Using EMG data to constrain optimization procedure improves finger tendon tension estimations during static fingertip force production

Determining tendon tensions of the finger muscles is crucial for the understanding and the rehabilitation of hand pathologies. Since no direct measurement is possible for a large number of finger muscle tendons, biomechanical modelling presents an alternative solution to indirectly evaluate these forces. However, the main problem is that the number of muscles spanning a joint exceeds the number of degrees of freedom of the joint resulting in mathematical under-determinate problems. In the current study, a method using both numerical optimization and the intra-muscular electromyography (EMG) data was developed to estimate the middle finger tendon tensions during static fingertip force production. The method used a numerical optimization procedure with the muscle stress squared criterion to determine a solution while the EMG data of three extrinsic hand muscles serve to enforce additional inequality constraints. The results were compared with those obtained with a classical numerical optimization and a method based on EMG only. The proposed method provides satisfactory results since the tendon tension estimations respected the mechanical equilibrium of the musculoskeletal system and were concordant with the EMG distribution pattern of the subjects. These results were not observed neither with the classical numerical optimization nor with the EMG-based method. This study demonstrates that including the EMG data of the three extrinsic muscles of the middle finger as inequality constraints in an optimization process can yield relevant tendon tensions with regard to individual muscle activation patterns, particularly concerning the antagonist muscles.     

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.     

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.     

Development of a novel MATLAB-based framework for implementing mechanical joint stability constraints within OpenSim musculoskeletal models

The Static Optimization (SO) solver in OpenSim estimates muscle activations and forces that only equilibrate applied moments. In this study, SO was enhanced through an open-access MATLAB interface, where calculated muscle activations can additionally satisfy crucial mechanical stability requirements. This Stability-Constrained SO (SCSO) is applicable to many OpenSim models and can potentially produce more biofidelic results than SO alone, especially when antagonistic muscle co-contraction is required to stabilize body joints. This hypothesis was tested using existing models and experimental data in the literature. Muscle activations were calculated by SO and SCSO for a spine model during two series of static trials (i.e. simulation 1 and 2), and also for a lower limb model (supplementary material 2). In simulation 1, symmetric and asymmetric flexion postures were compared, while in simulation 2, various external load heights were compared, where increases in load height did not change the external lumbar flexion moment, but necessitated higher EMG activations. During the tasks in simulation 1, the predicted muscle activations by SCSO demonstrated less average deviation from the EMG data (6.8% −7.5%) compared to those from SO (10.2%). In simulation 2, SO predicts constant muscle activations and forces, while SCSO predicts increases in the average activations of back and abdominal muscles that better match experimental data. Although the SCSO results are sensitive to some parameters (e.g. musculotendon stiffness), when considering the strategy of the central nervous system in distributing muscle forces and in activating antagonistic muscles, the assigned activations by SCSO are more biofidelic than SO.     

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.     

Estimating net lumbar sagittal plane moments from EMG data. The validity of calibration procedures.

In the present study the validity of EMG based methods to estimate the net moment working at the lumbar spine was investigated. Eight subjects performed a series of static and dynamic tasks. EMG was recorded from 8 locations over the back muscles. At the same time force platform and kinematic data for a linked segment analysis were collected. The net moment at the lumbar spine was calculated from the latter data and compared to EMG based estimates of the same moment. These estimates were derived from a linear regression between the EMG amplitudes and the net moments obtained during static ramp calibrations. It appeared that calibration in several postures, covering the range occurring in the tasks studied, and in a posture in the middle of this range, yielded estimates of the group averaged 10th, 50th, and 90th percentile of the net moments which were within 10% of the real value. The explained variance obtained in the calibration procedure proved not to be a good indicator of the validity of the procedure.     

Analysis of tendinous actuation in balancing the maximal fingertip force for normal and abnormal forefinger system

This work displayed the force capabilities of the musculoskeletal system of the forefinger under external loading. Different states of normal and pathological fingers are studied. We evaluated the impact of losing musculo-tendon unit strength capacities in terms of maximal output fingertip force and tendon tensions distribution. A biomechanical model for a static force analysis is developed through anatomical and kinematic studies. An optimisation approach is then used to determine tendon tension distribution when performing an isometric task. Furthermore, pathological fingers with common cases of injured flexors and extensors are analysed. The method of simulation for forefinger abnormities is described. Furthermore, the simulation results are interpreted.     

