scholarly journals Electromyography-Driven Forward Dynamics Simulation to Estimate In Vivo Joint Contact Forces During Normal, Smooth, and Bouncy Gaits

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Swithin S. Razu ◽  
Trent M. Guess
Keyword(s):  
Contact Force ◽  
Temporal Patterns ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Dynamics Simulation ◽  
Muscle Forces ◽  
Model Predictions ◽  
Subject Specific ◽  
Full Body

Computational models that predict in vivo joint loading and muscle forces can potentially enhance and augment our knowledge of both typical and pathological gaits. To adopt such models into clinical applications, studies validating modeling predictions are essential. This study created a full-body musculoskeletal model using data from the “Sixth Grand Challenge Competition to Predict in vivo Knee Loads.” This model incorporates subject-specific geometries of the right leg in order to concurrently predict knee contact forces, ligament forces, muscle forces, and ground contact forces. The objectives of this paper are twofold: (1) to describe an electromyography (EMG)-driven modeling methodology to predict knee contact forces and (2) to validate model predictions by evaluating the model predictions against known values for a patient with an instrumented total knee replacement (TKR) for three distinctly different gait styles (normal, smooth, and bouncy gaits). The model integrates a subject-specific knee model onto a previously validated generic full-body musculoskeletal model. The combined model included six degrees-of-freedom (6DOF) patellofemoral and tibiofemoral joints, ligament forces, and deformable contact forces with viscous damping. The foot/shoe/floor interactions were modeled by incorporating shoe geometries to the feet. Contact between shoe segments and the floor surface was used to constrain the shoe segments. A novel EMG-driven feedforward with feedback trim motor control strategy was used to concurrently estimate muscle forces and knee contact forces from standard motion capture data collected on the individual subject. The predicted medial, lateral, and total tibiofemoral forces represented the overall measured magnitude and temporal patterns with good root-mean-squared errors (RMSEs) and Pearson's correlation (p2). The model accuracy was high: medial, lateral, and total tibiofemoral contact force RMSEs = 0.15, 0.14, 0.21 body weight (BW), and (0.92 < p2 < 0.96) for normal gait; RMSEs = 0.18 BW, 0.21 BW, 0.29 BW, and (0.81 < p2 < 0.93) for smooth gait; and RMSEs = 0.21 BW, 0.22 BW, 0.33 BW, and (0.86 < p2 < 0.95) for bouncy gait, respectively. Overall, the model captured the general shape, magnitude, and temporal patterns of the contact force profiles accurately. Potential applications of this proposed model include predictive biomechanics simulations, design of TKR components, soft tissue balancing, and surgical simulation.

scholarly journals Prediction of knee loading in native knee and total knee arthroplasty : a forward dynamics computational study

2019 ◽  
Author(s):  
◽  
Swithin Samuel Razu
Keyword(s):  
Total Knee Arthroplasty ◽  
Knee Arthroplasty ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Muscle Forces ◽  
Model Predictions ◽  
Subject Specific ◽  
Joint Contact ◽  
Total Knee

"The goal of this dissertation is to develop a musculoskeletal model and corroborate model predictions to experimentally measured in vivo knee contact forces, in order to study the biomechanical consequences of two different total knee arthroplasty designs. The two main contributions of this dissertation are: (1) Corroboration to experimental data: The development of an EMG-driven, full-body, musculoskeletal model with subject-specific leg geometries including deformable contacts, ligaments, 6DOF knee joint, and a shoe-floor model that can concurrently predict muscle forces, ligament forces, and joint contact forces. Model predictions of tibiofemoral joint contact forces were evaluated against the subject-specific in vivo measurements from the instrumented TKR for three distinctly different styles of over ground gait. (2) Virtual surgery in TKA: The musculoskeletal modeling methodology was then used to develop a model for one healthy participant with a native knee and then virtually replacing the native knee with fixed-bearing and mobile-bearing total knee arthroplasty designs performing gait and step-up tasks. This approach minimized the biomechanical impact of variations in sex, geometry, implant size, design and positioning, ligament location and tension, and muscle forces found across patients. The differences in biomechanics were compared for the two designs. 1.2 Significance of this Research The world health organization ranks musculoskeletal disorders as the second largest contributor to disability worldwide. Conservative estimates put the national cost of direct care for musculoskeletal disease at $212.7 billion a year [1]. Many people who suffer from neuromuscular or musculoskeletal diseases may benefit from the insights gained from surgery simulations, since musculoskeletal reconstructions are commonly performed on these individuals. Improved surgical outcomes will benefit these individuals not only in the short-term, but also in the long-term, since their future rehabilitation needs may be reduced. For example, although total knee arthroplasty is a common surgical procedure for the treatment of osteoarthritis with over 700,000 procedures performed each year [2], many patients are unhappy with the ultimate results [3]. Ten to 30% of patients report [4] pain, dissatisfaction with function, and the need for further surgery such as revision after the initial surgery resulting in costs exceeding $11 billion [5]. Potentially, simulation studies that quantify the important biomechanical variables will reduce the need for revision surgeries in patients."--Introduction.

