Dependence of jumping performance on muscle properties when humans use only calf muscles for propulsion

A hybrid framework to predict ski jumping forces by combining data-driven pose estimation and model-based force calculation

The aim of this paper is to propose a hybrid framework that combines a data-driven pose estimation with model-based force calculation in order to predict the ski jumping force from a recorded motion video. A skeletal model consisting of five joints (ear, hip, knee, ankle, and toe) and four rigid segments (head/arm/trunk or HAT, thigh, shank, and foot) connecting each joint is developed. The joint forces are calculated from the dynamic equilibrium equations, which requires the time history of joint coordinates. They are estimated from a recorded motion video using a deep neural network for pose estimation trained with human motion data. Joint coordinates can be obtained by the proposed deep neural network directly from images of jumping motion without using any markers. The validity and usefulness of the proposed method are confirmed in lab experiments. Further, our method is practically applicable to the study in a real competition environment because it is not required to attach any sensor or marker to athletes.Highlights A method to predict the ski jumping force from a recorded motion video is proposed.It combines a data-driven pose estimation with a model-based force calculation.The proposed method does not require any markers and sensors to be attached to athletes.In a laboratory environment, the relative error in the maximum jumping force is less than 7%.The method can be easily applied to a field study in a real competition environment.

Effect of Concurrent Power Training and High-Intensity Interval Cycling on Muscle Morphology and Performance

ABSTRACT

Spiliopoulou, P, Zaras, N, Methenitis, S, Papadimas, G, Papadopoulos, C, Bogdanis, GC, and Terzis, G. Effect of concurrent power training and high-intensity interval cycling on muscle morphology and performance. J Strength Cond Res 35(9): 2464-2471, 2021-The aim of the study was to examine the effect of performing high-intensity interval cycling on muscle morphology and performance immediately after power training (PT). Twenty healthy female physical education students were assigned into 2 training groups. One group performed PT, and the other group performed the same PT followed by high-intensity interval aerobic training on a cycle ergometer (PTC). Training was performed 3 days per week for 6 weeks. Countermovement jump (CMJ) height and CMJ power, half-squat maximal strength (1 repetition maximum), maximum aerobic power, vastus lateralis muscle fiber composition, and cross-sectional area (CSA) were evaluated before and after the intervention. Countermovement jump height increased after PT (10.1 ± 6.6%, p = 0.002) but not after PTC (-5.1 ± 10.5%, p = 0.099), with significant difference between groups (p = 0.001). Countermovement jump power increased after PT (4.5 ± 4.9%, p = 0.021) but not after PTC (-2.4 ± 6.4, p = 0.278), with significant difference between groups (p = 0.017). One repetition maximum increased similarly in both groups. Muscle fiber composition was not altered after either PT or PTC. Vastus lateralis muscle fiber CSA increased significantly and similarly after both PT (I: 16.9 ± 16.2%, p = 0.035, ΙΙΑ: 12.7 ± 10.9%, p = 0.008,ΙΙΧ: 15.5 ± 17.1%, p = 0.021) and PTC (Ι: 18.0 ± 23.7%, p = 0.033,ΙΙΑ: 18.2 ± 11.4%, p = 0.001,ΙΙΧ: 25.5 ± 19.6%, p = 0.003). These results suggest that the addition of high-intensity interval cycling to PT inhibits the anticipated increase in jumping performance induced by PT per se. This inhibition is not explained by changes in muscle fiber type composition or vastus lateralis muscle fiber CSA adaptations.

