An open-source model and solution method to predict co-contraction in the finger

A novel open-source biomechanical model of the index finger with an electromyography (EMG)-constrained static optimization solution method are developed with the goal of improving co-contraction estimates and providing means to assess tendon tension distribution through the finger. The Intrinsic model has four degrees of freedom and seven muscles (with a 14 component extensor mechanism). A novel plugin developed for the OpenSim modelling software applied the EMG-constrained static optimization solution method. Ten participants performed static pressing in three finger postures and five dynamic free motion tasks. Index finger 3D kinematics, force (5, 15, 30 N), and EMG (4 extrinsic muscles and first dorsal interosseous) were used in the analysis. The Intrinsic model predicted co-contraction increased by 29% during static pressing over the existing model. Further, tendon tension distribution patterns and forces, known to be essential to produce finger action, were determined by the model across all postures. The Intrinsic model and custom solution method improved co-contraction estimates to facilitate force propagation through the finger. These tools improve our interpretation of loads in the finger to develop better rehabilitation and workplace injury risk reduction strategies.     

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.     

Finger joint coordination during tapping

We investigated finger joint coordination during tapping by characterizing joint kinematics and torques in terms of muscle activation patterns and energy profiles. Six subjects tapped with their index finger on a computer keyswitch as if they were typing on the middle row of a keyboard. Fingertip force, keyswitch position, kinematics of the metacarpophalangeal (MCP) and the proximal and distal interphalangeal (IP) joints, and intramuscular electromyography of intrinsic and extrinsic finger muscles were measured simultaneously. Finger joint torques were calculated based on a closed-form Newton–Euler inverse dynamic model of the finger. During the keystroke, the MCP joint flexed and the IP joints extended before and throughout the loading phase of the contact period, creating a closing reciprocal motion of the finger joints. As the finger lifted, the MCP joint extended and the interphalangeal (IP) joints flexed, creating an opening reciprocal motion. Intrinsic finger muscle and extrinsic flexor activities both began after the initiation of the downward finger movement. The intrinsic finger muscle activity preceded both the IP joint extension and the onset of extrinsic muscle activity. Only extrinsic extensor activity was present as the finger was lifted. While both potential energy and kinetic energy are present and large enough to overcome the work necessary to press the keyswitch, the motor control strategies utilize the muscle forces and joint torques to ensure a successful keystroke.     

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.     

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.     

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.     

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.     

A 3D visualization and simulation of the individual human jaw

A new biomechanical three-dimensional (3D) model for the human mandible based on computer-generated virtual model is proposed. Using maps obtained from the special kinds of photos of the face of the real subject, it is possible to attribute personality to the virtual character, while computer animation offers movements and characteristics within the confines of space and time of the virtual world. A simple two-dimensional model of the jaw cannot explain the biomechanics, where the muscular forces through occlusion and condylar surfaces are in the state of 3D equilibrium. In the model all forces are resolved into components according to a selected coordinate system. The muscular forces act on the jaw, along with the necessary force level for chewing as some kind of mandible balance, preventing dislocation and loading of nonarticular tissues. In the work is used new approach to computer-generated animation of virtual 3D characters (called "Body SABA"), using in one object package of minimal costs and easy for operation.     

A demonstration of validity of 3-D video motion analysis method for measuring finger flexion and extension

This study demonstrates the validity of using 3-D video motion analysis to measure hand motion. Several researchers have devised ingenious methods to study normal and abnormal hand movements. Although very helpful, these earlier studies are static representations of a dynamic phenomenon. Despite the many studies of hand motion using scientifically impeccable techniques, little is known about digital motion, and there are still few researchers investigating dynamic three-dimensional motion of the hand. Results from a three-camera video motion analysis system were compared to those from the "gold standard", 2-D lateral view fluoroscopy. We used these two methods to record hand motion simultaneously during unrestricted flexion and extension of the index finger of the dominant hand in 6 neurologically normal, healthy volunteers. After collection and post-processing, the waveforms of the PIP, DIP and MCP joint angles were compared using the adjusted coefficient of multiple determination (R2(a), or CMD). The mean CMD values for the MCP, PIP and DIP joint angle waveforms were 0.96, 0.98 and 0.94, respectively, suggesting a close similarity between motion of comparable joints analyzed by the 2-D and 3-D methods. This shows that the method of 3-D motion analysis is capable of accurately quantifying digital joint motion. It is anticipated that 3-D motion analysis, in addition to being used as a research tool, will also have clinical applications such as surgical planning in neuromuscular disorders and the documentation of abnormal motion in many other pathological hand conditions.     