scholarly journals Concurrent Prediction of Muscle and Tibiofemoral Contact Forces During Treadmill Gait

2014 ◽  
Vol 136 (2) ◽  
Author(s):  
Trent M. Guess ◽  
Antonis P. Stylianou ◽  
Mohammad Kia
Keyword(s):  
Femoral Component ◽  
Gait Cycle ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Grand Challenge ◽  
Subject Specific ◽  
The Right ◽  
Anterior Posterior ◽  
Rms Errors

Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the “Grand Challenge Competition to Predict in-vivo Knee Loads” for the 2013 American Society of Mechanical Engineers Summer Bioengineering Conference (Fregly et al., 2012, “Grand Challenge Competition to Predict in vivo Knee Loads,” J. Orthop. Res., 30, pp. 503–513) to develop a full body, musculoskeletal model with subject specific right leg geometries that can concurrently predict muscle forces, ligament forces, and knee and ground contact forces. The model includes representation of foot/floor interactions and predicted tibiofemoral joint loads were compared to measured tibial loads for two different cycles of treadmill gait. The model used anthropometric data (height and weight) to scale the joint center locations and mass properties of a generic model and then used subject bone geometries to more accurately position the hip and ankle. The musculoskeletal model included 44 muscles on the right leg, and subject specific geometries were used to create a 12 degrees-of-freedom anatomical right knee that included both patellofemoral and tibiofemoral articulations. Tibiofemoral motion was constrained by deformable contacts defined between the tibial insert and femoral component geometries and by ligaments. Patellofemoral motion was constrained by contact between the patellar button and femoral component geometries and the patellar tendon. Shoe geometries were added to the feet, and shoe motion was constrained by contact between three shoe segments per foot and the treadmill surface. Six-axis springs constrained motion between the feet and shoe segments. Experimental motion capture data provided input to an inverse kinematics stage, and the final forward dynamics simulations tracked joint angle errors for the left leg and upper body and tracked muscle length errors for the right leg. The one cycle RMS errors between the predicted and measured tibia contact were 178 N and 168 N for the medial and lateral sides for the first gait cycle and 209 N and 228 N for the medial and lateral sides for the faster second gait cycle. One cycle RMS errors between predicted and measured ground reaction forces were 12 N, 13 N, and 65 N in the anterior-posterior, medial-lateral, and vertical directions for the first gait cycle and 43 N, 15 N, and 96 N in the anterior-posterior, medial-lateral, and vertical directions for the second gait cycle.

Intra-Articular Knee Contact Force Estimation During Walking Using Force-Reaction Elements and Subject-Specific Joint Model2

2016 ◽  
Vol 138 (2) ◽  
Author(s):  
Yihwan Jung ◽  
Cong-Bo Phan ◽  
Seungbum Koo
Keyword(s):  
Contact Force ◽  
Inverse Dynamics ◽  
Reaction Force ◽  
Muscle Tension ◽  
Contact Forces ◽  
Contact Model ◽  
Grand Challenge ◽  
Subject Specific ◽  
Mean Square Errors

Joint contact forces measured with instrumented knee implants have not only revealed general patterns of joint loading but also showed individual variations that could be due to differences in anatomy and joint kinematics. Musculoskeletal human models for dynamic simulation have been utilized to understand body kinetics including joint moments, muscle tension, and knee contact forces. The objectives of this study were to develop a knee contact model which can predict knee contact forces using an inverse dynamics-based optimization solver and to investigate the effect of joint constraints on knee contact force prediction. A knee contact model was developed to include 32 reaction force elements on the surface of a tibial insert of a total knee replacement (TKR), which was embedded in a full-body musculoskeletal model. Various external measurements including motion data and external force data during walking trials of a subject with an instrumented knee implant were provided from the Sixth Grand Challenge Competition to Predict in vivo Knee Loads. Knee contact forces in the medial and lateral portions of the instrumented knee implant were also provided for the same walking trials. A knee contact model with a hinge joint and normal alignment could predict knee contact forces with root mean square errors (RMSEs) of 165 N and 288 N for the medial and lateral portions of the knee, respectively, and coefficients of determination (R2) of 0.70 and −0.63. When the degrees-of-freedom (DOF) of the knee and locations of leg markers were adjusted to account for the valgus lower-limb alignment of the subject, RMSE values improved to 144 N and 179 N, and R2 values improved to 0.77 and 0.37, respectively. The proposed knee contact model with subject-specific joint model could predict in vivo knee contact forces with reasonable accuracy. This model may contribute to the development and improvement of knee arthroplasty.