Lower extremity joints and their contributions to whole limb extension

Lower extremity multi-joint strength curves tend not to evaluate individual joint contributions to endpoint force in maximum effort isometric whole limb extension. Therefore, the purpose of this study was to measure the contribution of the hip, knee, and ankle to vertical ground reaction force in maximum effort isometric whole limb extension at various postures. An effect of posture on the contributions of the hip, knee, and ankle to vertical ground reaction force was found (F_(3,96) = 85.31, p < 0.0001; F_(3,96) = 21.32, p < 0.0001; F_(3,96) = 130.61, p < 0.0001 for the hip, knee, and ankle, respectively). The hip and knee contributed most to vertical endpoint force when the lower limb was in a flexed posture, and their contributions decreased when posture was extended. Conversely, the ankle contributed least when the limb was flexed, but its contribution increased as posture was changed from flexed to more extended. In comparison to recent research involving induced acceleration analysis, it appears that the hip, knee, and ankle utilize the same force allocation strategy in multi-joint maximum effort isometric leg extensions and activities of daily living.

A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful

The ultimate goal of most neuromusculoskeletal modeling research is to improve the treatment of movement impairments. However, even though neuromusculoskeletal models have become more realistic anatomically, physiologically, and neurologically over the past 25 years, they have yet to make a positive impact on the design of clinical treatments for movement impairments. Such impairments are caused by common conditions such as stroke, osteoarthritis, Parkinson’s disease, spinal cord injury, cerebral palsy, limb amputation, and even cancer. The lack of clinical impact is somewhat surprising given that comparable computational technology has transformed the design of airplanes, automobiles, and other commercial products over the same time period. This paper provides the author’s personal perspective for how neuromusculoskeletal models can become clinically useful. First, the paper motivates the potential value of neuromusculoskeletal models for clinical treatment design. Next, it highlights five challenges to achieving clinical utility and provides suggestions for how to overcome them. After that, it describes clinical, technical, collaboration, and practical needs that must be addressed for neuromusculoskeletal models to fulfill their clinical potential, along with recommendations for meeting them. Finally, it discusses how more complex modeling and experimental methods could enhance neuromusculoskeletal model fidelity, personalization, and utilization. The author hopes that these ideas will provide a conceptual blueprint that will help the neuromusculoskeletal modeling research community work toward clinical utility.

A Review of Forward-Dynamics Simulation Models for Predicting Optimal Technique in Maximal Effort Sporting Movements

The identification of optimum technique for maximal effort sporting tasks is one of the greatest challenges within sports biomechanics. A theoretical approach using forward-dynamics simulation allows individual parameters to be systematically perturbed independently of potentially confounding variables. Each study typically follows a four-stage process of model construction, parameter determination, model evaluation, and model optimization. This review critically evaluates forward-dynamics simulation models of maximal effort sporting movements using a dynamical systems theory framework. Organismic, environmental, and task constraints applied within such models are critically evaluated, and recommendations are made regarding future directions and best practices. The incorporation of self-organizational processes representing movement variability and “intrinsic dynamics” remains limited. In the future, forward-dynamics simulation models predicting individual-specific optimal techniques of sporting movements may be used as indicative rather than prescriptive tools within a coaching framework to aid applied practice and understanding, although researchers and practitioners should continue to consider concerns resulting from dynamical systems theory regarding the complexity of models and particularly regarding self-organization processes.

Foot structure is correlated with performance in a single-joint jumping task

Variability in musculoskeletal structure has the potential to influence locomotor function. It has been shown, for example, that sprinters have smaller Achilles tendon moment arms and longer toes than non-sprinters, and toe length has been found to correlate with toe flexor work in running humans. These findings suggest that interindividual variation in human foot structure allows for function that is adapted to various motor tasks. The purpose of this study was to test for correlations between foot anthropometry and single-joint maximal-height jumping performance. Ten male subjects performed static jumps using only their ankles for propulsion. Several anthropometric measures were taken. Bivariate correlation analyses were performed between all anthropometric variables and the average jump height for each subject. Results showed that the best jumpers had longer lateral heel lengths (r=0.871; p=0.001) and longer toes (r=0.712; p=0.021). None of the other anthropometric variables (stature, mass, lower extremity lengths) measured were found to correlate significantly with jump height. A factor analysis was performed to investigate whether some underlying feature related to body stature could explain jumping performance. Taller subjects did not necessarily jump higher. Specific variations in foot structure, unrelated to other general stature measures, were associated with performance in this single-joint jumping task.