Analysis of tendinous actuation in balancing the maximal fingertip force for normal and abnormal forefinger system

This work displayed the force capabilities of the musculoskeletal system of the forefinger under external loading. Different states of normal and pathological fingers are studied. We evaluated the impact of losing musculo-tendon unit strength capacities in terms of maximal output fingertip force and tendon tensions distribution. A biomechanical model for a static force analysis is developed through anatomical and kinematic studies. An optimisation approach is then used to determine tendon tension distribution when performing an isometric task. Furthermore, pathological fingers with common cases of injured flexors and extensors are analysed. The method of simulation for forefinger abnormities is described. Furthermore, the simulation results are interpreted.     

Extension of a state-of-the-art optimization criterion to predict co-contraction

Most studies concerned with the prediction of muscle forces have tried to predict a physiologically reasonable, synergistic muscle behavior. In addition to the load sharing of synergistic muscles, co-contraction of antagonistic muscles also occurs. An extension to a standard quadratic criterion for the calculation of muscle forces is presented in this study. This extension however is not limited to quadratic optimization. The extension is applied to a planar, one degree of freedom model of the human knee. For this model an analytical solution is presented. With the extended criterion it was possible to predict and control the amount of co-contraction for the knee model. The enforced antagonistic muscle activity led to higher agonistic muscle activity. In the absence of an external load flexor and extensor muscles were activated. As a consequence the knee joint was preloaded. This might indicate that antagonistic muscle activity is generated to maintain or improve joint stability. In conclusion, this study presents a novel approach to predict co-contraction when using optimization techniques to determine muscle forces by introducing a shift parameter for the optimization criterion.     

An EMG-CT method using multiple surface electrodes in the forearm

Electromyography computed tomography (EMG-CT) method is proposed for visualizing the individual muscle activities in the human forearm. An EMG conduction model was formulated for reverse-estimation of muscle activities using EMG signals obtained with multi surface electrodes. The optimization process was calculated using sequential quadratic programming by comparing the estimated EMG values from the model with the measured values. The individual muscle activities in the deep region were estimated and used to produce an EMG tomographic image. For validation of the method, isometric contractions of finger muscles were examined for three subjects, applying a flexion load (4.9, 7.4 and 9.8 N) to the proximal interphalangeal joint of the middle finger. EMG signals in the forearm were recorded during the tasks using multiple surface electrodes, which were bound around the subject’s forearm. The EMG-CT method illustrates the distribution of muscle activities within the forearm. The change in amplitude and area of activated muscles can be observed. The normalized muscle activities of all three subjects appear to increase monotonically with increases in the load. Kinesiologically, this method was able to estimate individual muscle activation values and could provide a novel tool for studying hand function and development of an examination for evaluating rehabilitation.     

Motor control theories improve biomechanical model of the hand for finger pressing tasks

BackgroundBiomechanical models are a useful tool to estimate tendon tensions. Unfortunately, in previous fingers' models, each finger acts independently from the others. This is contradictory with hand motor control theories which show that fingers are functionally linked in order to balance the wrist/forearm joint with minimal tendon tensions. (i.e. principle of minimization of the secondary moments). We propose to adapt a hand biomechanical model according to this principle by including the wrist joint. We will determine whether the finger tendon tensions changed with the wrist joint added to the model.MethodsTwo models have been tested: one considering fingers independently (model A) and one with the fingers mechanically linked by the inclusion of the wrist balance (model B). A single set of data, additional results from the literature and in-vivo values have been used to compare the results.ResultsModel A corroborates previous results in the literature. Contrast results were obtained with model B, especially for the Ring and Little fingers. Different tendon tensions were obtained, particularly, in finger extensor muscles critical to balance the wrist.DiscussionWe discuss the biomechanical results in accordance with the hand/finger motor control theories. It appears that the wrist joint balance is critical for finger tendon tension estimation. When including the wrist joint into finger models, the tendon tension estimations agree well with the minimization of secondary moments and the force deficit.     

