. The data could also be applied to humanoid robotic hands. Sixty-eight fingers were measured in seventeen hands in nine subjects. Fingers exhibited great joint mobility variability, with passive proximal interphalangeal hyperextension ranging from zero to almost fifty degrees. Increased measurement accuracy was obtained by using marker frames to amplify finger segment motions. Gravitational forces on the marker frames were not found to invalidate measurements. The recorded interphalangeal joint trajectories were highly consistent, demonstrating the underlying coupling mechanism. The increased accuracy and large sample size allowed for evaluation of detailed trajectory variability, systematic differences between flexion and extension trajectories, and three trigger types, distinct from flexor tendon triggers, involving initial flexion deficits in either proximal or distal interphalangeal joint. The experimental methods, data and analysis should advance insight into normal and pathological finger biomechanics (e.g., swanneck deformities), and could help improve clinical differential diagnostics of trigger finger causes. The marker frame measuring method may be useful to quantify interphalangeal joints trajectories in surgical/rehabilitative outcome studies. The data as a whole provide the most comprehensive collection of interphalangeal joint trajectories for clinical reference and model validation known to us to date.     

Incorporating the length-dependent passive-force generating muscle properties of the extrinsic finger muscles into a wrist and finger biomechanical musculoskeletal model

Dynamic movement trajectories of low mass systems have been shown to be predominantly influenced by passive viscoelastic joint forces and torques compared to momentum and inertia. The hand is comprised of 27 small mass segments. Because of the influence of the extrinsic finger muscles, the passive torques about each finger joint become a complex function dependent on the posture of multiple joints of the distal upper limb. However, biomechanical models implemented for the dynamic simulation of hand movements generally don’t extend proximally to include the wrist and distal upper limb. Thus, they cannot accurately represent these complex passive torques. The purpose of this short communication is to both describe a method to incorporate the length-dependent passive properties of the extrinsic index finger muscles into a biomechanical model of the upper limb and to demonstrate their influence on combined movement of the wrist and fingers. Leveraging a unique set of experimental data, that describes the net passive torque contributed by the extrinsic finger muscles about the metacarpophalangeal joint of the index finger as a function of both metacarpophalangeal and wrist postures, we simulated the length-dependent passive properties of the extrinsic finger muscles. Dynamic forward simulations demonstrate that a model including these properties passively exhibits coordinated movement between the wrist and finger joints, mimicking tenodesis, a behavior that is absent when the length-dependent properties are removed. This work emphasizes the importance of incorporating the length-dependent properties of the extrinsic finger muscles into biomechanical models to study healthy and impaired hand movements.     

Estimating in vivo passive forces of the index finger muscles: Exploring model parameters

We compared predicted passive finger joint torques from a biomechanical model that includes the exponential passive muscle force–length relationship documented in the literature with finger joint torques estimated from measures in ten adult volunteers. The estimated finger joint torques were calculated from measured right index fingertip force, joint postures, and anthropometry across 18 finger and wrist postures with the forearm muscles relaxed. The biomechanical model predicting passive finger joint torques included three extrinsic and three intrinsic finger muscles. The values for the predicted passive joint torques were much larger than the values calculated from the fingertip force and posture measures with an average RMS error of 7.6 N cm. Sensitivity analysis indicated that the predicted joint torques were most sensitive to passive force–length model parameters compared to anthropometric and postural parameters. Using Monte Carlo simulation, we determined a new set of values for the passive force–length model parameters that reduced the differences between the joint torques calculated from the two methods to an average RMS value of 0.5 N cm, a 94% average improvement of error from the torques predicted using the existing data. These new parameter values did vary across individuals; however, using an average set for the parameter values across subjects still reduced the average RMS difference to 0.8 N cm. These new parameters may improve dynamic modeling of the finger during sub-maximal force activities and are based on in vivo data rather than traditional in vitro data.     

