Hossein Ehsani

Analyzing synergistic and antagonistic muscle behavior during elbow planar flexion-extension: Entropy-assisted vs. shift-parameter criterion

Providing a capable musculoskeletal model for predicting antagonistic muscle forces has been dramatically flourished in recent decades. To reach this destiny, many researchers have struggled to modify objective functions in optimization-based models. The purpose of this paper is to compare two objective functions (Entropy-assisted and shift parameter objective function) exhibited in the literature for predicting muscle co-contraction. Furthermore, the effect of these objective functions in forecasting synergic muscles pattern was taken into account. To do so, a 2 DOF upper limb skeletal model actuated with 15 muscles, has been developed. A phenomenological Hill-based model in accompanied with a rigid tendon was employed to represent musculotendon units. While performing a flexion/extension in the elbow, the upper arm was held stationary in a vertical pose. Exploiting the kinematic data and considering different values (range 0 to 1 with step of 0.1) for entropy weight and shift parameter in the objective function of the static optimization problems, activation level of muscles spanning the elbow was obtained. The results showed that by increasing either of these parameters activation level of agonist and antagonist muscles rise. Besides, inspecting the results, it was clear that both of the optimization problems led to a same trend in the results and by choosing proper weight and shift parameter it was possible to minimize the difference between the obtained results from these two objective functions. Furthermore, considering a graphical approach it was showed that the entropy-assisted problem was a convex one which tried to obtain a minimum state of total activation. Contemplating this fact and utilizing each muscles moment generation capacity, synergic behavior of muscles spanning elbow was discussed. We also examined the validity of the results, using EMG signals of Brachioradialis (BRD) and lateral head of Triceps (TRILAT). Although EMG signal of BRD was somehow consistent with activation level of this muscle, EMG signal of TRILAT was in conflict with the results of static optimization problem.

An EMG-driven musculoskeletal model to predict muscle forces during performing a weight training exercise with a dumbbell

Musculoskeletal system of human body is a redundant system and as a result, employing only inverse dynamics techniques to obtain muscle forces would lead to a dead end. Using EMG signals in order to obtain muscle forces, has been used extensively. In this study, in order to predict muscle forces of elbow flexors (Biceps brachii, brachioradialis, and brachialis) and extensors (Triceps brachii) during flexion/extension weight training with a dumbbell, a hybrid EMG-driven method has been implemented. 6 subjects (4 women and 2 men) were volunteered for the experiments. During performing the action, using a high speed camera and a muscle tester device, kinematic information and EMG signals were obtained, respectively. Besides, exploiting manual muscle testing method, maximum voluntary contraction of all of the mentioned muscles for each subject has been measured. The EMG-driven method, incorporated a forward and an inverse dynamics approach, and by comparing the joint moments obtained from these two routines, the unknown variables of the model (electromechanical delay, shape factor, excitation filter coefficients) were obtained. Finally, in order to compare the virtue of the muscle forces, these results were compared with the same results obtained from a static optimization method (objective function: sum of squared muscle forces). Conducting a two-way ANOVA for comparing the results, a significant difference between the two results, has been observed (P <; 0.005).

Kinematic and kinetic analyses of the Wing Chun straight punch

The main purpose of this study was to identify factors that may affect the performance of Wing Chun straight punch. Seven male professional subjects participated in the experiment. They were asked to perform the straight punch while standing in front of a wall mounted force plate. Impact force data were collected with the force plate and upper extremity kinematics was recorded using a high-speed camera. Significant relationship was found between impulse and effective mass (r = 0.81, p < 0.0001) while no significant relationship was observed between impulse and impact velocity (r = 0.20, p = 0.36). The effective mass was inversely related to impact velocity (r = −0.72, p < 0.0005). Significant relationship was observed to elbow peak angular velocity for impact velocity (r = 0.44, p < 0.05), impact acceleration (r = 0.66, p < 0.002), impulse (r = −0.43, p < 0.05) and effective mass (r = −0.58, p < 0.01). The results indicated that the effective mass was the only variable in improving the effectiveness of the straight punch. Additionally, high values of the loading rate, as a sign of hand overuse injuries, was observed.