Evaluation of Predicted Knee Joint Muscle Forces During Gait Using an Instrumented Knee Implant

2008 ◽  
Author(s):  
Justin W. Fernandez ◽  
Hyung J. Kim ◽  
Massoud Akbarshahi ◽  
Jonathan P. Walter ◽  
Benjamin J. Fregly ◽  
...  
Keyword(s):  
Contact Forces ◽  
In Vivo Studies ◽  
Muscle Forces ◽  
Model Calculations ◽  
Musculoskeletal Models ◽  
Model Predictions ◽  
Joint Contact ◽  
Knee Muscle

Many studies have used musculoskeletal models to predict in vivo muscle forces at the knee during gait [1, 2]. Unfortunately, quantitative assessment of the model calculations is often impracticable. Various indirect methods have been used to evaluate the accuracy of model predictions, including comparisons against measurements of muscle activity, joint kinematics, ground reaction forces, and joint moments. In a recent study, an instrumented hip implant was used to validate calculations of hip contact forces directly [3]. The same model was subsequently used to validate model calculations of tibiofemoral loading during gait [4]. Instrumented knee implants have also been used in in vitro and in vivo studies to quantify differences in biomechanical performance between various TKR designs [5, 6]. The main aim of the present study was to evaluate model predictions of knee muscle forces by direct comparison with measurements obtained from an instrumented knee implant. Calculations of muscle and joint-contact loading were performed for level walking at slow, normal, and fast speeds.

scholarly journals An Electromyogram-Driven Musculoskeletal Model of the Knee to Predict in Vivo Joint Contact Forces During Normal and Novel Gait Patterns

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Kurt Manal ◽  
Thomas S. Buchanan
Keyword(s):  
Knee Joint ◽  
Contact Force ◽  
Contact Forces ◽  
Grand Challenge ◽  
Normal Walking ◽  
Gait Patterns ◽  
Internal Joint ◽  
Model Predictions ◽  
Joint Contact

Computational models that predict internal joint forces have the potential to enhance our understanding of normal and pathological movement. Validation studies of modeling results are necessary if such models are to be adopted by clinicians to complement patient treatment and rehabilitation. The purposes of this paper are: (1) to describe an electromyogram (EMG)-driven modeling approach to predict knee joint contact forces, and (2) to evaluate the accuracy of model predictions for two distinctly different gait patterns (normal walking and medial thrust gait) against known values for a patient with a force recording knee prosthesis. Blinded model predictions and revised model estimates for knee joint contact forces are reported for our entry in the 2012 Grand Challenge to predict in vivo knee loads. The EMG-driven model correctly predicted that medial compartment contact force for the medial thrust gait increased despite the decrease in knee adduction moment. Model accuracy was high: the difference in peak loading was less than 0.01 bodyweight (BW) with an R2 = 0.92. The model also predicted lateral loading for the normal walking trial with good accuracy exhibiting a peak loading difference of 0.04 BW and an R2 = 0.44. Overall, the EMG-driven model captured the general shape and timing of the contact force profiles and with accurate input data the model estimated joint contact forces with sufficient accuracy to enhance the interpretation of joint loading beyond what is possible from data obtained from standard motion capture studies.

scholarly journals Update on Grand Challenge Competition to Predict in Vivo Knee Loads

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Allison L. Kinney ◽  
Thor F. Besier ◽  
Darryl D. D'Lima ◽  
Benjamin J. Fregly
Keyword(s):  
Contact Force ◽  
Contact Forces ◽  
Single Subject ◽  
Grand Challenge ◽  
Muscle Forces ◽  
Data Set ◽  
Lateral Contact ◽  
Musculoskeletal Models ◽  
Rms Errors

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 R2 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 R2 = 0.91) better than variations in lateral contact force (highest R2 = 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.

scholarly journals Subject-Specific Finite Element Modeling of the Tibiofemoral Joint Based on CT, Magnetic Resonance Imaging and Dynamic Stereo-Radiography Data in Vivo

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
Robert E. Carey ◽  
Liying Zheng ◽  
Ameet K. Aiyangar ◽  
Christopher D. Harner ◽  
Xudong Zhang
Keyword(s):  
Magnetic Resonance Imaging ◽  
Finite Element ◽  
Magnetic Resonance ◽  
Contact Area ◽  
Resonance Imaging ◽  
Model Predictions ◽  
Subject Specific ◽  
Skeletal Kinematics ◽  
Tibiofemoral Kinematics

