Comparison of ISO Standard and TKR patient axial force profiles during the stance phase of gait

Ngai, Valentina; Wimmer, Markus A.

doi:10.1177/0954411911431650

Cited by 16 publications

(13 citation statements)

References 26 publications

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“…Because the mathematical modeling has much advanced since then, it can be expected that the new in vivo data deviate from the ISO loads. This expectation is supported by a comparison of the axial ISO force with the resultant forces during walking, obtained analytically as well as measured in our patients [22] . During the first 60% of the stance phase both loads differed markedly.…”

Section: Introductionsupporting

confidence: 82%

Standardized Loads Acting in Knee Implants

et al. 2014

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The loads acting in knee joints must be known for improving joint replacement, surgical procedures, physiotherapy, biomechanical computer simulations, and to advise patients with osteoarthritis or fractures about what activities to avoid. Such data would also allow verification of test standards for knee implants. This work analyzes data from 8 subjects with instrumented knee implants, which allowed measuring the contact forces and moments acting in the joint. The implants were powered inductively and the loads transmitted at radio frequency. The time courses of forces and moments during walking, stair climbing, and 6 more activities were averaged for subjects with I) average body weight and average load levels and II) high body weight and high load levels. During all investigated activities except jogging, the high force levels reached 3,372–4,218N. During slow jogging, they were up to 5,165N. The peak torque around the implant stem during walking was 10.5 Nm, which was higher than during all other activities including jogging. The transverse forces and the moments varied greatly between the subjects, especially during non-cyclic activities. The high load levels measured were mostly above those defined in the wear test ISO 14243. The loads defined in the ISO test standard should be adapted to the levels reported here. The new data will allow realistic investigations and improvements of joint replacement, surgical procedures for tendon repair, treatment of fractures, and others. Computer models of the load conditions in the lower extremities will become more realistic if the new data is used as a gold standard. However, due to the extreme individual variations of some load components, even the reported average load profiles can most likely not explain every failure of an implant or a surgical procedure.

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Section: Introductionsupporting

confidence: 82%

Standardized Loads Acting in Knee Implants

et al. 2014

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“…First, we changed our original assumption that knee anterior-posterior translation was the same as that of another patient with a similar prosthesis during normal walking, and that anterior-posterior translation did not occur during medial thrust gait. Instead, we modified the average anterior-posterior translation from a subset of TKR patients with NexGen CR prostheses previously evaluated in our laboratory [22,23] for use with the competition data. An anterior-posterior translation profile was created from the profile of a subset of patients with high total anterior-posterior translation during walking gait cycles [24].…”

Section: Methodsmentioning

confidence: 99%

Fine Tuning Total Knee Replacement Contact Force Prediction Algorithms Using Blinded Model Validation

Knowlton

Wimmer

2013

Journal of Biomechanical Engineering

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The purpose of this study was to perform a blinded comparison of model predictions of total knee replacement contact forces to in vivo forces from an instrumented prosthesis during normal walking and medial thrust gait by participating in the “Third Grand Challenge Competition to Predict in vivo Knee Loads.” We also evaluated model assumptions that were critical for accurate force predictions. Medial, lateral, and total axial forces through the knee were calculated using a previously developed and validated parametric numerical model. The model uses equilibrium equations between internal and external moments and forces to obtain knee joint contact forces and calculates a range of forces at instances during the gait cycle through parametric variation of muscle activity levels. For 100 instances during a normal over-ground gait cycle, model root mean square differences from eTibia data were 292, 248, and 281 for medial, lateral, and total contact forces, respectively. For 100 instances during a medial thrust gait cycle, model root mean square differences from eTibia data were 332, 234, and 470 for medial, lateral, and total contact forces, respectively. The percent difference between measured and predicted peak total axial force was 2.89% at the first peak and 9.36% at the second peak contact force for normal walking and 3.94% at the first peak and 14.86% at the second peak contact force for medial thrust gait. After unblinding, changes to model assumptions improved medial and lateral force predictions for both gait styles but did not improve total force predictions. Axial forces computed with the model compared well to the eTibia data under blinded and unblinded conditions. Knowledge of detailed knee kinematics, namely anterior-posterior translation, appears to be critical in obtaining accurate force predictions.

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“…The computational framework accurately predicts TKA contact forces. To date, TKA contact forces have been predicted for 35 patients with four different implant types [6][7][8]. Forces have been calculated for walking, chair, and stair activities.…”

Section: Discussion and Future Outlookmentioning

confidence: 99%

Computational Framework for Determining Patient-Specific Total Knee Arthroplasty Loading

Wimmer

2013

ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation

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The demand for total knee arthroplasty (TKA) is increasing steadily. In 2007, Kurtz et al. [1] predicted that TKA procedures would increase from 402,100 in 2003 to 3.48 million by 2030. Recent US national inpatient survey data have borne out these trends [2, 3]. Furthermore, demand is growing fastest in people younger than 65 [4] — patients who will need their implants to last the longest. The major factors limiting prosthesis longevity involve wear of the polyethylene bearing surfaces. Wear continues to be a problem at the knee; for example, advances that reduce hip implant wear such as crosslinking of polyethylene are not widely used in TKA due to fears of early material breakdown under knee loading conditions [5]. Preclinical TKA testing is performed with knee wear simulators under generic walking conditions. Efforts are ongoing by us [6] and others [7] to improve the physiological relevance of current testing standards. Nevertheless, a simulator would need to run ∼eight months continuously to simulate 20 years of walking, assuming one-million steps per year and speed of one cycle per second. As a complementary tool, computational models can test multiple conditions efficiently and ensure a faster turnaround time in the design process to eliminate inferior designs earlier. The purpose of this work is to describe a computational framework for predicting TKA loading, and ultimately implant longevity, on a patient-specific basis. The rationale is that, after developing a patient-specific computational framework, TKA designs of any material and under any patient behavior can be modulated to promote contact conditions best for implant longevity.

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Comparison of ISO Standard and TKR patient axial force profiles during the stance phase of gait

Cited by 16 publications

References 26 publications

Standardized Loads Acting in Knee Implants

Standardized Loads Acting in Knee Implants

Fine Tuning Total Knee Replacement Contact Force Prediction Algorithms Using Blinded Model Validation

Computational Framework for Determining Patient-Specific Total Knee Arthroplasty Loading

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