Muscle and Limb Mechanics

Understanding of the musculoskeletal system has evolved from the collection of individual phenomena in highly selected experimental preparations under highly controlled and often unphysiological conditions. At the systems level, it is now possible to construct complete and reasonably accurate models of the kinetics and energetics of realistic muscles and to combine them to understand the dynamics of complete musculoskeletal systems performing natural behaviors. At the reductionist level, it is possible to relate most of the individual phenomena to the anatomical structures and biochemical processes that account for them. Two large challenges remain. At a systems level, neuroscience must now account for how the nervous system learns to exploit the many complex features that evolution has incorporated into muscle and limb mechanics. At a reductionist level, medicine must now account for the many forms of pathology and disability that arise from the many diseases and injuries to which this highly evolved system is inevitably prone. © 2017 American Physiological Society. Compr Physiol 7:429-462, 2017.

Computational model of maximal-height single-joint jumping predicts bouncing as an optimal strategy

Maximal-height single-joint jumping, in which only the ankle muscles are used for propulsion, is a useful paradigm for joint-specific investigation of the mechanisms underlying optimal performance. In this study, we used a combination of computational modeling and experiments to determine the optimal strategy for this task. We hypothesized that our computer simulation and subjects would use a countermovement in order to maximize jump height. Our model was actuated by only a lumped plantarflexor and a lumped dorsiflexor, and we simulated maximal-height jumping using parameter optimization to determine the control excitations driving these muscles. Experimental data were collected from eight subjects who wore braces to limit knee motion during jumps. The model did not jump as high as the subjects did, but its jump height (12.8 cm) was similar to that found for subjects, 16.3±4.6 cm. The model jumped highest when it "bounced" by executing several countermovements in succession. Four of the subjects jumped highest when they also bounced; these subjects were also the highest jumpers and they bounced at 2.53±0.47 Hz, a value similar to that employed by the computational model, 2.78 Hz. The other four subjects, who failed to jump highest when bouncing, bounced at only 1.46±0.45 Hz when they attempted to do so. Simulation results indicated that subjects who used a bouncing strategy to record their highest jump made use of mechanical resonance to facilitate elastic energy storage in the Achilles tendon. Simulation results also showed that multiple bounces allowed the model to reach an optimal state in which potential energy was maximized prior to the final pushoff.

Sensitivity of a Hill-based muscle model to perturbations in model parameters

Musculoskeletal simulations of human movement commonly use Hill muscle models to predict muscle forces, but their sensitivity to model parameter values is not well understood. The purpose of this study was to evaluate muscle model sensitivity to perturbations in 14 Hill muscle model parameters in forward dynamic simulations of running and walking by varying each by +/-50%. Three evaluations of the muscle model were performed based on: (1) calculating the sensitivity of the muscle model only, (2) determining the continuous partial derivatives of the muscle equations with respect to each parameter, and (3) evaluating the effects on the running and walking simulations. Model evaluations were found to be very sensitive (percent change in outputs greater than parameter perturbation) to parameters defining the series elastic component (tendon), force-length curve of the contractile element and maximum isometric force. For some parameters, the range of literature values was larger than the model sensitivity. Model evaluations were insensitive to parameters defining the parallel elastic element, force-velocity curve of the contractile element and muscle activation time constants. The derivative method provided similar results, but also provided a generic, continuous equation that can easily be applied to other motions. The sensitivities of the running and walking simulations were reduced compared to the sensitivity of the muscle model alone. Results demonstrate the importance of evaluating sensitivity of a musculoskeletal simulation in a controlled manner and provide an indication of which parameters must be selected most carefully based on the sensitivity of a given movement.