Three dimensional model of the human mandible

A new biomechanical three-dimensional (3D) model for the human mandible is proposed. A simple two-dimensional model cannot explain the biomechanics of the human mandible, where muscular forces through occlusion and condylar surfaces are in a state of dynamical 3D equilibrium. All forces are resolved into components according to a selected coordinate system. The muscular forces, which during clenching act on the jaw, along with the necessary force level for chewing, also act as some kind of stabilizers of the mandibular condyles preventing dislocation and loading of nonarticular tissues.     

Simple and complex models for studying muscle function in walking

While simple models can be helpful in identifying basic features of muscle function, more complex models are needed to discern the functional roles of specific muscles in movement. In this paper, two very different models of walking, one simple and one complex, are used to study how muscle forces, gravitational forces and centrifugal forces (i.e. forces arising from motion of the joints) combine to produce the pattern of force exerted on the ground. Both the simple model and the complex one predict that muscles contribute significantly to the ground force pattern generated in walking; indeed, both models show that muscle action is responsible for the appearance of the two peaks in the vertical force. The simple model, an inverted double pendulum, suggests further that the first and second peaks are due to net extensor muscle moments exerted about the knee and ankle, respectively. Analyses based on a much more complex, muscle-actuated simulation of walking are in general agreement with these results; however, the more detailed model also reveals that both the hip extensor and hip abductor muscles contribute significantly to vertical motion of the centre of mass, and therefore to the appearance of the first peak in the vertical ground force, in early single-leg stance. This discrepancy in the model predictions is most probably explained by the difference in model complexity. First, movements of the upper body in the sagittal plane are not represented properly in the double-pendulum model, which may explain the anomalous result obtained for the contribution of a hip-extensor torque to the vertical ground force. Second, the double-pendulum model incorporates only three of the six major elements of walking, whereas the complex model is fully 3D and incorporates all six gait determinants. In particular, pelvic list occurs primarily in the frontal plane, so there is the potential for this mechanism to contribute significantly to the vertical ground force, especially during early single-leg stance when the hip abductors are activated with considerable force.     

Index finger position fluctuations reflect multi-muscle coordination

We hypothesized that movement fluctuations in the index finger reflect the integrated result of the coordination of multiple muscles because index finger movements are determined by the cooperation of multiple muscles spanning the metacarpophalangeal (MCP) joint. To evaluate this hypothesis, the aim of the present study was to examine the fluctuations of the index finger in abduction-adduction and extension-flexion directions during a position-holding task using two laser displacement sensors. Eleven healthy men maintained their index finger position while supporting a load at 5% of the maximal voluntary contraction force. To maintain the position of the index finger, displacement of the index finger in the abduction-adduction and extension-flexion directions was measured from a distance with two laser displacement sensors that were positioned to the lateral side of and above the index finger. The index finger movements fluctuated around the target position in not only the abduction-adduction direction but also the extension-flexion direction. The path length of finger displacement and the standard deviation of finger acceleration were significantly greater in the extension-flexion direction than in the abduction-adduction direction. These results suggest that the index finger movements quantified by two laser displacement sensors reflect the coordination of multiple muscles spanning the MCP joint.     

Development of a dynamic index finger and thumb model to study impairment

Modeling of the human hand provides insight for explaining deficits and planning treatment following injury. Creation of a dynamic model, however, is complicated by the actions of multi-articular tendons and their complex interactions with other soft tissues in the hand. This study explores the creation of a musculoskeletal model, including the thumb and index finger, to explore the effects of muscle activation deficits. The OpenSim model utilizes physiological axes of rotation at all joints, passive joint torques, and appropriate moment arms. The model was validated through comparison with kinematic and kinetic experimental data. Simulated fingertip forces resulting from modeled musculotendon loading largely fell within one standard deviation of experimental ranges for most index finger and thumb muscles, although agreement in the sagittal plane was generally better than for the coronal plane. Input of experimentally obtained electromyography data produced the expected simulated finger and thumb motion. Use of the model to predict the effects of activation deficits on pinch force production revealed that the intrinsic muscles, especially first dorsal interosseous (FDI) and adductor pollicis (ADP), had a substantial impact on the resulting fingertip force. Reducing FDI activation, such as might occur following stroke, altered fingertip force direction by up to 83° for production of a dorsal fingertip force; reducing ADP activation reduced force production in the thumb by up to 62%. This validated model can provide a means for evaluating clinical interventions.     

