Altered lower extremity joint mechanics occur during the star excursion balance test and single leg hop after ACL-reconstruction in a collegiate athlete.

The effects of ACL-reconstruction on lower extremity joint mechanics during performance of the Star Excursion Balance Test (SEBT) and Single Leg Hop (SLH) are limited. The purpose of this study was to determine if altered lower extremity mechanics occur during the SEBT and SLH after ACL-reconstruction. One female Division I collegiate athlete performed the SEBT and SLH tasks, bilaterally, both before ACL injury and 27 months after ACL-reconstruction. Maximal reach, hop distances, lower extremity joint kinematics and moments were compared between both time points. Musculoskeletal simulations were used to assess muscle force production during the SEBT and SLH at both time points. Compared to the pre-injury time point, SEBT reach distances were similar in both limbs after ACL-reconstruction except for the max anterior reach distance in the ipsilateral limb. The athlete demonstrated similar hop distances, bilaterally, after ACL-reconstruction compared to the pre-injury time point. Despite normal functional performance during the SEBT and SLH, the athlete exhibited altered lower extremity joint mechanics during both of these tasks. These results suggest that measuring the maximal reach and hop distances for these tasks, in combination with an analysis of the lower extremity joint mechanics that occur after ACL-reconstruction, may help clinicians and researchers to better understand the effects of ACL-reconstruction on the neuromuscular system during the SEBT and SLH.

Anterior cruciate ligament (ACL) loading in a collegiate athlete during sidestep cutting after ACL reconstruction: A case study.

BACKGROUND: Athletes with anterior cruciate ligament (ACL) injuries usually undergo ACL-reconstruction (ACLR) in order to restore joint stability, so that dynamic maneuvers such as the sidestep cut can be performed. Despite restoration of joint stability after ACLR, many athletes do not return to pre-injury levels and may be at a high risk of a second ACL injury. The purpose of this study was to determine whether or not ACL loading, would increase after ACLR. METHODS: One female Division I collegiate athlete performed bilateral unanticipated sidestep cuts both before ACL injury and 27months after ACLR. Musculoskeletal simulations were used to calculate ACL loading during the deceleration phase of the sidestep cuts. RESULTS: Twenty-seven months after ACLR, the athlete demonstrated higher total ACL loading in the ipsilateral limb as well as altered joint kinematics, moments, and quadriceps muscle force production. In the contralateral limb, there were no increases in total ACL loading or muscle force production yet altered lower extremity joint kinematics and moments were present after ACLR. CONCLUSIONS: Higher total ACL loading in the ipsilateral limb of this athlete may suggest an increased risk of second ACL injury. The results of this study provide an initial step in understanding the effects of ACLR on the risk of second ACL injury in an elite athlete and suggest that it is important to develop a better understanding of this surgical intervention on knee joint loading, in order to reduce the risk of second ACL injury while performing dynamic maneuvers.

Determining residual reduction algorithm kinematic tracking weights for a sidestep cut via numerical optimization.

Musculoskeletal modeling allows for the determination of various parameters during dynamic maneuvers by using in vivo kinematic and ground reaction force (GRF) data as inputs. Differences between experimental and model marker data and inconsistencies in the GRFs applied to these musculoskeletal models may not produce accurate simulations. Therefore, residual forces and moments are applied to these models in order to reduce these differences. Numerical optimization techniques can be used to determine optimal tracking weights of each degree of freedom of a musculoskeletal model in order to reduce differences between the experimental and model marker data as well as residual forces and moments. In this study, the particle swarm optimization (PSO) and simplex simulated annealing (SIMPSA) algorithms were used to determine optimal tracking weights for the simulation of a sidestep cut. The PSO and SIMPSA algorithms were able to produce model kinematics that were within 1.4° of experimental kinematics with residual forces and moments of less than 10 N and 18 Nm, respectively. The PSO algorithm was able to replicate the experimental kinematic data more closely and produce more dynamically consistent kinematic data for a sidestep cut compared to the SIMPSA algorithm. Future studies should use external optimization routines to determine dynamically consistent kinematic data and report the differences between experimental and model data for these musculoskeletal simulations.

Comparison of ACL strain estimated via a data-driven model with in vitro measurements.

