Computational stability of human knee joint at early stance in Gait: Effects of muscle coactivity and anterior cruciate ligament deficiency

Evaluating stability of human spine in static tasks: a combined in vivo-computational study

Various interpretations and parameters have been proposed to assess spinal stability such as antagonist muscle coactivity, trunk stiffness and spinal buckling load; however, the correlation between these parameters remains unknown. We evaluated spinal stability during different tasks while changing the external moment and load height and investigated likely relationships between different EMG- and model-based parameters (e.g., EMG coactivity ratio, trunk stiffness, force coactivity ratio) and stability margins. EMG and kinematics of 40 young healthy subjects were recorded during various quasi-static tasks. Muscle forces, trunk stiffness and stability margins were calculated by a nonlinear subject-specific EMG-assisted-optimization musculoskeletal model of the trunk. The load elevation and external moment increased muscle activities and trunk stiffness while all stability margins (i.e., buckling loads) decreased. The force coactivity ratio was strongly correlated with the hand-load stability margin (i.e., additional weight in hands to initiate instability; R² = 0.54) demonstrating the stabilizing role of abdominal muscles. The total trunk stiffness (Pearson's r = 0.96) and the sum of EMGs of back muscles (Pearson's r = 0.65) contributed the most to the T1 stability margin (i.e., additional required load at T1 for instability/buckling). Force coactivity ratio and trunk stiffness can be used as alternative spinal stability metrics.

Changes in gastrocnemii activation at mid-to-late stance markedly affects the intact and anterior cruciate ligament deficient knee biomechanics and stability in gait

INTRODUCTION

We aimed to quantify the sensitivity in biomechanical response and stability of the intact and anterior cruciate ligament deficient (ACL-D) joints at mid-to-late stance periods of gait to the alterations in activation of gastrocnemii (Gas) muscles.

METHODS

A validated kinematics-driven musculoskeletal finite-element model of the lower extremity is used to compute knee joint response and stability under reported kinetics-kinematics of healthy subjects. Activation in Gas is altered under prescribed gait data at the mid-to-late stance of gait and associated changes in remaining muscle forces/contact forces/areas/ACL force and joint stability are computed in both intact and ACL-D joints.

RESULTS

In the intact joint, the anterior-tibial-translation (ATT) as well as ACL and joint contact forces follow variations in Gas forces. Both the stability and ATT of an ACL-D joint are restored to the near-intact levels when the activity in Gas is reduced. Knee joint instability, excessive ATT as well as larger peak articular contact stresses with a posterior shift in contact areas are estimated under greater Gas forces.

CONCLUSIONS

ACL-D joint is unstable with ATT > 10 mm under larger activities in Gas. Gas is an ACL-antagonist while hamstrings and soleus are ACL-agonists. The near-intact joint stability and ATT of an ACL-D joint can be restored at a lower activation in Gas; or in other words, when activation in ACL-antagonist muscles drops compared with that in ACL-agonist muscles. Results could help analyze the gait of ACL-D copers and non-copers and provide better understanding towards improved preventive, diagnostic, and treatment approaches.

Knee flexion angle and muscle activations control the stability of an anterior cruciate ligament deficient joint in gait

Anterior cruciate ligament (ACL) is a primary structure and a commonly injured ligament of the knee joint. Some patients with ACL deficiency (ACLD) experience joint instability and require a reconstructive surgery to return to daily routines, some can adapt by limiting their activities while others, called copers, can return to high-level activities with no instability. We investigated the effects of alterations in the knee flexion angle (KFA) and muscle force activations on the stability and biomechanics of ACLD joints at 25, 50, and 75% periods of gait stance. ACLD joint stability is controlled by variations in both KFA and knee muscle forces. For the latter, a parameter called activity index is defined as the ratio of forces in ACL antagonists (quadriceps and gastrocnemii) to those in ACL agonists (hamstrings). Under a greater KFA (2-6° beyond the mean of reported values in healthy subjects), an ACLD joint regains its pre-injury stability levels. The ACLD joint stability also markedly improves at smaller quadriceps and larger hamstrings forces (activity indices of 2.0-3.6 at 25%) at the first half of stance and smaller gastrocnemii and larger hamstrings forces (activity indices of 0.1-1.1 at 50% and 0.1-1.2 at 75%) at the second half of stance. Activity index and KFA are both crucial when assessing the dynamic stability of an ACLD joint. These results are helpful in our understanding of the biomechanics and stability of ACLD joints towards improved prevention and treatment strategies.

