Dataset Information

Smooth and accurate predictions of joint contact force time-series in gait using over parameterised deep neural networks.

ABSTRACT: Alterations in joint contact forces (JCFs) are thought to be important mechanisms for the onset and progression of many musculoskeletal and orthopaedic pain disorders. Computational approaches to JCFs assessment represent the only non-invasive means of estimating in-vivo forces; but this cannot be undertaken in free-living environments. Here, we used deep neural networks to train models to predict JCFs, using only joint angles as predictors. Our neural network models were generally able to predict JCFs with errors within published minimal detectable change values. The errors ranged from the lowest value of 0.03 bodyweight (BW) (ankle medial-lateral JCF in walking) to a maximum of 0.65BW (knee VT JCF in running). Interestingly, we also found that over parametrised neural networks by training on longer epochs (>100) resulted in better and smoother waveform predictions. Our methods for predicting JCFs using only joint kinematics hold a lot of promise in allowing clinicians and coaches to continuously monitor tissue loading in free-living environments.

SUBMITTER: Liew BXW

PROVIDER: S-EPMC10350628 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Smooth and accurate predictions of joint contact force time-series in gait using over parameterised deep neural networks.

Liew Bernard X W BXW Rügamer David D Mei Qichang Q Altai Zainab Z Zhu Xuqi X Zhai Xiaojun X Cortes Nelson N

Frontiers in bioengineering and biotechnology 20230703

Alterations in joint contact forces (JCFs) are thought to be important mechanisms for the onset and progression of many musculoskeletal and orthopaedic pain disorders. Computational approaches to JCFs assessment represent the only non-invasive means of estimating <i>in-vivo</i> forces; but this cannot be undertaken in free-living environments. Here, we used deep neural networks to train models to predict JCFs, using only joint angles as predictors. Our neural network models were generally able t ...[more]

PMID: 37465692

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Project description:BackgroundControversy exists regarding the optimal bony fixation technique for lateral meniscal allografts.Purpose/hypothesisThe objective was to quantify knee joint contact mechanics across the lateral plateau for keyhole and bone plug meniscal allograft transplant fixation techniques throughout simulated gait. It was hypothesized that both methods of fixation would improve contact mechanics relative to the meniscectomized condition, while keyhole fixation would restore the distribution of contact stress closer to that of the intact knee.Study designControlled laboratory study.MethodsSix human cadaveric knees were mounted on a multidirectional dynamic simulator and subjected to the following conditions: (1) native intact meniscus, (2) keyhole fixation of the native meniscus, (3) bone plug fixation of the native meniscus, and (4) meniscectomy. Contact area, peak contact stress, and the distribution of stress across the tibial plateau were computed at 14% and 45% of the gait cycle, at which axial forces are at their highest. Translation of the weighted center of contact stress throughout simulated gait was computed.ResultsBoth bony fixation techniques improved contact mechanics relative to the meniscectomized condition. The keyhole technique was not significantly different from the intact condition for the following metrics: contact area, peak contact stress, distribution of force between the meniscal footprint and cartilage-to-cartilage contact, and the position of the weighted center of contact. In contrast, bone plug fixation resulted in a significant decrease of 21% to 28% in contact area at 14% and 45% of the simulated gait cycle, a significant increase in peak contact stresses of 34% at 45% of the gait cycle, and a shift in the weighted center of contact, which increased forces in the cartilage-to-cartilage contact area at 45% of the gait cycle.ConclusionWhile both keyhole and bone plug fixation methods improved lateral compartment contact mechanics relative to the meniscectomized knee, keyhole fixation restored contact mechanics closer to that of the intact knee.Clinical relevanceMethod of meniscal fixation is under the direct control of the surgeon. From a biomechanics perspective, keyhole fixation is advocated for its ability to mimic intact knee joint contact mechanics.

Dataset Information

Smooth and accurate predictions of joint contact force time-series in gait using over parameterised deep neural networks.

Publications

Smooth and accurate predictions of joint contact force time-series in gait using over parameterised deep neural networks.

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