Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.10.24.761008

Extending Musculoskeletal Modelling Validation Beyond Gait: Knee Loading and Kinematics During Daily Activities

Abstract

Musculoskeletal (MSK) modelling enables non-invasive estimation of internal body loads, which could inform the design of novel orthopedic implants and guide personalized treatment strategies. Extensive validation is a pre-requisite for the translation of MSK-modelling frameworks into clinical applications. This study validates predicted knee loads and local kinematics across multiple activities of daily living (ADLs) using motion-capture data from 184 activity cycles collected in six subjects performing five ADLs from the CAMS-Knee datasets. Personalized models incorporated subject-specific anthropometric, radiographic, and implantation data, along with a 6-DOF elastic-foundation contact model between implant components and a surgically balanced ligament model derived from cadaveric testing. Across activities, predicted knee contact force magnitudes showed good agreement with instrumented implant measurements (RMSE 0.46 BW; R2 = 0.81). The highest accuracy was found during level walking, whereas stair descent exhibited the largest discrepancies. Predicted implant kinematics showed qualitatively similar trends to fluoroscopic measurements across all ADLs, although with varying levels of accuracy across different degrees of freedom. EMG comparisons revealed broadly consistent activation timing between model predictions and experimental data, although gastrocnemius activation was poorly estimated during stair descent and downhill walking. By validating MSK model predictions across the complete range of activities available in the CAMS-Knee datasets, this study extends validation beyond previously analysed gait or bending tasks and reveals activity-specific discrepancies that reflect current limitations in modelling assumptions and would remain undetected in single-activity analyses. These findings provide a robust basis for future refinement of MSK models and support their development toward clinically meaningful applications.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

De Pieri, E., Sarabadani Tafreshi, S. C., Hörmann, S., Lund, M. E., Damm, P., Schütz, P., Taylor, W. R., Bandi, M., Seebeck, J.. 2026-10-27. Extending Musculoskeletal Modelling Validation Beyond Gait: Knee Loading and Kinematics During Daily Activities. https://doi.org/10.64898/2026.10.24.761008

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Mesoscale Soft Robotics for Mechanically Perturbing and Functionally Monitoring Responses in Human Organoids

Human organoids represent promising models for studies of significance to the biology and medical communities. Of the existing approaches for monitoring organoids, none offers the ability to apply programmable mechanical forces while simultaneously recording multi-modal physiological responses, of relevance to phenomena spanning from traumatic brain injuries to cardiac rhythm disorders. Here, we present a mesoscale soft robotic organoid interface that enables programmable delivery of forces to organoids of diverse shapes, and to map electrophysiological activity and mechanical responses. The platform combines actuation elements with integrated sensors for quantitative measurement and control. Studies using this technology reveal that spheroidal cortical organoids exhibit distinct responses to mechanical trauma, including silencing, recovery, and changes in neuronal firing patterns. Additional experiments on cardiac ring tissues demonstrate that sustained stretching induces beat-to-beat rhythm variability and altered conduction. The results establish a framework for investigating force-triggered transitions between physiological and disease-like states in human tissue models.

bioengineering↗

Few-shot regulatory sequence design with a genomic language model

A central challenge in generative biology is translating knowledge learned from natural sequences and experiments into designs with desired functions. In-context learning (ICL) is an emergent capability of large language models that allows them to adapt to new tasks from a few examples without additional training, enabling these models to become general-purpose learners. Here, we show that the genome language model, Evo 2, exhibits generative ICL in biological sequence design. Prompting with just tens of examples conditions Evo 2 to generate novel and diverse regulatory DNA sequences without any additional training. Mechanistic analysis suggests that genomic ICL may originate from induction, similar to phenomena observed in natural language. Reinforcement learning leveraging sequence-to-function models as experiment-derived rewards further strengthens ICL. We first validate this approach by generating enhancers that drive cell-type-specific gene expression in three human cell lines. Extending this approach in vivo, enhancers designed using human regulatory element data selectively label layer 5 extratelencephalic neurons in the mouse cortex with high specificity and stronger activity than existing enhancers. Our study provides evidence of emergent properties in genomic sequence models and introduces a promising approach for improving functional conditioning in generative biology.

bioengineering↗

IOP-independent treatment for neurodegeneration in glaucoma using optimized ROS-scavenging microparticles for sustained release of erythropoietin

Glaucoma is a slow-progressing neurodegenerative disease of the optic projection to the brain and a leading cause of blindness worldwide. Current treatments are targeted towards lowering intraocular pressure (IOP), the only known, modifiable risk factor; however, this strategy is ineffective in many patients. An early hallmark of glaucomatous neurodegeneration is increased reactive oxygen species (ROS), representing an alternative opportunity for intervention to halt or slow disease progression. In this work, we optimize a ROS-scavenging copolymer, poly(propylene sulfide-co-ethylene sulfide) (PPSES), for formulation of size-controlled, stabilized, antioxidant microparticles (MPs) for sustained release of the protein erythropoietin (EPO). EPO promotes biological antioxidant defense via activation of NRF2-mediated transcription of antioxidant genes. This MP system overcomes the short half-life of EPO and leverages the combined benefits of bioactive EPO with long-lasting, inherently antioxidant PPSES MPs. The lead EPO-MP formulation preserves neurons in both mouse and non-human primate models of glaucoma through suppression of oxidative stress and optic nerve degeneration. EPO-loaded PPSES MPs represent a translationally relevant therapy for long-term management of glaucoma independent of IOP.

bioengineering↗