Muscular activity patterns in 1-legged vs. 2-legged pedaling

BACKGROUND

One-legged pedaling is of interest to elite cyclists and clinicians. However, muscular usage in 1-legged vs. 2-legged pedaling is not fully understood. Thus, the study was aimed to examine changes in leg muscle activation patterns between 2-legged and 1-legged pedaling.

METHODS

Fifteen healthy young recreational cyclists performed both 1-legged and 2-legged pedaling trials at about 30 Watt per leg. Surface electromyography electrodes were placed on 10 major muscles of the left leg. Linear envelope electromyography data were integrated to quantify muscle activities for each crank cycle quadrant to evaluate muscle activation changes.

RESULTS

Overall, the prescribed constant power requirements led to reduced downstroke crank torque and extension-related muscle activities (vastus lateralis, vastus medialis, and soleus) in 1-legged pedaling. Flexion-related muscle activities (biceps femoris long head, semitendinosus, lateral gastrocnemius, medial gastrocnemius, tensor fasciae latae, and tibialis anterior) in the upstroke phase increased to compensate for the absence of contralateral leg crank torque. During the upstroke, simultaneous increases were seen in the hamstrings and uni-articular knee extensors, and in the ankle plantarflexors and dorsiflexors. At the top of the crank cycle, greater hip flexor activity stabilized the pelvis.

CONCLUSION

The observed changes in muscle activities are due to a variety of changes in mechanical aspects of the pedaling motion when pedaling with only 1 leg, including altered crank torque patterns without the contralateral leg, reduced pelvis stability, and increased knee and ankle stiffness during the upstroke.

Usefulness of Muscle Synergy Analysis in Individuals With Knee Osteoarthritis During Gait

OBJECTIVE

To clarify whether there are any muscle synergy changes in individuals with knee osteoarthritis, and to determine whether muscle synergy analysis could be applied to other musculoskeletal diseases.

METHODS

Subjects in this study included 11 young controls (YC), 10 elderly controls (EC), and 10 knee osteoarthritis patients (KOA). Gait was assessed on a split-belt treadmill at 3 km/h. A non-negative matrix factorization (NNMF) was applied to the electromyogram data matrix to extract muscle synergies. To assess the similarity of each module, we performed the NNMF analysis assuming four modules for all of the participants. Further, we calculated joint angles to compare the kinematic data between the module groups.

RESULTS

The number of muscle modules was significantly lower in the EC (2-3) and KOA (2-3) groups than in the YC group (3-4), which reflects the merging of late swing and early stance modules. The EC and KOA groups also showed greater knee flexion angles in the early stance phase. Contrarily, by focusing on the module structure, we found that the merging of early and late stance modules is characteristic in KOA.

CONCLUSION

The lower number of modules in the EC and KOA groups was due to the muscle co-contraction with increased knee flexion angle. Contrarily, the merging of early and late stance modules are modular structures specific to KOA and may be biomarkers for detecting KOA.

SIGNIFICANCE

Describing the changes in multiple muscle control associated with musculoskeletal degeneration can serve as a fundamental biomarker in joint disease.

Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Overall Strategy

Recent explorations of knee biomechanics have benefited from computational modeling, specifically leveraging advancements in finite element analysis and rigid body dynamics of joint and tissue mechanics. A large number of models have emerged with different levels of fidelity in anatomical and mechanical representation. Adapted modeling and simulation processes vary widely, based on justifiable choices in relation to anticipated use of the model. However, there are situations where modelers' decisions seem to be subjective, arbitrary, and difficult to rationalize. Regardless of the basis, these decisions form the "art" of modeling, which impact the conclusions of simulation-based studies on knee function. These decisions may also hinder the reproducibility of models and simulations, impeding their broader use in areas such as clinical decision making and personalized medicine. This document summarizes an ongoing project that aims to capture the modeling and simulation workflow in its entirety-operation procedures, deviations, models, by-products of modeling, simulation results, and comparative evaluations of case studies and applications. The ultimate goal of the project is to delineate the art of a cohort of knee modeling teams through a publicly accessible, transparent approach and begin to unravel the complex array of factors that may lead to a lack of reproducibility. This manuscript outlines our approach along with progress made so far. Potential implications on reproducibility, on science, engineering, and training of modeling and simulation, on modeling standards, and on regulatory affairs are also noted.