Wrist and digital joint motion produce unique flexor tendon force and excursion in the canine forelimb

The force and excursion within the canine digital flexor tendons were measured during passive joint manipulations that simulate those used during rehabilitation after flexor tendon repair and during active muscle contraction, simulating the active rehabilitation protocol. Tendon force was measured using a small buckle placed upon the tendon while excursion was measured using a suture marker and video analysis method. Passive finger motion imposed with the wrist flexed resulted in dramatically lower tendon force (approximately 5 N) compared to passive motion imposed with the wrist extended (approximately 17 N). Lower excursions were seen at the level of the proximal interphalangeal joint with the wrist flexed (approximately 1.5 mm) while high excursion was observed when the wrist was extended or when synergistic finger and wrist motion were imposed (approximately 3.5 mm). Bivariate discriminant analysis of both force and excursion data revealed a natural clustering of the data into three general mechanical paradigms. With the wrist extended and with either one finger or four fingers manipulated, tendons experienced high loads of approximately 1500 g and high excursions of approximately 3.5 mm. In contrast, the same manipulations performed with the wrist flexed resulted in low tendon forces (4-8 N) and low tendon excursions of approximately 1.5 mm. Synergistic wrist and finger manipulation provided the third paradigm where tendon force was relatively low (approximately 4 N) but excursion was as high as those seen in the groups which were manipulated with the wrist extended. Active muscle contraction produced a modest tendon excursion (approximately 1 mm) and high or low tendon force with the wrist extended or flexed, respectively. These data provide the basis for experimentally testable hypotheses with regard to the factors that most significantly affect functional recovery after digital flexor tendon injury and define the normal mechanical operating characteristics of these tendons.     

Finger joint force minimization in pianists using optimization techniques

A numerical optimization procedure was used to determine finger positions that minimize and maximize finger tendon and joint force objective functions during piano play. A biomechanical finger model for sagittal plane motion, based on finger anatomy, was used to investigate finger tendon tensions and joint reaction forces for finger positions used in playing the piano. For commonly used piano key strike positions, flexor and intrinsic muscle tendon tensions ranged from 0.7 to 3.2 times the fingertip key strike force, while resultant inter-joint compressive forces ranged from 2 to 7 times the magnitude of the fingertip force. In general, use of a curved finger position, with a large metacarpophalangeal joint flexion angle and a small proximal interphalangeal joint flexion angle, reduces flexor tendon tension and resultant finger joint force.     

Estimation of finger muscle tendon tensions and pulley forces during specific sport-climbing grip techniques

The present work displayed the first quantitative data of forces acting on tendons and pulleys during specific sport-climbing grip techniques. A three-dimensional static biomechanical model was used to estimate finger muscle tendon and pulley forces during the "slope" and the "crimp" grip. In the slope grip the finger joints are flexed, and in the crimp grip the distal interphalangeal (DIP) joint is hyperextended while the other joints are flexed. The tendons of the flexor digitorum profundus and superficialis (FDP and FDS), the extensor digitorum communis (EDC), the ulnar and radial interosseus (UI and RI), the lumbrical muscle (LU) and two annular pulleys (A2 and A4) were considered in the model. For the crimp grip in equilibrium conditions, a passive moment for the DIP joint was taken into account in the biomechanical model. This moment was quantified by relating the FDP intramuscular electromyogram (EMG) to the DIP joint external moment. Its intensity was estimated at a quarter of the external moment. The involvement of this parameter in the moment equilibrium equation for the DIP joint is thus essential. The FDP-to-FDS tendon-force ratio was 1.75:1 in the crimp grip and 0.88:1 in the slope grip. This result showed that the FDP was the prime finger flexor in the crimp grip, whereas the tendon tensions were equally distributed between the FDP and FDS tendons in the slope grip. The forces acting on the pulleys were 36 times lower for A2 in the slope grip than in the crimp grip, while the forces acting on A4 were 4 times lower. This current work provides both an experimental procedure and a biomechanical model that allows estimation of tendon tensions and pulley forces crucial for the knowledge about finger injuries in sport climbing.     