A general-purpose framework to simulate musculoskeletal system of human body: using a motion tracking approach.

Computation of muscle force patterns that produce specified movements of muscle-actuated dynamic models is an important and challenging problem. This problem is an undetermined one, and then a proper optimization is required to calculate muscle forces. The purpose of this paper is to develop a general model for calculating all muscle activation and force patterns in an arbitrary human body movement. For this aim, the equations of a multibody system forward dynamics, which is considered for skeletal system of the human body model, is derived using Lagrange–Euler formulation. Next, muscle contraction dynamics is added to this model and forward dynamics of an arbitrary musculoskeletal system is obtained. For optimization purpose, the obtained model is used in computed muscle control algorithm, and a closed-loop system for tracking desired motions is derived. Finally, a popular sport exercise, biceps curl, is simulated by using this algorithm and the validity of the obtained results is evaluated via EMG signals.

Investigating the role of foot placement on the muscular forces of knee extensors in horizontal leg press: A static optimization approach

Horizontal leg press is a basic weight training exercise to strengthen extensor muscles of knee joint. Considering the specific purpose of this training, its performed with different techniques. One of the major debates about performing this task concerns foot placement on the foot-plate. In this study, in order to investigate the effect of foot placement on the muscle contraction of knee extensors, a 3-DOF musculoskeletal model of lower-extremity was developed. This model was comprised of 40 skeletal muscles of lower-extremity. Each muscle was modeled with a phenomenological Hill-based model in accompanied with a rigid tendon. Considering the position of feet on the foot-plate (high or low), two types of experiments were designed: Leg Press High (LPH) and Leg Press Low (LPL). 6 healthy volunteers (2 women and 4 men) participated in this study. Experiments were performed at 30% and 70% of each persons MVC (the maximum weight in which a person could perform the exercise correctly) on the LPL and LPH protocols. Amalgamating the mean values of kinematic data and a constrained static optimization (sum of squared activations as the objective function and discritisized state equations of the multibody system as constraints), the required activation level of each muscle was obtained. The results showed a significant difference between the obtained muscle forces for knee extensors (vastus intermedius, vastus lateralis, vastus medialis, and rectus femoris) in each technique (p<;0.05). The muscle forces obtained in LPH technique were significantly smaller from the same ones in LPL. This observation suggests that if strengthening the knee extensors is of desire, LPH technique is not the correct format for performing the exercise. Another important spotlight in the results concerned the activation patterns of knee extensors. Despite the synergic behavior of all the extensors, because of the different operating range of these muscles, dissimilarity between activation patterns was observed.

A comparison between computed muscle control method and static optimization technique to determine muscle forces during a weight training exercise with a dumbbell

On account of redundancy of musculoskeletal system of human body, using pure multibody system dynamics to simulate this system is not enough. Optimization-based methods have been developed to overcome this difficulty. In this study, by simulating a flexion/extension weight training exercise with a dumbbell, two of these methods (Computed Muscle Control and Traditional Static Optimization) have been compared. 6 healthy right-handed subjects have participated in this study. During performing the actions, using a high speed camera the kinematic information of the motion has been captured. To actuate the system, a Hill-based muscle model in accompanied with a stiff tendon has been considered. The forces of elbow flexors (Biceps brachii, brachioradial, brachialis) and extensors (Triceps brachii) have been computed using two methods. Using a two-way ANOVA method the obtained results from both of the methods have been compared to each other and a significant difference has been observed (P <; 0.005). All of the mathematical models and methods have been implemented on MATLAB.

