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The presence of muscle redundancy and co-activation of agonist-antagonist pairs in vivo makes the optimization of the load distribution between muscles in physiologic joint simulators vital. This optimization is usually achieved by employing different control strategies based on position and/or force feedback. A muscle activated physiologic wrist simulator was developed to test and iteratively refine such control strategies on a functional replica of a human arm. Motions of the wrist were recreated by applying tensile loads using electromechanical actuators. Load cells were used to monitor the force applied by each muscle and an optical motion capture system was used to track joint angles of the wrist in real-time. Four control strategies were evaluated based on their kinematic error, repeatability and ability to vary co-contraction. With kinematic errors of less than 1.5°, the ability to vary co-contraction, and without the need for predefined antagonistic forces or muscle force ratios, novel control strategies - hybrid control and cascade control - were preferred over standard control strategies - position control and force control. Muscle forces obtained from hybrid and cascade control corresponded well with in vivo EMG data and muscle force data from other wrist simulators in the literature. The decoupling of the wrist axes combined with the robustness of the control strategies resulted in complex motions, like dart thrower׳s motion and circumduction, being accurate and repeatable. Thus, two novel strategies with repeatable kinematics and physiologically relevant muscle forces are introduced for the control of joint simulators., (Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.)

This paper introduces a new approach for computing lower extremity muscle forces by incorporating equations that consider "bone structure" and "prevention of bending by load reduction" into existing optimization algorithms. Lower extremity muscle and joint forces, during normal gait, were calculated and compared using two different optimization approaches. We added constraint equations that prevent femoral bending loads to an existing approach that considers "minimal total muscular force". Gait parameters such as kinematics, ground reaction forces, and surface electromyographic activation patterns were examined using standardized gait analysis. A subject-specific anatomic model of the lower extremities, obtained from magnetic resonance images of a healthy male, was used for the simulations. Finite element analysis was used to calculate femoral loads. The conventional method of calculating muscle forces leads to higher rates of femoral bending and structural stress than the new approach. Adding equations with structural subject-specific parameters in our new approach resulted in reduced femoral stress patterns. These findings show that our new approach improves the accuracy of femoral stress and strain simulations. Structural overloads caused by bending can be avoided during inverse calculation of muscle forces., (Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.)

Unstable sitting on a wobble chair with different balance difficulty levels can be used as an effective tool in exercises as well as evaluation and therapeutic stages of rehabilitation. No data on muscle activity levels and spinal loads are however available to assess its safety compared to other regular daily activities. The goal of this study was to estimate muscle forces and spinal loads in a seated unstable wobble chair task. In vivo 3D kinematics of the trunk and seat collected in an earlier study were used here to drive computational trunk musculoskeletal models of 6 normal and 6 low-back pain subject groups sitting on a wobble chair for a duration of 10s. Results revealed no significant differences between kinematics, muscle forces, spinal loads and force plate reaction forces when comparing these two groups. The estimated muscle forces and spinal loads were moderate though larger than those in a stationary sitting posture. Local spinal forces at the L5-S1 disc varied with time and reached their peaks (1473 N and 1720 N in compression, 691 N and 687 N in posterior-anterior shear and 153 N and 208 N in right-left shear, respectively for healthy and CLBP groups) being much greater relative to those in the stationary sitting posture (means of 12 subjects: 768 N, 284 N and 0 N, respectively). The wobble chair with characteristics considered in this study is found hence safe enough as a therapeutic exercise for both healthy and low-back pain subjects., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: Persons with lower limb amputation walk with increased and asymmetric trunk motion; a characteristic that is likely to impose distinct demands on trunk muscles to maintain equilibrium and stability of the spine. However, trunk muscle responses to such changes in net mechanical demands, and the resultant effects on spinal loads, have yet to be determined in this population., Methods: Building on a prior study, trunk and pelvic kinematics collected during level-ground walking from 40 males (20 with unilateral transfemoral amputation and 20 matched controls) were used as inputs to a kinematics-driven, nonlinear finite element model of the lower back to estimate forces in 10 global (attached to thorax) and 46 local (attached to lumbar vertebrae) trunk muscles, as well as compression, lateral, and antero-posterior shear forces at all spinal levels., Findings: Trunk muscle force and spinal load maxima corresponded with heel strike and toe off events, and among persons with amputation, were respectively 10-40% and 17-95% larger during intact vs. prosthetic stance, as well as 6-80% and 26-60% larger during intact stance relative to controls., Interpretation: During gait, larger spinal loads with transfemoral amputation appear to be the result of a complex pattern of trunk muscle recruitment, particularly involving co-activation of antagonistic muscles during intact limb stance; a period when these individuals are confident and likely to use the trunk to assist with forward progression. Given the repetitive nature of walking, repeated exposure to such elevated loading likely increases the risk for low back pain in this population., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Gastrocnemius is a premier muscle crossing the knee, but its role in knee biomechanics and on the anterior cruciate ligament (ACL) remains less clear when compared to hamstrings and quadriceps. The effect of changes in gastrocnemius force at late stance when it peaks on the knee joint response and ACL force was initially investigated using a lower extremity musculoskeletal model driven by gait kinematics-kinetics. The tibiofemoral joint under isolated isometric contraction of gastrocnemius was subsequently analyzed at different force levels and flexion angles (0°-90°). Changes in gastrocnemius force at late stance markedly influenced hamstrings forces. Gastrocnemius acted as ACL antagonist by substantially increasing its force. Simulations under isolated contraction of gastrocnemius confirmed this role at all flexion angles, in particular, at extreme knee flexion angles (0° and 90°). Constraint on varus/valgus rotations substantially decreased this effect. Although hamstrings and gastrocnemius are both knee joint flexors, they play opposite roles in respectively protecting or loading ACL. Although the quadriceps is also recognized as antagonist of ACL, at larger joint flexion and in contrast to quadriceps, activity in gastrocnemius substantially increased ACL forces (anteromedial bundle). The fact that gastrocnemius is an antagonist of ACL should help in effective prevention and management of ACL injuries.

