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Yumeng Li, He Wang and Kathy J. Simpson

. 16 Assessing tibiofemoral contact forces has been suggested as an essential approach to understand the initiation and progression of knee injuries and diseases. 18 Computer-simulated musculoskeletal models are often used to estimate tibiofemoral contact forces during various movements. 19 , 20

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Hans Kainz, Hoa X. Hoang, Chris Stockton, Roslyn R. Boyd, David G. Lloyd and Christopher P. Carty

Gait analysis together with musculoskeletal modeling can be used to assess pathological gait, 1 predict musculoskeletal loading, 2 and evaluate the outcome of clinical interventions. 3 The model used for musculoskeletal analyses can be created directly from medical images 4 or

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R. Tyler Richardson, Elizabeth A. Rapp, R. Garry Quinton, Kristen F. Nicholson, Brian A. Knarr, Stephanie A. Russo, Jill S. Higginson and James G. Richards

Musculoskeletal modeling is capable of estimating physiological parameters that cannot be directly measured, 1 , 2 however, the validity of the results must be assessed. A substantial challenge of modeling the shoulder lies in proper implementation of scapular kinematics. 3 , 4 Scapular

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David C. Kingston and Stacey M. Acker

musculoskeletal model. Black spheres are manually selected landmarks matching those from Horsman et al. Blue lines indicate muscle paths. Green spheres within a muscle path are scaled VIA points. Red lines are knee joint ligaments (not used in this iteration). The reader is referred to the online version of this

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Zachary F. Lerner, Derek J. Haight, Matthew S. DeMers, Wayne J. Board and Raymond C. Browning

Net muscle moments (NMMs) have been used as proxy measures of joint loading, but musculoskeletal models can estimate contact forces within joints. The purpose of this study was to use a musculoskeletal model to estimate tibiofemoral forces and to examine the relationship between NMMs and tibiofemoral forces across walking speeds. We collected kinematic, kinetic, and electromyographic data as ten adult participants walked on a dual-belt force-measuring treadmill at 0.75, 1.25, and 1.50 m/s. We scaled a musculoskeletal model to each participant and used OpenSim to calculate the NMMs and muscle forces through inverse dynamics and weighted static optimization, respectively. We determined tibiofemoral forces from the vector sum of intersegmental and muscle forces crossing the knee. Estimated tibiofemoral forces increased with walking speed. Peak earlystance compressive tibiofemoral forces increased 52% as walking speed increased from 0.75 to 1.50 m/s, whereas peak knee extension NMMs increased by 168%. During late stance, peak compressive tibiofemoral forces increased by 18% as speed increased. Although compressive loads at the knee did not increase in direct proportion to NMMs, faster walking resulted in greater compressive forces during weight acceptance and increased compressive and anterior/posterior tibiofemoral loading rates in addition to a greater abduction NMM.

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Amy R. Lewis, William S.P. Robertson, Elissa J. Phillips, Paul N. Grimshaw and Marc Portus

Optimization of propulsion technique for both performance and injury risk can be achieved using musculoskeletal modeling approaches, which can take into account athlete-specific physical attributes. The limiting factor of this approach, however, is the inherent reliance on the quality of input parameters

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Antoine Falisse, Sam Van Rossom, Johannes Gijsbers, Frans Steenbrink, Ben J.H. van Basten, Ilse Jonkers, Antonie J. van den Bogert and Friedl De Groote

Musculoskeletal models for biomechanical simulations have become increasingly popular to analyze human movement. In addition to joint kinematics and kinetics, musculoskeletal models enable researchers and clinicians to assess other biomechanical variables, such as muscle lengths and forces

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Prasanna Sritharan, Luke G. Perraton, Mario A. Munoz, Peter Pivonka and Adam L. Bryant

trial was first recorded to determine anatomical measurements for subsequent musculoskeletal modeling. The single-leg hop trials were then undertaken as described above. The spatial trajectories of the retroreflective markers were collected using a 12-camera Vicon motion analysis system (Oxford Metrics

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Nathalie Alexander and Hermann Schwameder

While inclined walking is a frequent daily activity, muscle forces during this activity have rarely been examined. Musculoskeletal models are commonly used to estimate internal forces in healthy populations, but these require a priori validation. The aim of this study was to compare estimated muscle activity using a musculoskeletal model with measured EMG data during inclined walking. Ten healthy male participants walked at different inclinations of 0°, ± 6°, ± 12°, and ± 18° on a ramp equipped with 2 force plates. Kinematics, kinetics, and muscle activity of the musculus (m.) biceps femoris, m. rectus femoris, m. vastus lateralis, m. tibialis anterior, and m. gastrocnemius lateralis were recorded. Agreement between estimated and measured muscle activity was determined via correlation coefficients, mean absolute errors, and trend analysis. Correlation coefficients between estimated and measured muscle activity for approximately 69% of the conditions were above 0.7. Mean absolute errors were rather high with only approximately 38% being ≤ 30%. Trend analysis revealed similar estimated and measured muscle activities for all muscles and tasks (uphill and downhill walking), except m. tibialis anterior during uphill walking. This model can be used for further analysis in similar groups of participants.

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Amy K. Hegarty, Max J. Kurz, Wayne Stuberg and Anne K. Silverman

The goal of this pilot study was to characterize the effects of gait training on the capacity of muscles to produce body accelerations and relate these changes to mobility improvements seen in children with cerebral palsy (CP). Five children (14 years ± 3 y; GMFCS I-II) with spastic diplegic CP participated in a 6-week gait training program. Changes in 10-m fast-as-possible walking speed and 6-minute walking endurance were used to assess changes in mobility. In addition, musculoskeletal modeling was used to determine the potential of lower-limb muscles to accelerate the body’s center of mass vertically and forward during stance. The mobility changes after the training were mixed, with some children demonstrating vast improvements, while others appeared to be minimal. However, the musculoskeletal results revealed unique responses for each child. The most common changes occurred in the capacity for the hip and knee extensors to produce body support and the hip flexors to produce body propulsion. These results cannot yet be generalized to the broad population of children with CP, but demonstrate that therapy protocols may be enhanced by modeling analyses. The pilot study results provide motivation for gait training emphasizing upright leg posture, mediolateral balance, and ankle push-off.