Deriving a closed form of equations of motion of musculoskeletal system of human body: Using Lagrangian dynamics

Musculoskeletal simulation of human body is one of the most fascinating research areas in biomechanics. The cornerstone of this type of simulation, regardless of the approach, is obtaining the differential equations of the system. The purpose of this paper is deriving equations of motion of an arbitrary musculoskeletal model of the human body by using Denavit-Hartenberg parameters in accompanied by Lagrangian dynamics. A closed form algorithm has been developed to obtain the governing equations of motion. Skeletal muscle system has been included in this model and the generalized force of this kind of actuator has been derived in the model. To verify the obtained equations, a simple two-link model has been considered. To overcome the difficulty of redundancy, a static optimization approach was used. The obtained results, which were muscle forces, showed quite a well correspondence with the input trajectories for each joint.

Developing a hybrid method for solving optimal control problems of the musculoskeletal system of the human body: Combination of linear and angular actuators

Musculoskeletal modeling plays an important role in gaining insight into coordination of muscles during human movement. Optimal control can be an effectual method for solving muscle redundancy due to its accuracy; however, this technique suffers from high computational cost. Torque driven methods in which moments-instead of muscles-are considered as actuators of the musculoskeletal systems can reduce the redundancy of the system and the number of unknowns; consequently, it enhances the computational speed. Should we want to define the force of individual muscle(s), this approach is not sufficient. In this study, we provide a hybrid model including muscle-based and moment-based methods in order to compensate this limitation. To reach this goal, a 2-degree-of-freedom skeletal model was considered. Two different sets of actuators were assumed for this model. In the first one six musculotendon units were considered as the actuators of this model. A Hill-based muscle model in accompanied with a stiff tendon was employed to represent the musculotendon units. In the second problem, except for the 5th muscle, we summarized the effects of the musculotendon units into rotational actuators, i.e. torques. The results obtained from the hybrid model and the outcomes of the muscle-driven one, in terms of the joint trajectories, first derivative of joint trajectories and the magnitude of muscle force were compared to each other. While these results were equivalent to each other up to six significant figures, the results of the hybrid method were obtained more than five times faster than the outcomes of the muscle-driven method.

Compliant Vs. rigid tendon models: A simulation study on precision, computational efficiency and numerical stability

Providing an efficient mathematical model of the skeletal muscles which takes both computational efficiency and accuracy into account is a crucial factor in the simulations of multiple-muscle problems. Previous studies stated that ignoring the elastic characteristics of the tendon can reduce the time cost of simulations at the expense of introducing some minor errors if the ratio of tendon slack length to muscle optimum length is less than or equal to unity. The purpose of this paper was to test the precision, efficiency and numerical stability of this criterion for the muscles of the human body in their usual length excursions. In this regard two muscles of the upper extremity (Brachioradialis (BRD) long head of biceps (BICL)) and one from the lower extremity (soleus (SOL)) of the human body have been chosen. Two variations of a general Hill-based musculotendon model have been considered in this study. In the first one, using a nonlinear spring the elastic properties of the tendon has been incorporated into the model and in the second one, ignoring this properties, a constant length for the tendon has been assumed. The mean absolute error between the force profiles of the two models for BRD, BICL and SOL were 4.2, 12 and 13.1 respectively. Also rigid-tendon model was 7.3 to 9.5 times faster than compliant-tendon model using the implicit integrator. For BRD the outcomes of the two models, have similar trends and the discrepancies between the force profiles are negligible. However, the results obtained from the compliant-tendon model illustrate some numerical stability problems. In the second muscle, i.e. BICL, likewise BRD the trends of the force profiles are the same; however, the disparity among the outcomes of the two models have escalated. Likewise BRD, the rigid-tendon model required less computational time. Inspecting the results obtained for SOL, one can easily spot the significant differences between the outcomes of the two models. Considering the tendon slack length to the optimum muscle length ratio for the three mentioned musculotendon units, one can draw this conclusion that, in case this value is less than unity using the rigid-tendon model is recommended. If this value is not much greater than unity, like BICL, exploiting the rigid-tendon model will increase the computational efficiency in expense of contaminating the outcomes with some amounts of error. However, if this ratio is far from unity, like SOL, ignoring the length alterations in the tendon is not recommended.