Computer modeling and simulation techniques have been increasingly used to investigate anterior cruciate ligament (ACL) loading during dynamic activities in an attempt to improve our understanding of injury mechanisms and development of injury prevention programs. However, the accuracy of many of these models remains unknown and thus the purpose of this study was to compare estimates of ACL strain from a previously developed three-dimensional, data-driven model with those obtained via in vitro measurements. ACL strain was measured as the knee was cycled from approximately 10° to 120° of flexion at 20 deg s(-1) with static loads of 100, 50, and 50 N applied to the quadriceps, biceps femoris and medial hamstrings (semimembranosus and semitendinosus) tendons, respectively. A two segment, five-degree-of-freedom musculoskeletal knee model was then scaled to match the cadaver's anthropometry and in silico ACL strains were then determined based on the knee joint kinematics and moments of force. Maximum and minimum ACL strains estimated in silico were within 0.2 and 0.42% of that measured in vitro, respectively. Additionally, the model estimated ACL strain with a bias (mean difference) of -0.03% and dynamic accuracy (rms error) of 0.36% across the flexion-extension cycle. These preliminary results suggest that the proposed model was capable of estimating ACL strains during a simple flexion-extension cycle. Future studies should validate the model under more dynamic conditions with variable muscle loading. This model could then be used to estimate ACL strains during dynamic sporting activities where ACL injuries are more common.

Predictive Neuromuscular Fatigue of the Lower Extremity Utilizing Computer Modeling.

This paper studies the modeling of lower extremity muscle forces and their correlation to neuromuscular fatigue. Two analytical fatigue models were combined with a musculoskeletal model to estimate the effects of hamstrings fatigue on lower extremity muscle forces during a side step cut. One of the fatigue models (Tang) used subject-specific knee flexor muscle fatigue and recovery data while the second model (Xia) used previously established fatigue and recovery parameters. Both fatigue models were able to predict hamstrings fatigue within 20% of the experimental data, with the semimembranosus and semitendinosus muscles demonstrating the largest (11%) and smallest (1%) differences, respectively. In addition, various hamstrings fatigue levels (10-90%) on lower extremity muscle force production were assessed using one of the analytical fatigue models. As hamstrings fatigue levels increased, the quadriceps muscle forces decreased by 21% (p < 0.01), while gastrocnemius muscle forces increased by 36% (p < 0.01). The results of this study validate the use of two analytical fatigue models in determining the effects of neuromuscular fatigue during a side step cut, and therefore, this model can be used to assess fatigue effects on risk of lower extremity injury during athletic maneuvers. Understanding the effects of fatigue on muscle force production may provide insight on muscle group compensations that may lead to altered lower extremity motion patterns as seen in noncontact anterior cruciate ligament (ACL) injuries.

Influence of kinematic analysis methods on detecting ankle and subtalar joint instability.

Patients with subtalar joint instability may be misdiagnosed with ankle instability, which may lead to chronic instability at the subtalar joint. Therefore, it is important to understand the difference in kinematics after ligament sectioning and differentiate the changes in kinematics between ankle and subtalar instability. Three methods may be used to determine the joint kinematics; the Euler angles, the Joint Coordinate System (JCS) and the helical axis (HA). The purpose of this study was to investigate the influence of using either method to detect subtalar and ankle joints instability. 3D kinematics at the ankle and subtalar joint were analyzed on 8 cadaveric specimens while the foot was intact and after sequentially sectioning the anterior talofibular ligament (ATFL), the calcaneofibular ligament (CFL), the cervical ligament and the interosseous talocalcaneal ligament (ITCL). Comparison in kinematics calculated from sensor and anatomical landmarks was conducted as well as the influence of Euler angles and JCS rotation sequence (between ISB recommendation and previous research) on the subtalar joint. All data showed a significant increase in inversion when the ITCL was sectioned. There were differences in the data calculated using sensors coordinate systems vs. anatomic coordinate systems. Anatomic coordinate systems were recommended for these calculations. The Euler angle and JCS gave similar results. Differences in Euler angles and JCS sequence lead to the same conclusion in detecting instability at the ankle and subtalar joint. As expected, the HA detected instability in plantarflexion at the ankle joint and in inversion at the subtalar joint.

Optimized surgical tool for pectus bar extraction.

Surgeons on a daily basis improve or rescue human lives. Therefore, they should be provided with the most optimal tools so their skills are fully utilized. In this paper, we present such an optimized tool for surgeons who employ the Nuss procedure to correct pectus excavatum - a congenital chest wall deformity. The Nuss procedure is a minimally invasive procedure that results in the placement of a metal bar inside the chest cavity. The bar is removed after approximately two years. Surgeons have been reporting that the currently available tools for the bar extraction do not provide the most optimal functionality. Therefore, we have proposed an optimized and improved design of the tool for the bar extraction. The improved design tool is further analyzed using finite element techniques. Additionally, we have built a physical prototype to ensure that the new tool to seamlessly integrate with the bar and to further evaluate by the surgeons who routinely practice the Nuss procedure. In order to validate in the future the final design, we have manufactured wax models that will serve as the patterns in the casting process of metal prototypes. They should provide enough strength to withstand stresses present in the bar straightening process.