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.     

A demonstration of the validity of a 3-D video motion analysis method for measuring finger flexion and extension

This study demonstrates the validity of using 3-D video motion analysis to measure hand motion. Several researchers have devised ingenious methods to study normal and abnormal hand movements. Although very helpful, these earlier studies are static representations of a dynamic phenomenon. Despite the many studies of hand motion using scientifically impeccable techniques, little is known about digital motion, and there are still few researchers investigating dynamic three-dimensional motion of the hand. Results from a three-camera video motion analysis system were compared to those from the “gold standard”, 2-D lateral view fluoroscopy. We used these two methods to record hand motion simultaneously during unrestricted flexion and extension of the index finger of the dominant hand in 6 neurologically normal, healthy volunteers. After collection and post-processing, the waveforms of the PIP, DIP and MCP joint angles were compared using the adjusted coefficient of multiple determination (R²_a, or CMD). The mean CMD values for the MCP, PIP and DIP joint angle waveforms were 0.96, 0.98 and 0.94, respectively, suggesting a close similarity between motion of comparable joints analyzed by the 2-D and 3-D methods. This shows that the method of 3-D motion analysis is capable of accurately quantifying digital joint motion.

It is anticipated that 3-D motion analysis, in addition to being used as a research tool, will also have clinical applications such as surgical planning in neuromuscular disorders and the documentation of abnormal motion in many other pathological hand conditions.     

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.     

A mode hypothesis for finger interaction during multi-finger force-production tasks

 Finger forces are known to change involuntarily during multi-finger force-production tasks, even when a finger's involvement in a task is not consciously changed (the enslaving effect). Furthermore, during maximal force-production (MVC) tests, the force produced by a given finger in a multi-finger task is smaller than the force generated by this finger in its single-finger MVC test (the force-deficit effect). A set of hypothetical control variables – modes – is introduced. Modes can be estimated based on individual finger forces during single-finger MVC tests. We show that a simple formal model based on modes with only one free parameter accounts for finger forces during a variety of multi-finger MVC tests. The free parameter accounts for the force-deficit effect, and its value depends only on the number of explicitly involved fingers. This approach offers a simple framework for the analysis of finger interaction during multi-finger actions. Received: 7 December 2001 / Accepted in revised form: 17 April 2002 Correspondence to: F. Danion (e-mail: danion@laps.univ-mrs.fr, Tel.: +33-491-172265, Fax: +33-491-172252)     

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.     

Agreement of measured and calculated muscle activity during highly dynamic movements modelled with a spherical knee joint

The inclusion of muscle forces into the analysis of joint contact forces has improved their accuracy. But it has not been validated if such force and activity calculations are valid during highly dynamic multidirectional movements. The purpose of this study was to validate calculated muscle activation of a lower extremity model with a spherical knee joint for running, sprinting and 90°-cutting. Kinematics, kinetics and lower limb muscle activation of ten participants were investigated in a 3D motion capture setup including EMG. A lower extremity rigid body model was used to calculate the activation of these muscles with an inverse dynamics approach and a cubic cost function. Correlation coefficients were calculated to compare measured and calculated activation. The results showed good correlation of the modelled and calculated data with a few exceptions. The highest average correlations were found during walking (r = 0.81) and the lowest during cutting (r = 0.57). Tibialis anterior had the lowest average correlation (r = 0.33) over all movements while gastrocnemius medius had the highest correlation (r = 0.9). The implementation of a spherical knee joint increased the agreement between measured and modelled activation compared to studies using a hinge joint knee. Although some stabilizing muscles showed low correlations during dynamic movements, the investigated model calculates muscle activity sufficiently.