Use of antagonist muscle EMG in the assessment of neuromuscular health of the low back

Background

Non-specific low back pain (LBP) has been one of the most frequently occurring musculoskeletal problems. Impairment in the mechanical stability of the lumbar spine has been known to lower the safety margin of the spine musculature and can result in the occurrence of pain symptoms of the low back area. Previously, changes in spinal stability have been identified by investigating recruitment patterns of low back and abdominal muscles in laboratory experiments with controlled postures and physical activities that were hard to conduct in daily life. The main objective of this study was to explore the possibility of developing a reliable spine stability assessment method using surface electromyography (EMG) of the low back and abdominal muscles in common physical activities.

Methods

Twenty asymptomatic young participants conducted normal walking, plank, and isometric back extension activities prior to and immediately after maintaining a 10-min static upper body deep flexion on a flat bed. EMG data of the erector spinae, external oblique, and rectus abdominals were collected bilaterally, and their mean normalized amplitude values were compared between before and after the static deep flexion. Changes in the amplitude and co-contraction ratio values were evaluated to understand how muscle recruitment patterns have changed after the static deep flexion.

Results

Mean normalized amplitude of antagonist muscles (erector spinae muscles while conducting plank; external oblique and rectus abdominal muscles while conducting isometric back extension) decreased significantly (P < 0.05) after the 10-min static deep flexion. Normalized amplitude of agonist muscles did not vary significantly after deep flexion.

Conclusions

Results of this study suggest the possibility of using surface EMG in the evaluation of spinal stability and low back health status in simple exercise postures that can be done in non-laboratory settings. Specifically, amplitude of antagonist muscles was found to be more sensitive than agonist muscles in identifying changes in the spinal stability associated with the 10-min static deep flexion. Further research with various loading conditions and physical activities need to be performed to improve the reliability and utility of the findings of the current study.     

Support for a linear length-tension relation of the torso extensor muscles: An investigation of the length and velocity EMG-force relationships

This study investigated the hypothesis that the length-tension relation of the torso erectors would be linear, mirroring the observed linear increase in extension strength capability toward full flexion. The effect of torso extension velocity on the tension capability of these muscles was also investigated for common motion speeds. A myoelectric-based approach was used wherein a dynamic biomechanical model incorporating active and passive tissue characteristics provided muscle kinematic estimates during controlled sagittal plane extension motions. A double linear optimization formulation from the literature provided muscle tension estimates. The data of five male subjects supported the hypothesis of a linear length-tension relation toward full flexion for both the erector spinae and latissimus muscles. Velocity trends agreed with that predicted by Hill's exponential relation, although linear trends were found to fit the data almost as well. The results have implications for muscle tension estimation in biomechanical torso modeling, and suggest a possible low back pain injury mechanism through tissue strain while lifting in fully flexed postures.     

A regression model predicting isometric shoulder muscle activities from arm postures and shoulder joint moments

Tissue overloading is a major contributor to shoulder musculoskeletal injuries. Previous studies attempted to use regression-based methods to predict muscle activities from shoulder kinematics and shoulder kinetics. While a regression-based method can address co-contraction of the antagonist muscles as opposed to the optimization method, most of these regression models were based on limited shoulder postures. The purpose of this study was to develop a set of regression equations to predict the 10th percentile, the median, and the 90th percentile of normalized electromyography (nEMG) activities from shoulder postures and net shoulder moments. Forty participants generated various 3-D shoulder moments at 96 static postures. The nEMG of 16 shoulder muscles was measured and the 3-D net shoulder moment was calculated using a static biomechanical model. A stepwise regression was used to derive the regression equations. The results indicated the measured range of the 3-D shoulder moment in this study was similar to those observed during work requiring light physical capacity. The r² of all the regression equations ranged between 0.228 and 0.818. For the median of the nEMG, the average r² among all 16 muscles was 0.645, and the five muscles with the greatest r² were the three deltoids, supraspinatus, and infraspinatus. The results can be used by practitioners to estimate the range of the shoulder muscle activities given a specific arm posture and net shoulder moment.     