A finite element infant eye model to investigate retinal forces in shaken baby syndrome.

BACKGROUND: Shaken baby syndrome (SBS) is a form of abuse in which an infant, typically 6 months or less, is held and submitted to repeated acceleration-deceleration forces. One of the indicators of abuse is bilateral retinal hemorrhaging. A computational model of an infant eye, using the finite element method, is built in order to assess forces at the posterior retina for a shaking and an impact motions. METHOD: The eye model is based on histological studies, diagrams, and materials from previous literature. Motions are applied to the model to simulate a four-cycle shaking motion in 1 second with maximum extension/flexion of the neck. The retinal forces of the shaking motion, at the posterior eye, are compared to an impact pulse (60G) simulating a fall for a total duration of 100 ms. RESULTS: The shaking motion, for the first cycle, shows retinal force means at the posterior eye to be around 0.08 N sustained from the time range of 50 to 200 ms, into the shake, with a peak in excess of 0.2 N. The impulse, area under the curve, is 15 N-ms for 250 msec for the first cycle. The impact simulation reveals a mean retinal force around 0.025 N for a time range of 0 to 26 ms, with a peak force around 0.11 N. Moreover, the impulse for the impact simulation is 13 times lower than the shaking motion. CONCLUSION: The results suggest that shaking alone may be enough to cause retinal hemorrhaging, as there are more sustained and higher forces in the posterior retina, compared to an impact due to a fall. This is in part due to the optic nerve causing more localized stresses in a shaking motion than an impact.

Effects of initial seated position in low speed rear-end impacts: a comparison with the TNO rear impact dummy (TRID) model.

Injury-producing mechanisms associated with rear-end impact collision has remained a mystery not withstanding numerous investigations devoted to its scrutiny. Several criteria have been proposed to predict the injury-causing mechanism, but none have been universally accepted. The challenge lies in determining a set of testing procedures representative of real-world collisions, wherein the results obtained are not only the same as human testing, but remain consistent with various subjects and impact conditions. It is hypothesized that one of the most important considerations in the testing methodology is the effect of initial seated position (ISP) on occupant kinematics during a rear impact collision. This study involves two parts that evaluates the effects of ISP during rear-end impact. In the first part, head acceleration results of computer simulation using Hybrid III TNO rear impact dummy (TRID) are compared to physical impact testing (PIT) of humans. The second part focuses on the computer simulation using TRID to obtain different neck parameters such as NIC (Neck Injury Criterion), NIJ (Neck Injury Predictor), neck forces and moments to predict the level of neck injury such as whiplash associated disorder (WAD) during low speed rear-end impact. In PIT, a total of 17 rear-impact tests were conducted with a nominal 8-km/hour change in velocity to 5 subjects in four different seated positions comprising of a normal position (NP) and three out of positions (OOP). The first position was a NP, defined as torso against the seat back, looking straight ahead, hands on the steering wheel, and feet on the floor. The second position was a head flex position (HFP), defined as the normal position with head flexed forward approximately 20 degrees. The third position was a torso lean position (TLP), defined as the normal position with torso leaned forward approximately 10 degrees away from the seat back. Lastly, a torso lean head flex position (TLHFP), defined as the normal position with the head flexed forward approximately 20 degrees and torso leaned forward approximately 10 degrees. The head acceleration plots from PIT reveal that for the third and fourth positions (TLP and TLHFP) when the subject torso leaned forward, the peak head acceleration for the subject decreased and there was also a delay in reaching the peak. The Hybrid III-TRID anthropomorphic test dummy (ATD) was used in the same four different seated positions using computer simulation software MAthematical DYnamic MOdel (MADYMO 6.0) and the head acceleration results were compared to PIT. The comparison demonstrates that the Hybrid III-TRID ATD with MADYMO can be a reliable testing procedure during low-speed, rear-end impact for the four ISPs considered since the head acceleration plots deviated within the range of PIT head acceleration plots for different human subjects. This ensures that the second part of the study with neck injury using computer simulation results is a reliable testing procedure. It can be observed that MADYMO results have a greater error when compared to PIT when more than one OOP condition is employed as in TLHFP. All these observations would help in providing a tool to better understand the injury mechanisms and provide an accurate testing procedure for rear-end impact.