Sensitivity of knee replacement contact calculations to kinematic measurement errors

Fregly, Benjamin J.; Banks, Scott A.; D’Lima, Darryl D.; Colwell, Clifford W.

doi:10.1002/jor.20548

Cited by 37 publications

(50 citation statements)

References 30 publications

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“…The statistically significant motions at the CMC joint are generally consistent with previously reported patterns of cartilage damage, which typically starts in the volar quadrants of the CMC joint [16,20]. Given the large change in contact pressure that may result even from very little joint motion [10], a follow-up study of changes in joint space and joint congruence at the CMC joint will be useful to quantify the influence of loading and to determine whether mechanical measures other than kinematics may be statistically and clinically different with sex and age.…”

Section: Discussionsupporting

confidence: 87%

In Vivo Kinematics of the Thumb Carpometacarpal Joint During Three Isometric Functional Tasks

Halilaj

Rainbow

Got

et al. 2014

Clinical Orthopaedics &Amp; Related Research

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Background The thumb carpometacarpal (CMC) joint is often affected by osteoarthritis-a mechanically mediated disease. Pathomechanics of the CMC joint, however, are not thoroughly understood due to a paucity of in vivo data. Questions/purposes We documented normal, in vivo CMC joint kinematics during isometric functional tasks. We hypothesized there would be motion of the CMC joint during these tasks and that this motion would differ with sex and age group. We also sought to determine whether the rotations at the CMC joint were coupled and whether the trapezium moved with respect to the third metacarpal. Methods Forty-six asymptomatic subjects were CT-scanned in a neutral position and during three functional tasks (key pinch, jar grasp, jar twist), in an unloaded and a loaded position. Kinematics of the first metacarpal, third metacarpal, and the trapezium were then computed. Results Significant motion was identified in the CMC joint during all tasks. Sex did not have an effect on CMC joint kinematics. Motion patterns differed with age group, but these differences were not systematic across the tasks. Rotation at the CMC joint was generally coupled and posture of the trapezium relative to the third metacarpal changed significantly with thumb position. Conclusions The healthy CMC joint is relatively stable during key pinch, jar grasp, and jar twist tasks, despite sex and age group. Clinical Relevance Our findings indicate that directionally coupled motion patterns in the CMC joint, which lead to a specific loading profile, are similar in men and women. These patterns, in addition to other, nonkinematic influences, especially in the female population, may contribute to the pathomechanics of the osteoarthritic joint.

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Section: Discussionsupporting

confidence: 87%

In Vivo Kinematics of the Thumb Carpometacarpal Joint During Three Isometric Functional Tasks

Halilaj

Rainbow

Got

et al. 2014

Clinical Orthopaedics &Amp; Related Research

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“…This step performed an optimization analysis in Matlab using a six DOF elastic foundation contact model of the subject's femoral component and tibial insert. For each time frame, the optimizer adjusted contact-sensitive DOFs (i.e., superior-inferior translation, varus-valgus rotation, and mediallateral translation [33]) so that calculated contact forces matched measured tibial contact forces, while the remaining DOFs were locked at values from inverse kinematics (flexion angle) and fluoroscopy (anterior-posterior translation and internal-external rotation) [11,34]. The third step estimated patellofemoral kinematics using tibiofemoral kinematics prescribed from the first two steps.…”

Section: Methodsmentioning

confidence: 99%

Muscle Synergies May Improve Optimization Prediction of Knee Contact Forces During Walking

Walter

Kinney

Banks

et al. 2014

Journal of Biomechanical Engineering

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The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a forcemeasuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) CalibrateþMatch where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrateþ Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrateþ Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the CalibrateþMatch case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R 2 ! 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the PrecalibrateþPredict and CalibrateþPredict cases, synergy controls yielded better contact force predictions (0.61 < R 2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R 2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values.

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“…If tibio-femoral bone motion can be measured during physiological activities with a sufficient degree of accuracy, then the FE method can provide important information regarding tissue interactions during these activities. But, tibiofemoral contact is sensitive to kinematic boundary conditions and small variations in knee kinematics (0.1 mm translations and 0.1 • orientations) can result in significant differences in joint contact for natural [12] and prosthetic [13] knee models.…”

Section: Introductionmentioning

confidence: 98%

A subject specific multibody model of the knee with menisci

Guess

Thiagarajan

Kia

et al. 2010

Medical Engineering & Physics

148

111

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Sensitivity of knee replacement contact calculations to kinematic measurement errors

Cited by 37 publications

References 30 publications

In Vivo Kinematics of the Thumb Carpometacarpal Joint During Three Isometric Functional Tasks

In Vivo Kinematics of the Thumb Carpometacarpal Joint During Three Isometric Functional Tasks

Muscle Synergies May Improve Optimization Prediction of Knee Contact Forces During Walking

A subject specific multibody model of the knee with menisci

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