Measurement of distribution of maximum index-fingertip force in all directions at fingertip in flexion/extension plane

The purpose of the present study is to investigate whether distribution patterns of the maximum fingertip force in all directions from 0 deg to 360 deg around the index fingertip are the same among subjects. Distributions of the maximum index fingertip force were measured at four finger postures for five subjects (healthy males, ages 21 to 25). It became apparent that distribution patterns of the fingertip force were very similar among subjects, through the application of an analysis of variance (level of significance: 5%) to the measurement results. In the production of the maximum fingertip force, Valero-Cuevas et al. [1998, 2000] reported that patterns of control signals for driving muscle forces were common among subjects. The results of the present study indicate that patterns of maximum fingertip force are also similar among subjects. Therefore, the possibility is high that the static transfer characteristic for index fingers from input (i.e., control signals to muscles) to output (ie., the maximum fingertip force) is also common among subjects.     

Static optimization underestimates antagonist muscle activity at the glenohumeral joint: A musculoskeletal modeling study

Static optimization is commonly employed in musculoskeletal modeling to estimate muscle and joint loading; however, the ability of this approach to predict antagonist muscle activity at the shoulder is poorly understood. Antagonist muscles, which contribute negatively to a net joint moment, are known to be important for maintaining glenohumeral joint stability. This study aimed to compare muscle and joint force predictions from a subject-specific neuromusculoskeletal model of the shoulder driven entirely by measured muscle electromyography (EMG) data with those from a musculoskeletal model employing static optimization. Four healthy adults performed six sub-maximal upper-limb contractions including shoulder abduction, adduction, flexion, extension, internal rotation and external rotation. EMG data were simultaneously measured from 16 shoulder muscles using surface and intramuscular electrodes, and joint motion evaluated using video motion analysis. Muscle and joint forces were calculated using both a calibrated EMG-driven neuromusculoskeletal modeling framework, and musculoskeletal model simulations that employed static optimization. The EMG-driven model predicted antagonistic muscle function for pectoralis major, latissimus dorsi and teres major during abduction and flexion; supraspinatus during adduction; middle deltoid during extension; and subscapularis, pectoralis major and latissimus dorsi during external rotation. In contrast, static optimization neural solutions showed little or no recruitment of these muscles, and preferentially activated agonistic prime movers with large moment arms. As a consequence, glenohumeral joint force calculations varied substantially between models. The findings suggest that static optimization may under-estimate the activity of muscle antagonists, and therefore, their contribution to glenohumeral joint stability.     

A calibrated EMG-informed neuromusculoskeletal model can appropriately account for muscle co-contraction in the estimation of hip joint contact forces in people with hip osteoarthritis

Abnormal hip joint contact forces (HJCF) are considered a primary mechanical contributor to the progression of hip osteoarthritis (OA). Compared to healthy controls, people with hip OA often present with altered muscle activation patterns and greater muscle co-contraction, both of which can influence HJCF. Neuromusculoskeletal (NMS) modelling is non-invasive approach to estimating HJCF, whereby different neural control solutions can be used to estimate muscle forces. Static optimisation, available within the popular NMS modelling software OpenSim, is a commonly used neural control solution, but may not account for an individual’s unique muscle activation patterns and/or co-contraction that are often evident in pathological population. Alternatively, electromyography (EMG)-assisted neural control solutions, available within CEINMS software, have been shown to account for individual activation patterns in healthy people. Nonetheless, their application in people with hip OA, with conceivably greater levels of co-contraction, is yet to be explored. The aim of this study was to compare HJCF estimations using static optimisation (in OpenSim) and EMG-assisted (in CEINMS) neural control solutions during walking in people with hip OA. EMG-assisted neural control solution was more consistent with both EMG and joint moment data than static optimisation, and also predicted significantly higher HJCF peaks (p < 0.001). The EMG-assisted neural control solution also accounted for more muscle co-contraction than static optimisation (p = 0.03), which probably contributed to these higher HJCF peaks. Findings suggest that the EMG-assisted neural control solution may estimate more physiologically plausible HJCF than static optimisation in a population with high levels of co-contraction, such as hip OA.