The linear co-variance between joint muscle torques is not a generalized principle

In 1996, Gottlieb et al. [Gottlieb GL, Song Q, Hong D, Almeida GL, Corcos DM. Coordinating movement at two joints: A principle of linear covariance. J Neurophysiol 1996;75(4):1760–4] identified a linear co-variance between the joint muscle torques generated at two connected joints. The joint muscle torques changed directions and magnitudes in a synchronized and linear fashion and called it the principle of linear co-variance. Here we showed that this principle cannot hold for some class of movements. Neurologically normal subjects performed multijoint movements involving elbow and shoulder with reversal towards three targets in the sagittal plane without any constraints. The movement kinematics was calculated using the X and Y coordinates of the markers positioned over the joints. Inverse dynamics was used to calculate the joint muscle, interaction and net torques. We found that for the class of voluntary movements analyzed, the joint muscle torques of the elbow and the shoulder were not linearly correlated. The same was observed for the interaction torques. But, the net torques at both joints, i.e., the sum of the interaction and the joint muscle torques were linearly correlated. We showed that by decoupling the joint muscle torques, but keeping the net torques linearly correlated, the CNS was able to generate fast and accurate movements with straight fingertip paths. The movement paths were typical of the ones in which the joint muscle torques were linearly correlated.     

Finger Muscle Attachments for an OpenSim Upper-Extremity Model

We determined muscle attachment points for the index, middle, ring and little fingers in an OpenSim upper-extremity model. Attachment points were selected to match both experimentally measured locations and mechanical function (moment arms). Although experimental measurements of finger muscle attachments have been made, models differ from specimens in many respects such as bone segment ratio, joint kinematics and coordinate system. Likewise, moment arms are not available for all intrinsic finger muscles. Therefore, it was necessary to scale and translate muscle attachments from one experimental or model environment to another while preserving mechanical function. We used a two-step process. First, we estimated muscle function by calculating moment arms for all intrinsic and extrinsic muscles using the partial velocity method. Second, optimization using Simulated Annealing and Hooke-Jeeves algorithms found muscle-tendon paths that minimized root mean square (RMS) differences between experimental and modeled moment arms. The partial velocity method resulted in variance accounted for (VAF) between measured and calculated moment arms of 75.5% on average (range from 48.5% to 99.5%) for intrinsic and extrinsic index finger muscles where measured data were available. RMS error between experimental and optimized values was within one standard deviation (S.D) of measured moment arm (mean RMS error = 1.5 mm < measured S.D = 2.5 mm). Validation of both steps of the technique allowed for estimation of muscle attachment points for muscles whose moment arms have not been measured. Differences between modeled and experimentally measured muscle attachments, averaged over all finger joints, were less than 4.9 mm (within 7.1% of the average length of the muscle-tendon paths). The resulting non-proprietary musculoskeletal model of the human fingers could be useful for many applications, including better understanding of complex multi-touch and gestural movements.     

Reverse engineering finger extensor apparatus morphology from measured coupled interphalangeal joint angle trajectories - a generic 2D kinematic model

The interphalangeal (IP) finger joints coordinate as a mechanism when the deep flexor is active. This mechanism is created by the complex finger extensor apparatus (EA) - a confluence of end tendons of one or two extensors, radial and ulnar interossei, and lumbrical - which inserts as a single structure into both the middle and distal phalanges. Although the IP-coupling principle was well demonstrated more than half a century ago, the detailed relationship between EA morphology and IP coupling remains not well described. Main reasons are that by dissection the EA's fiber network loses functional consistency, while fibers becoming taut or slack beyond measuring resolutions complicate measuring functional fiber motions. To circumvent these difficulties, we present a two dimensional kinematic multi tendon-string EA model of fiber slackness and tautness through IP motion, including the retinacular and oblique retinacular EA ligaments. The model parameters were the strings' lengths and attachment points. The model's functional redundancies were resolved by individually interactively fitting model IP trajectories to previously measured IP trajectories of 68 fingers. All model trajectories accurately fitted their target IP trajectories for proximal interphalangeal (PIP) joint ranges smaller than 25° to 45°; about half accurately fitted over the entire IP range with the remaining half having maximum approximation errors between 3° to 12°, while all models again converged to target trajectories for full IP flexion. These accuracies suggest the model reflects real functional EA principles, with potential applications in biomechanical modeling, surgical reconstruction, rehabilitation, and prosthetic EA replacements.     

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.