Differences in Muscle Demand and Joint Contact Forces Between Running and Skipping.

Skipping has been proposed as a viable cross-training exercise to running due to its lower knee contact forces and higher whole-body energy expenditure. However, how individual muscle forces, energy expenditure, and joint loading are affected by differences in running and skipping mechanics remains unclear. The purpose of this study was to compare individual muscle forces, energy expenditure, and lower extremity joint contact forces between running and skipping using musculoskeletal modeling and simulations of young adults (n = 5) performing running and skipping at 2.5 m·s-1 on an instrumented treadmill. In agreement with previous work, running had greater knee and patella contact forces than skipping which was accompanied by greater knee extensor energetic demand. Conversely, skipping had greater ankle contact forces and required greater energetic demand from the uniarticular ankle plantarflexors. There were no differences in hip contact forces between gaits. These findings further support skipping as a viable alternative to running if the primary goal is to reduce joint loading at the commonly injured patellofemoral joint. However, for those with ankle injuries, skipping may not be a viable alternative due to the increased ankle loads. These findings may help clinicians prescribe activities most appropriate for a patient's individual training or rehabilitation goals.

Is modular control related to functional outcomes in individuals with knee osteoarthritis and following total knee arthroplasty?

BACKGROUND: Individuals who undergo total knee arthroplasty (TKA) for treatment of knee osteoarthritis often experience suboptimal outcomes. Investigation of neuromuscular control strategies in these individuals may reveal factors that contribute to these functional deficits. The purpose of this pilot study was to determine the relationship between patient function and modular control during gait before and after TKA. METHODS: Electromyography data from 36 participants (38 knees) were collected from 8 lower extremity muscles on the TKA-involved limb during ≥5 over-ground walking trials before (n = 30), 6-months after (n = 26), and 24-months after (n = 13) surgery. Muscle modules were estimated using non-negative matrix factorization. The number of modules was determined from 500 resampled trials. RESULTS: A higher number of modules was related to better performance-based and patient-reported function before and 6-months after surgery. Participants with organization similar to healthy, age-matched controls trended toward better function 24-months after surgery, though these results were not statistically significant. We also observed plasticity in the participants' modular control strategies, with 100% of participants who were present before and 24-months after surgery (10/10) demonstrating changes in the number of modules and/or organization of at least 1 module. CONCLUSIONS: This pilot work suggests that functional improvements following TKA may initially present as increases in the number of modules recruited during gait. Subsequent improvements in function may present as improved module organization. NOTEWORTHY: This work is the first to characterize motor modules in TKA both before and after surgery and to demonstrate changes in the number and organization of modules over the time course of recovery, which may be related to changes in patient function. The plasticity of modular control following TKA is a key finding which has not been previously documented and may be useful in predicting or improving surgical outcomes through novel rehabilitation protocols.

Discover your potential: The influence of kinematics on a muscle's ability to contribute to the sit-to-stand transfer.

Existing methods for estimating how individual muscles contribute to a movement require extensive time and experimental resources. In this study we developed an efficient method for determining how changes to lower extremity joint kinematics affect the potential of individual muscles to contribute to whole-body center-of-mass vertical (support) and anteroposterior (progression) accelerations. A 4-link 2-dimensional model was used to assess the effect of kinematic changes on muscle function. Joint kinematics were systematically varied throughout ranges observed during the momentum transfer phase of the sit-to-stand transfer. Each muscle's potential to contribute to support and progression was computed and compared to simulated potentials estimated by traditional dynamic simulation methods for young adults and individuals with knee osteoarthritis. The new method required 4-10s to compute muscle potentials per kinematic state and computed potentials were consistent with simulated potentials. The new method identified differences in muscle potentials between groups due to kinematic differences, particularly decreased anterior pelvic tilt in young adults, and revealed kinematic and muscle strengthening modifications to increase support. The methods presented provide an efficient, systematic approach to evaluate how joint kinematic adjustments alter a muscle's ability to contribute to movement and can identify potential sources of pathologic movement and rehabilitation strategies.

Effects of age and knee osteoarthritis on the modular control of walking: A pilot study.