In this paper, we present a new methodology for subject-specific finite element modeling of the tibiofemoral joint based on in vivo computed tomography (CT), magnetic resonance imaging (MRI), and dynamic stereo-radiography (DSX) data. We implemented and compared two techniques to incorporate in vivo skeletal kinematics as boundary conditions: one used MRI-measured tibiofemoral kinematics in a nonweight-bearing supine position and allowed five degrees of freedom (excluding flexion-extension) at the joint in response to an axially applied force; the other used DSX-measured tibiofemoral kinematics in a weight-bearing standing position and permitted only axial translation in response to the same force. Verification and comparison of the model predictions employed data from a meniscus transplantation study subject with a meniscectomized and an intact knee. The model-predicted cartilage-cartilage contact areas were examined against “benchmarks” from a novel in situ contact area analysis (ISCAA) in which the intersection volume between nondeformed femoral and tibial cartilage was characterized to determine the contact. The results showed that the DSX-based model predicted contact areas in close alignment with the benchmarks, and outperformed the MRI-based model: the contact centroid predicted by the former was on average 85% closer to the benchmark location. The DSX-based FE model predictions also indicated that the (lateral) meniscectomy increased the contact area in the lateral compartment and increased the maximum contact pressure and maximum compressive stress in both compartments. We discuss the importance of accurate, task-specific skeletal kinematics in subject-specific FE modeling, along with the effects of simplifying assumptions and limitations.

Development of a Full Flexion 3D Musculoskeletal Model of the Knee Considering Intersegmental Contact During High Knee Flexion Movements

2020 ◽  
Vol 36 (6) ◽  
pp. 444-456
Author(s):  
David C. Kingston ◽  
Stacey M. Acker
Keyword(s):  
Body Weight ◽  
Knee Flexion ◽  
Knee Extensor ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Model Verification ◽  
In Vivo Studies ◽  
Muscle Groups ◽  
The Right

A musculoskeletal model of the right lower limb was developed to estimate 3D tibial contact forces in high knee flexion postures. This model determined the effect of intersegmental contact between thigh–calf and heel–gluteal structures on tibial contact forces. This model includes direct tracking and 3D orientation of intersegmental contact force, femoral translations from in vivo studies, wrapping of knee extensor musculature, and a novel optimization constraint for multielement muscle groups. Model verification consisted of calculating the error between estimated tibial compressive forces and direct measurements from the Grand Knee Challenge during movements to ∼120° of knee flexion as no high knee flexion data are available. Tibial compression estimates strongly fit implant data during walking (R2 = .83) and squatting (R2 = .93) with a root mean squared difference of .47 and .16 body weight, respectively. Incorporating intersegmental contact significantly reduced model estimates of peak tibial anterior–posterior shear and increased peak medial–lateral shear during the static phase of high knee flexion movements by an average of .33 and .07 body weight, respectively. This model supports prior work in that intersegmental contact is a critical parameter when estimating tibial contact forces in high knee flexion movements across a range of culturally and occupationally relevant postures.

Optimization of Quadriceps Force Distribution for Minimization of Patellofemoral Contact Pressure During a Squat

2007 ◽  
Author(s):  
Aarthi S. Shankar ◽  
Trent M. Guess
Keyword(s):  
Contact Pressure ◽  
Vastus Lateralis ◽  
Rectus Femoris ◽  
Strong Relationship ◽  
Lateral Force ◽  
Quadriceps Muscle ◽  
Contact Forces ◽  
In Vivo Studies ◽  
Muscle Forces

Patellofemoral Pain (PFP) syndrome is a very common knee disorder. A possible cause may be excessive lateral force applied by the quadriceps and the patellar tendon producing an abnormal distribution of force and pressure within the patellofemoral joint [1]. EMG and in-vivo studies have been conducted to understand the function of the quadriceps and its relationship with PFP [2,3]. These studies suggest a strong relationship between muscle forces and PFP which originates from high lateral retropatellar contact forces. A dynamic computational model of the knee was developed which includes the quadriceps muscles Rectus Femoris (RF), Vastus Intermedius (VI), Vastus Lateralis (VL), and Vastus Medialis (VM) represented as force vectors. The model can predict retro-patellar contact pressures and the action of the individual quadriceps muscles based on the predicted pressures. The objective of this study was to develop a control system which could optimize the distribution of quadriceps muscle forces to minimize contact pressure between the patella and the femur of the knee during a squat.

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