Longer moment arm results in smaller joint moment development, power and work outputs in fast motions

Effects of moment arm length on kinetic outputs of a musculoskeletal system (muscle force development, joint moment development, joint power output and joint work output) were evaluated using computer simulation. A skeletal system of the human ankle joint was constructed: a lower leg segment and a foot segment were connected with a hinge joint. A Hill-type model of the musculus soleus (m. soleus), consisting of a contractile element and a series elastic element, was attached to the skeletal system. The model of the m. soleus was maximally activated, while the ankle joint was plantarflexed/dorsiflexed at a variation of constant angular velocities, simulating isokinetic exercises on a muscle testing machine. Profiles of the kinetic outputs (muscle force development, joint moment development, joint power output and joint work output) were obtained. Thereafter, the location of the insertion of the m. soleus was shifted toward the dorsal/ventral direction by 1cm, which had an effect of lengthening/shortening the moment arm length, respectively. The kinetic outputs of the musculoskeletal system during the simulated isokinetic exercises were evaluated with these longer/shorter moment arm lengths. It was found that longer moment arm resulted in smaller joint moment development, smaller joint power output and smaller joint work output in the larger plantarflexion angular velocity region (>120 degrees/s). This is because larger muscle shortening velocity was required with longer moment arm to achieve a certain joint angular velocity. Larger muscle shortening velocity resulted in smaller muscle force development because of the force-velocity relation of the muscle. It was suggested that this phenomenon should be taken into consideration when investigating the joint moment-joint angle and/or joint moment-joint angular velocity characteristics of experimental data.

Computer modeling and simulation of human movement

Recent interest in using modeling and simulation to study movement is driven by the belief that this approach can provide insight into how the nervous system and muscles interact to produce coordinated motion of the body parts. With the computational resources available today, large-scale models of the body can be used to produce realistic simulations of movement that are an order of magnitude more complex than those produced just 10 years ago. This chapter reviews how the structure of the neuromusculoskeletal system is commonly represented in a multijoint model of movement, how modeling may be combined with optimization theory to simulate the dynamics of a motor task, and how model output can be analyzed to describe and explain muscle function. Some results obtained from simulations of jumping, pedaling, and walking are also reviewed to illustrate the approach.

A control theoretic model of the forearm

In this paper, a control theoretic model of the forearm is developed and analyzed, and a computational method for predicting muscle activations necessary to generate specified motions is described. A detailed geometric model of the forearm kinematics, including the carrying angle and models of how the biceps and the supinator tendons wrap around the bones, is used. Also, including a dynamics model, the final model is a system of differential equations where the muscle activations play the role of control signals. Due to the large number of muscles, the problem of finding muscle activations is redundant, and this problem is solved by an optimization procedure. The computed muscle activations for ballistic movements clearly recaptures the triphasic ABC (Activation-Braking-Clamping) pattern. It is also transparent, from the muscle activation patterns, how the muscles cooperate and counteract in order to accomplish desired motions. A comparison with previously reported experimental data is included and the model predictions can be seen to be partially in agreement with the experimental data.

Effects of Neuromuscular Strength Training on Vertical Jumping Performance— A Computer Simulation Study

The purpose of this study was twofold: (a) to systematically investigate the effect of altering specific neuromuscular parameters on maximum vertical jump height, and (b) to systematically investigate the effect of strengthening specific muscle groups on maximum vertical jump height. A two-dimensional musculoskeletal model which consisted of four rigid segments, three joints, and six Hill-type muscle models, representing the six major muscles and muscle groups in the lower extremity that contribute to jumping performance, was trained systematically. Maximum isometric muscle force, maximum muscle shortening velocity, and maximum muscle activation, which were manipulated to simulate the effects of strength training, all had substantial effects on jumping performance. Part of the increase in jumping performance could be explained solely by the interaction between the three neuromuscular parameters. It appeared that the most effective way to improve jumping performance was to train the knee extensors among all lower extremity muscles. For the model to fully benefit from any training effects of the neuromuscular system, it was necessary to continue to reoptimize the muscle coordination, in particular after the strength training sessions that focused on increasing maximum isometric muscle force.