BACKGROUND: Older adults and individuals with knee osteoarthritis (KOA) often exhibit reduced locomotor function and altered muscle activity. Identifying age- and KOA-related changes to the modular control of gait may provide insight into the neurological mechanisms underlying reduced walking performance in these populations. The purpose of this pilot study was to determine if the modular control of walking differs between younger and older adults without KOA and adults with end-stage KOA. METHODS: Kinematic, kinetic, and electromyography data were collected from ten younger (23.5 ± 3.1 years) and ten older (63.5 ± 3.4 years) adults without KOA and ten adults with KOA (64.0 ± 4.0 years) walking at their self-selected speed. Separate non-negative matrix factorizations of 500 bootstrapped samples determined the number of modules required to reconstruct each participant's electromyography. One-way Analysis of Variance tests assessed the effect of group on walking speed and the number of modules. Kendall rank correlations (τb) assessed the association between the number of modules and self-selected walking speed. RESULTS: The number of modules required in the younger adults (3.2 ± 0.4) was greater than in the individuals with KOA (2.3 ± 0.7; p = 0.002), though neither cohorts' required number of modules differed significantly from the unimpaired older adults (2.7 ± 0.5; p ≥ 0.113). A significant association between module number and walking speed was observed (τb = 0.350, p = 0.021) and individuals with KOA walked significantly slower (0.095 ± 0.21 m/s) than younger adults (1.24 ± 0.15 m/s; p = 0.005). Individuals with KOA also exhibited altered module activation patterns and composition (which muscles are associated with each module) compared to unimpaired adults. CONCLUSION: These findings suggest aging alone may not significantly alter modular control; however, the combined effects of knee osteoarthritis and aging may together impair the modular control of gait.

Analysis of the Relative Motion Between the Socket and Residual Limb in Transtibial Amputees While Wearing a Transverse Rotation Adapter.

The coupling between the residual limb and the lower-limb prosthesis is not rigid. As a result, external loading produces movement between the prosthesis and residual limb that can lead to undesirable soft-tissue shear stresses. As these stresses are difficult to measure, limb loading is commonly used as a surrogate. However, the relationship between limb loading and the displacements responsible for those stresses remains unknown. To better understand the limb motion within the socket, an inverse kinematic analysis was performed to estimate the motion between the socket and tibia for 10 individuals with a transtibial amputation performing walking and turning activities at 3 different speeds. The authors estimated the rotational stiffness of the limb-socket body to quantify the limb properties when coupled with the socket and highlight how this approach could help inform prosthetic prescriptions. Results showed that peak transverse displacement had a significant, linear relationship with peak transverse loading. Stiffness of the limb-socket body varied significantly between individuals, activities (walking and turning), and speeds. These results suggest that transverse limb loading can serve as a surrogate for residual-limb shear stress and that the setup of a prosthesis could be individually tailored using standard motion capture and inverse kinematic analyses.

Effects of Optimization Technique on Simulated Muscle Activations and Forces.

Two optimization techniques, static optimization (SO) and computed muscle control (CMC), are often used in OpenSim to estimate the muscle activations and forces responsible for movement. Although differences between SO and CMC muscle function have been reported, the accuracy of each technique and the combined effect of optimization and model choice on simulated muscle function is unclear. The purpose of this study was to quantitatively compare the SO and CMC estimates of muscle activations and forces during gait with the experimental data in the Gait2392 and Full Body Running models. In OpenSim (version 3.1), muscle function during gait was estimated using SO and CMC in 6 subjects in each model and validated against experimental muscle activations and joint torques. Experimental and simulated activation agreement was sensitive to optimization technique for the soleus and tibialis anterior. Knee extension torque error was greater with CMC than SO. Muscle forces, activations, and co-contraction indices tended to be higher with CMC and more sensitive to model choice. CMC's inclusion of passive muscle forces, muscle activation-contraction dynamics, and a proportional-derivative controller to track kinematics contributes to these differences. Model and optimization technique choices should be validated using experimental activations collected simultaneously with the data used to generate the simulation.

Muscle contributions to mediolateral and anteroposterior foot placement during walking.

