Changes in In Vivo Knee Contact Forces through Gait Modification

Gait modification represents a non-invasive method for reducing knee joint loading in patients with knee osteoarthritis. Previous studies have shown that a variety of gait modifications are effective in reducing the external knee adduction moment. The external knee adduction moment is often used as a surrogate measure of medial compartment force. However, a recent study showed that reductions in the external knee adduction moment do not guarantee reductions in medial compartment loads. Therefore, direct measurement of changes in knee contact force is important for determining the effectiveness of gait modifications. A previous study found that medial thrust gait and walking with hiking poles reduced contact force in a patient with a force-measuring knee replacement. The purpose of this study was to investigate the effects of additional gait modifications (mild crouch, moderate crouch, forefoot strike and bouncy gait) and four configurations of hiking poles on medial and lateral contact forces measured by a force-measuring knee replacement

Muscle Synergies Improve Estimation of Knee Contact Forces during Walking

This study investigates whether use of subject-specific muscle synergies can improve optimization predictions of muscle excitation patterns and knee contact forces during walking. Muscle synergies describe how a small number of neural commands generated by the nervous system can be linearly combined to produce the broad range of muscle electromyographic (EMG) signals measured experimentally. By quantifying the interdependence of individual EMG signals, muscle synergies provide dimensionality reduction for the neural control redundancy problem. Our hypothesis was that use of subjectspecific muscle synergies to limit muscle excitation patterns would improve prediction of muscle EMG patterns at the hip, knee, and ankle and of contact forces at the knee using a subject-specific lower body musculoskeletal computer model. The predictions were evaluated against in vivo experimental data collected from a subject implanted with a force-measuring tibial prosthesis

Synergies Controls Improve Prediction of Knee Contact Forces and Muscle Excitations during Gait

This study investigates whether use of muscle excitation controls constructed from subjectspecific muscle synergy information can improve optimization prediction of knee contact forces and muscle excitations during walking. Muscle synergies quantify how a large number of experimental muscle electromyographic (EMG) signals can be reconstructed by linearly mixing a much smaller number of neural commands generated by the nervous system. Our hypothesis was that controlling all muscle excitations with a small set of experimentally calculated neural commands would improve prediction of knee contact forces and leg muscle excitations compared to using independently controlled muscle excitations

Reproducibility in modeling and simulation of the knee:Academic, industry, and regulatory perspectives

Stakeholders in the modeling and simulation (M&amp;S) community organized a workshop at the 2019 Annual Meeting of the Orthopaedic Research Society (ORS) entitled “Reproducibility in Modeling and Simulation of the Knee: Academic, Industry, and Regulatory Perspectives.” The goal was to discuss efforts among these stakeholders to address irreproducibility in M&amp;S focusing on the knee joint. An academic representative from a leading orthopedic hospital in the United States described a multi-institutional, open effort funded by the National Institutes of Health to assess model reproducibility in computational knee biomechanics. A regulatory representative from the United States Food and Drug Administration indicated the necessity of standards for reproducibility to increase utility of M&amp;S in the regulatory setting. An industry representative from a major orthopedic implant company emphasized improving reproducibility by addressing indeterminacy in personalized modeling through sensitivity analyses, thereby enhancing preclinical evaluation of joint replacement technology. Thought leaders in the M&amp;S community stressed the importance of data sharing to minimize duplication of efforts. A survey comprised 103 attendees revealed strong support for the workshop and for increasing emphasis on computational modeling at future ORS meetings. Nearly all survey respondents (97%) considered reproducibility to be an important issue. Almost half of respondents (45%) tried and failed to reproduce the work of others. Two-thirds of respondents (67%) declared that individual laboratories are most responsible for ensuring reproducible research whereas 44% thought that journals are most responsible. Thought leaders and survey respondents emphasized that computational models must be reproducible and credible to advance knee M&amp;S.</p

3D trunk orientation measured using inertial measurement units during anatomical and dynamic sports motions

Trunk motion is related to the performance and risk of injuries during dynamic sports motions. Optical motion capture is traditionally used to measure trunk motion during dynamic sports motions, but these systems are typically constrained to a laboratory environment. Inertial measurement units (IMUs) might provide a suitable alternative for measuring the trunk orientation during dynamic sports motions. The objective of the present study was to assess the accuracy of the three-dimensional trunk orientation measured using IMUs during dynamic sports motions and isolated anatomical trunk motions. The motions were recorded with two IMUs and an optical motion capture system (gold standard). Ten participants performed a total of 71 sports motions (19 golf swings, 15 one-handed ball throws, 19 tennis serves, and 18 baseball swings) and 125 anatomical trunk motions (42, 41, and 42 trials of lateral flexion, axial rotation, and flexion/extension, respectively). The root-mean-square differences between the IMU- and optical motion capture-based trunk angles were less than 5 degrees, and the similarity between the methods was on average across all trials “very good” to “excellent” (R ≥ 0.85; R2 ≥ 0.80). Across the dynamic sports motions, even higher measures of similarity were found (R ≥ 0.90; R2 ≥ 0.82). When aligned to the relevant segment, the current IMUs are a promising alternative to optical motion capture and previous presented IMU-based systems for the field-based measurement of the three-dimensional trunk orientation during dynamic sports motions and the anatomical trunk motions

Update on Grand Challenge Competition to Predict in Vivo Knee Loads

Validation is critical if clinicians are to use musculoskeletal models to optimize treatment of individual patients with a variety of musculoskeletal disorders. This paper provides an update on the annual Grand Challenge Competition to Predict in Vivo Knee Loads, a unique opportunity for direct validation of knee contact forces and indirect validation of knee muscle forces predicted by musculoskeletal models. Three competitions (2010, 2011, and 2012) have been held at the annual American Society of Mechanical Engineers Summer Bioengineering Conference, and two more competitions are planned for the 2013 and 2014 conferences. Each year of the competition, a comprehensive data set collected from a single subject implanted with a force-measuring knee replacement is released. Competitors predict medial and lateral knee contact forces for two gait trials without knowledge of the experimental knee contact force measurements. Predictions are evaluated by calculating root-mean-square (RMS) errors and R(2) values relative to the experimentally measured medial and lateral contact forces. For the first three years of the competition, competitors used a variety of methods to predict knee contact and muscle forces, including static and dynamic optimization, EMG-driven models, and parametric numerical models. Overall, errors in predicted contact forces were comparable across years, with average RMS errors for the four competition winners ranging from 229 N to 312 N for medial contact force and from 238 N to 326 N for lateral contact force. Competitors generally predicted variations in medial contact force (highest R(2 )= 0.91) better than variations in lateral contact force (highest R(2 )= 0.70). Thus, significant room for improvement exists in the remaining two competitions. The entire musculoskeletal modeling community is encouraged to use the competition data and models for their own model validation efforts