Computational analysis of knee joint stability following total knee arthroplasty

The overall objective of this study was to introduce knee joint power as a potential measure to investigate knee joint stability following total knee arthroplasty (TKA). Specific aims were to investigate whether weakened knee joint stabilizers cause abnormal kinematics and how it influences the knee joint kinetic (i.e., power) in response to perturbation. Patient-specific musculoskeletal models were simulated with experimental gait data from six TKA patients (baseline models). Muscle strength and ligament force parameter were reduced by up to 30% to simulate weak knee joint stabilizers (weak models). Two different muscle recruitment criteria were tested to examine whether altered muscle recruitment pattern can mask the influence of weakened stabilizers on the knee joint kinematics and kinetics. Level-walking knee joint kinematics and kinetics were calculated though force-dependent kinematic and inverse dynamic analyses. Bode analysis was then recruited to estimate the knee joint power in response to a simulated perturbation. Weak models resulted in larger anterior-posterior (A-P) displacement and internal-external (I-E) rotation compared to baseline (I-E: 18.4 ± 8.5 vs. 11.6 ± 5.7 (deg), A-P: 9.7 ± 5.6 vs. 5.5 ± 4.1 (mm)). Changes in muscle recruitment criterion however altered the results such that A-P and I-E were not notably different from baseline models. In response to the simulated perturbation, weak models versus baseline models generated a delayed power response with unbounded magnitudes. Perturbed power behavior of the knee remained unaltered regardless of the muscle recruitment criteria. In conclusion, impairment at the knee joint stabilizers may or may not lead to excessive joint motions but it notably affects the knee joint power in response to a perturbation. Whether perturbed knee joint power is associated with the patient-reported outcome requires further investigation.

Can altered neuromuscular coordination restore soft tissue loading patterns in anterior cruciate ligament and menisci deficient knees during walking?

Injuries to the anterior cruciate ligament (ACL) and menisci commonly lead to early onset osteoarthritis. Treatments that can restore normative cartilage loading patterns may mitigate the risk of osteoarthritis, though it is unclear whether such a goal is achievable through conservative rehabilitation. We used musculoskeletal simulation to predict cartilage and ligament loading patterns during walking in intact, ACL deficient, menisci deficient, and ACL-menisci deficient knees. Stochastic simulations with varying coordination strategies were then used to test whether neuromuscular control could be modulated to restore normative knee mechanics in the pathologic conditions. During early stance, a 3 mm increase in anterior tibial translation was predicted in the ACL deficient knee. Mean cartilage contact pressure increased by 18% and 24% on the medial and lateral plateaus, respectively, in the menisci deficient knee. Variations in neuromuscular coordination were insufficient to restore normative cartilage contact patterns in either the ACL or menisci deficient knees. Elevated cartilage contact pressures in the pathologic knees were observed in regions where cartilage wear patterns have previously been reported. These results suggest that altered cartilage tissue loading during gait may contribute to region-specific degeneration patterns, and that varying neuromuscular coordination in isolation is unlikely to restore normative knee mechanics.

Automatic registration of MRI-based joint models to high-speed biplanar radiographs for precise quantification of in vivo anterior cruciate ligament deformation during gait

Understanding in vivo joint mechanics during dynamic activity is crucial for revealing mechanisms of injury and disease development. To this end, laboratories have utilized computed tomography (CT) to create 3-dimensional (3D) models of bone, which are then registered to high-speed biplanar radiographic data captured during movement in order to measure in vivo joint kinematics. In the present study, we describe a system for measuring dynamic joint mechanics using 3D surface models of the joint created from magnetic resonance imaging (MRI) registered to high-speed biplanar radiographs using a novel automatic registration algorithm. The use of MRI allows for modeling of both bony and soft tissue structures. Specifically, the attachment site footprints of the anterior cruciate ligament (ACL) on the femur and tibia can be modeled, allowing for measurement of dynamic ACL deformation. In the present study, we demonstrate the precision of this system by tracking the motion of a cadaveric porcine knee joint. We then utilize this system to quantify in vivo ACL deformation during gait in four healthy volunteers.