Foot placement is critical to balance control during walking and is primarily controlled by muscle force generation. Although gluteus medius activity has been associated with mediolateral foot placement, how other muscles contribute to foot placement is not clear. Furthermore, although dynamic walking models have suggested that anteroposterior foot placement can be passively controlled, the extent to which muscles actively contribute to anteroposterior foot placement has not been determined. The objective of this study was to identify individual muscle contributions to mediolateral and anteroposterior foot placement during walking in healthy adults. Dynamic simulations of walking were developed for six older adults and a segmental power analysis was performed to determine the individual muscle contributions to the mediolateral and anteroposterior power delivered to the foot segment. The simulations revealed the ipsilateral swing limb gluteus medius, iliopsoas, rectus femoris and hamstrings and the contralateral stance limb gluteus medius and ankle plantarflexors were primary contributors to both mediolateral and anteroposterior foot placement. Muscle contributions to foot placement were found to be highly influenced by their contributions to pelvis power, which was dominated by those muscles crossing the hip joint. Thus, impaired balance control may be improved by focusing rehabilitation interventions on optimizing the coordination of those muscles crossing the hip joint and the ankle plantarflexors.

Paretic propulsion as a measure of walking performance and functional motor recovery post-stroke: A review.

BACKGROUND: Although walking speed is the most common measure of gait performance post-stroke, improved walking speed following rehabilitation does not always indicate the recovery of paretic limb function. Over the last decade, the measure paretic propulsion (Pp, defined as the propulsive impulse generated by the paretic leg divided by the sum of the propulsive impulses of both legs) has been established as a measure of paretic limb output and recently targeted in post-stroke rehabilitation paradigms. However, the literature lacks a detailed synthesis of how paretic propulsion, walking speed, and other biomechanical and neuromuscular measures collectively relate to post-stroke walking performance and motor recovery. OBJECTIVE: The aim of this review was to assess factors associated with the ability to generate Pp and identify rehabilitation targets aimed at improving Pp and paretic limb function. METHODS: Relevant literature was collected in which paretic propulsion was used to quantify and assess propulsion symmetry and function in hemiparetic gait. RESULTS: Paretic leg extension during terminal stance is strongly associated with Pp. Both paretic leg extension and propulsion are related to step length asymmetry, revealing an interaction between spatiotemporal, kinematic and kinetic metrics that underlies hemiparetic walking performance. The importance of plantarflexor function in producing propulsion is highlighted by the association of an independent plantarflexor excitation module with increased Pp. Furthermore, the literature suggests that although current rehabilitation techniques can improve Pp, these improvements depend on the patient's baseline plantarflexor function. SIGNIFICANCE: Pp provides a quantitative measure of propulsion symmetry and should be a primary target of post-stroke gait rehabilitation. The current literature suggests rehabilitation techniques that target both plantarflexor function and leg extension may restore paretic limb function and improve gait asymmetries in individuals post stroke.

Interpreting Musculoskeletal Models and Dynamic Simulations: Causes and Effects of Differences Between Models.

With more than 29,000 OpenSim users, several musculoskeletal models with varying levels of complexity are available to study human gait. However, how different model parameters affect estimated joint and muscle function between models is not fully understood. The purpose of this study is to determine the effects of four OpenSim models (Gait2392, Lower Limb Model 2010, Full-Body OpenSim Model, and Full Body Model 2016) on gait mechanics and estimates of muscle forces and activations. Using OpenSim 3.1 and the same experimental data for all models, six young adults were scaled in each model, gait kinematics were reproduced, and static optimization estimated muscle function. Simulated measures differed between models by up to 6.5° knee range of motion, 0.012 Nm/Nm peak knee flexion moment, 0.49 peak rectus femoris activation, and 462 N peak rectus femoris force. Differences in coordinate system definitions between models altered joint kinematics, influencing joint moments. Muscle parameter and joint moment discrepancies altered muscle activations and forces. Additional model complexity yielded greater error between experimental and simulated measures; therefore, this study suggests Gait2392 is a sufficient model for studying walking in healthy young adults. Future research is needed to determine which model(s) is best for tasks with more complex motion.