Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2020.08.23.262048

Computational Modeling: Human Dynamic Model

Liu, L.·Cooper, J.·Ballard, D.
View original source ↗Export metadata ↓

Abstract

Improvements in quantitative measurements of human physical activity are proving extraordinarily useful for studying the underlying musculoskeletal system. Dynamic models of human movement support clinical efforts to analyze, rehabilitate injuries. They are also used in biomechanics to understand and diagnose motor pathologies, find new motor strategies that decrease the risk of injury, and predict potential problems from a particular procedure. In addition, they provide useful constraints for underlying neural circuits. This paper describes a physics-based movement analysis method for analyzing and simulating bipedal humanoid movements. A 48 degree of freedom dynamic model of humans has been developed to report humanoid movements energetic components. It has sufficient speed and accuracy to analyze and synthesize real-time interactive applications, such as psychophysics experiments using virtual reality or human-in-the-loop teleoperation of a simulated robotic system. The dynamic model is fast and robust while still providing results sufficiently accurate to be used to believably animate a humanoid character or estimate internal joint forces used during a movement for creating effort-contingent experimental stimuli. A virtual reality environment developed as part of this research supports controlled experiments for systematically recording human behaviors.

Source connections

Explore related subjects

physiologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Liu, L., Cooper, J., Ballard, D.. 2020-08-24. Computational Modeling: Human Dynamic Model. https://doi.org/10.1101/2020.08.23.262048

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

KEEP EXPLORING

Related preprints

bioRxiv2026

IBD-Derived Colonic Fibroblasts Exhibit an Osteopontin-Enriched Secretome, and Osteopontin Restrains Human Colonic Organoid Maturation

Background: Intestinal fibroblasts are extensively remodeled in inflammatory bowel disease (IBD), yet the soluble stromal signals that directly influence epithelial maturation remain incompletely understood. We examined whether fibroblasts derived from inflamed IBD colon display an osteopontin (OPN; SPP1)-enriched secretory phenotype and whether extracellular OPN directly modifies non-neoplastic human colonic epithelium. Methods: Conditioned media from 5 noninflamed-associated fibroblast (NAF) and 4 inflammatory-associated fibroblast (IAF) cultures were analyzed in the validated multi-donor cytokine-array matrix, with orthogonal SPP1 RT-qPCR validation in a complementary fibroblast cohort. Recombinant OPN was then tested in human colonic organoids from 3 donors using donor-resolved molecular and functional analyses under standard, fibroblast-conditioned, and WNT-modified culture conditions. Donor identity defined biological replication. Results: OPN showed the strongest positive rank-based separation between IAF and NAF cultures: all 4 IAF values were higher than all 5 NAF values (Cliff's delta=1.00; exact Mann-Whitney P=0.0159; median ratio=3.64; Benjamini-Hochberg q=.19). Fibroblast RT-qPCR showed approximately 10-fold higher mean SPP1 expression in IAF than NAF cultures (P<.05). In organoids, OPN consistently reduced KRT20, FABP1, CA2, and MUC2 from Day 5 to Day 9. SOX9, HES1, and NOTCH1 increased at Day 9, whereas LGR5 and ALDH provided no evidence of canonical stem-cell expansion. Organoid-area and EdU responses were modest and donor dependent. Conclusions: IBD-derived colonic fibroblasts can display an OPN-enriched secretory phenotype. In human colonic organoids, OPN is sufficient to impair epithelial maturation, whereas its effects on growth and proliferation are variable and depend on the surrounding niche.

physiology↗
bioRxiv2026

A multiscale analysis of liver lobule fibrosis and its impact on drug propagation and metabolism - a DLA approach

Employing DLA methods, this paper explores the self-assembly of collagen fibers and resulting fibrosis at three scales up to the scale of regular lobule models. This allows a mechanistic exploration of the effects of collagen on drug transport (flow and diffusion) and metabolism. In addition, this method permits an analysis of fiber growth characteristics. First, variations of the DLA method of Parkinson et al (1994) will be used to generate multiple explicit collagen microfibril self-assembly using DLA particles in one dimension using cubic grid blocks of (4 mm)3 in a 240 x 20 x 20 grid model. The second stage will be to assess the consequences of various densities of these fibers in three dimensions on flow reductions at a higher scale. Here we utilize DLA methods in cubic grid blocks of (80 nm)3 to mimic 3D collagen self-assembly of fibrils. We then apply a pressure gradient or specified flow rates across a spatially gridded version of these models to quantify flow effects. This region represents a local zone of liver tissue affected by fibrosis. Analytic models of fibrotic effects on flow are employed for comparison. A third stage explores the implications of fibrosis in a liver lobule model using multiple grid blocks of size 3200 mm to represent the lobule tissue. Here, a continuum model of fiber density is employed, based on the previous two scales. The model also includes the effects of additional grid blocks representing sinusoidal flow paths found in the lobule. We contrast and quantify drug propagation and metabolism of molecular dissolved versus nanoparticle delivery vehicles in fibrotic media, achieved by upscaling explicit collagen distributions to appropriate average values.

physiology↗
bioRxiv2026

Pulmonary pressure load shapes right ventricular molecular remodelling in dilated cardiomyopathy

Right ventricular (RV) adaptation to pulmonary hypertension determines outcome in dilated cardiomyopathy (DCM), but the molecular mechanisms of the transition to decompensation remain unclear. We analysed RV tissue from explanted hearts of patients with end-stage DCM using single-nucleus RNA sequencing (n=21), mass spectrometry and Olink Reveal proteomics (both n=44), and integrated these molecular profiles with echocardiographic and right-heart catheterisation measures to identify molecular correlates of RV dysfunction. Mean pulmonary arterial pressure was the dominant correlate of RV transcriptional remodelling, particularly in cardiomyocytes, where higher pressure was associated with contractile remodelling, autophagy, vesicle trafficking and glucose metabolism. In contrast, RV decompensation was characterised by immune activation and reduced oxidative phosphorylation exclusively at the proteomic level. Integrative multi-omics factor analysis (MOFA) further identified fibrosis as the dominant molecular program shared across transcriptomic and proteomic layers. Together, these findings indicate molecular adaptation to pressure load and tissue fibrosis during progression towards RV failure.

physiology↗