A Dynamic Optimization Solution for Vertical Jumping in Three Dimensions

A three-dimensional model of the human body is used to simulate a maximal vertical jump. The body is modeled as a 10-segment, 23 degree-of-freedom (dof), mechanical linkage, actuated by 54 muscles. Six generalized coordinates describe the position and orientation of the pelvis relative to the ground; the remaining nine segments branch in an open chain from the pelvis. The head, arms, and torso (HAT) are modeled as a single rigid body. The HAT articulates with the pelvis via a 3 dof ball-and-socket joint. Each hip is modeled as a 3 dof ball-and-socket joint, and each knee is modeled as a 1 dof hinge joint. Each foot is represented by a hindfoot and toes segment. The hindfoot articulates with the shank via a 2 dof universal joint, and the toes articulate with the hindfoot via a 1 dof hinge joint. Interaction of the feet with the ground is modeled using a series of spring-damper units placed under the sole of each foot. The path of each muscle is represented by either a series of straight lines or a combination of straight lines and space curves. Each actuator is modeled as a three-element, Hill-type muscle in series with tendon. A first-order process is assumed to model muscle excitation-contraction dynamics. Dynamic optimization theory is used to calculate the pattern of muscle excitations that produces a maximal vertical jump. Quantitative comparisons between model and experiment indicate that the model reproduces the kinematic, kinetic, and muscle-coordination patterns evident when humans jump to their maximum achievable heights.

Dynamics of force and muscle stimulation in human vertical jumping

PURPOSE

The purpose of this study was to gain insight into the importance of stimulation dynamics for force development in human vertical jumping.

METHODS

Maximum height squat jumps were performed by 21 male subjects. As a measure of signal dynamics, rise time (RT) was used, i.e., the time taken by the signal to increase from 10% to 90% of its peak value. RT were calculated for time histories of smoothed rectified electromyograms (SREMG) of seven lower extremity muscles, net moments about hip, knee, and ankle joints, and components of the ground reaction force vector.

RESULTS

Average RT values were 105-143 ms for SREMG signals, 90-112 ms for joint moments, and 120 ms for the vertical component of the ground reaction force (Fz). A coefficient of linear correlation of 0.88 was found between RT of SREMG of m. gluteus maximus (GLU) and RT of Fz. To explain this correlation, it was speculated that for an effective transfer from joint extensions to vertical motion of the center of mass (CM), the motion of CM needs a forward component during the push-off. Given the starting position, only the hip extensor muscles are able to generate such a forward acceleration of CM. To preserve the forward motion of CM, RT of knee and ankle joint moments need to be adjusted to RT of the hip joint moment. Thus, the greater RT of the hip joint moment and RT of GLU-SREMG, the greater RT of Fz.

CONCLUSIONS

Overall, it was concluded that the time it takes to develop muscle stimulation has a substantial effect on the dynamics of force development in vertical jumping, and that this effect should not be neglected in studies of the control of explosive movements.

Moment arms and lengths of human upper limb muscles as functions of joint angles

Modeling of musculoskeletal structures requires accurate data on anatomical parameters such as muscle lengths (MLs), moment arms (MAs) and those describing the upper limb position. Using a geometrical model of planar arm movements with three degrees of freedom, we present, in an analytical form, the available information on the relationship between MAs and MLs and joint angles for thirteen human upper limb muscles. The degrees of freedom included are shoulder flexion/extension, elbow flexion/extension, and either wrist flexion/extension (the forearm in supination) or radial/ulnar deviation (the forearm in mid-pronation). Previously published MA/angle curves were approximated by polynomials. ML/angle curves were obtained by combining the constant values of MLs (defined by the distance between the origin and insertion points for a specific upper limb position) with a variable part obtained by multiplying the MA (joint radius) and the joint angle. The MAs of the prime wrist movers in radial/ulnar deviation were linear functions of the joint angle (R2 > or = 0.9954), while quadratic polynomials accurately described their MAs during wrist flexion/extensions. The relationship between MAs and the elbow angle was described by 2nd, 3rd or 5th-order polynomials (R2 > or = 0.9904), with a lesser quality of fit for the anconeus (R2 = 0.9349). In the full range of angular displacements, the length of wrist, elbow and shoulder muscles can change by 8.5, 55 and 200%, respectively.