Clinical gait analysis provides great contributions to the understanding of gait patterns. However, a complete distribution of muscle forces throughout the gait cycle is a current challenge for many researchers. Two techniques are often used to estimate muscle forces: inverse dynamics with static optimization and computer muscle control that uses forward dynamics to minimize tracking. The first method often involves limitations due to changing muscle dynamics and possible signal artefacts that depend on day-to-day variation in the position of electromyographic (EMG) electrodes. Nevertheless, in clinical gait analysis, the method of inverse dynamics is a fundamental and commonly used computational procedure to calculate the force and torque reactions at various body joints. Our aim was to develop a generic musculoskeletal model that could be able to be applied in the clinical setting. The musculoskeletal model of the lower limb presents a simulation for the EMG data to address the common limitations of these techniques. This model presents a new point of view from the inverse dynamics used on clinical gait analysis, including the EMG information, and shows a similar performance to another model available in the OpenSim software. The main problem of these methods to achieve a correct muscle coordination is the lack of complete EMG data for all muscles modelled. We present a technique that simulates the EMG activity and presents a good correlation with the muscle forces throughout the gait cycle. Also, this method showed great similarities whit the real EMG data recorded from the subjects doing the same movement.

Scaled generic musculoskeletal models are commonly used to drive dynamic simulations of motions. It is however, acknowledged that not accounting for variability in musculoskeletal geometry and musculotendon parameters may confound the simulation results, even when analysing control subjects. This study documents the three-dimensional anatomical variability of musculotendon origins and insertions of 33 lower limb muscles determined based on magnetic resonance imaging in six subjects. This anatomical variability was compared to the musculotendon point location in a generic musculoskeletal model. Furthermore, the sensitivity of muscle forces during gait, calculated using static optimization, to perturbations of the musculotendon point location was analyzed with a generic model. More specific, a probabilistic approach was used: for each analyzed musculotendon point, the three-dimensional location was re-sampled with a uniform Latin hypercube method within the anatomical variability and the static optimization problem was then re-solved for all perturbations. We found that musculotendon point locations in the generic model showed only variable correspondences with the anatomical variability. The anatomical variability of musculotendon point location did affect the calculated muscle forces: muscles most sensitive to perturbations within the anatomical variability are iliacus and psoas. Perturbation of the gluteus medius anterior, iliacus and psoas induces the largest concomitant changes in muscle forces of the unperturbed muscles. Therefore, when creating subject-specific musculoskeletal models, these attachment points should be defined accurately. In addition, the size of the anatomical variability of the musculotendon point location was not related to the sensitivity of the calculated muscle forces., (Copyright © 2015. Published by Elsevier Ltd.)