Estimating the contribution of muscles to joint torque based on motor-unit activity

Because most joints in the human arm are crossed by a number of muscles which exceeds the number of degrees of freedom for those joints, the motor system can use a variety of muscle activation patterns for the same torque in each joint. We have developed a mode to estimate the contribution of individual muscles to the total torque in a joint based on intramuscular EMG recordings. EMG activity recorded with surface electrodes may be contaminated with cross-talk from other muscles. Moreover, it may not be representative for the activation of a muscle when there are several subpopulations of motor units in the muscle. We derive a relation between the recruitment threshold of a motor unit in a subpopulation for force in various directions and the relative contribution by that subpopulation to joint torque. A set of linear equations can then be constructed which relates the contribution of each subpopulation (and therefore of each muscle) to the total joint torque. If the activition of individual subpopulations is modulated differently for forces in various directions, the relative contribution of the individual subpopulations to the total joint torque can be estimated.

A noninvasive technique for in vivo measurement of joint torques of biarticular muscles

The objective of this work was to develop a noninvasive method to measure the joint torques produced by biarticular muscles at two joints simultaneously. During intramuscular stimulation of the cat medial gastrocnemius (MG) muscle, torques at the ankle and knee joints were calculated from forces measured in two dimensions at the end point of the cat paw under isometric conditions. The method was verified by the known anatomical properties of cat MG muscle and the tibialis anterior (TA) muscle. The MG muscle was shown to produce a significant flexion torque at the knee, besides an extension torque at the ankle. This was in agreement with its anatomical arrangement. The TA muscle produced primarily an ankle flexion torque. The small knee torque, due to measurement errors, yielded an estimate of measurement accuracy of 3.0 +/- 2.1% (n = 52). The coupling ratio of the MG muscle, defined as T(ankle)/T(knee), varied significantly with both knee and ankle angles. The profile of MG mechanical coupling agreed qualitatively with changes in limb configuration. The method can be used to measure recruitment properties of electrically stimulated biarticular muscles, and may potentially be used to study the biomechanics of biarticular coupling.

Estimated mechanical properties of synergistic muscles involved in movements of a variety of human joints

One of the most challenging aspects of biomechanical modelling is parameter estimation. Parameter values that define the nonlinear relations within the classic Hill-based muscle model structure have been estimated for a large number of muscles involved in movements of a number of joints. The technique used to estimate these parameters is based on combining information on muscle as a material with geometrical data on muscle-joint anatomy. The resulting relations are compatible with available human experimental data and with past modelling estimates. An estimation of the relative importance of the various synergistic muscle properties during dynamic movement tasks is also provided, aided by examples of muscle load-sharing as a function of optimization criteria including measures of position error, muscle stress and neural effort.

A simulation of rat edl force output based on intrinsic muscle properties

Force-velocity and force-length relations were obtained for the edl of four Wistar rats in order to characterise the contractile properties (CE) of these muscle-tendon complexes. Compliances of the undamped part of the series components (SE) were measured in quick length decreases. Force-extension relations of SEs were obtained by integration of compliance to force. A muscle model consisting of CE, SE and a visco-elastic element was used to simulate the force output of the muscle tendon complex in response to a changing muscle length lOI as input. This simulated force was compared with the experimental force of the same muscle measured in response to the same lOI as input. Tetanic contractions were used in all experiments. The results show that this muscle model can predict the experimental force within a mean maximal error not larger than approximately 14% of the force amplitude. However the comparison of simulated force with experimental force and a few additional experiments show that the muscles do not have a unique instantaneous force-velocity characteristic. As shown by several other studies, force seems to be influenced by many other variables (time, history etc.) than CE length and velocity.