Physical exercise is recommended to improve tibia strength, a common site for stress injuries, while identifying optimal training regimens remains a significant challenge. This study investigated tibial responses to varied exercise regimens using a subject-specific computational modeling approach. A subject-specific neuro-musculoskeletal model was combined with a finite element model to assess the effects of various exercises (jumping, landing, squatting, and walking) on tibial strain energy density (SED), as well as the impact of adjustable leg weights placed at different sites (shank versus thigh). The temporal relationship between joint/muscular loads and SED was then analyzed. A non-linear relationship between load weights and SED increase was observed, with 4% body weight load being the optimal load weight. Additionally, load carriage sites significantly influenced SED levels, emphasizing the necessity for individualized training regimens. The gastrocnemius, soleus, and peroneal muscles were identified as key contributors to tibial SED, with the highest correlations observed during various activities. This study underscored the utility of the subject-specific computational model in assessing the biomechanical impact of varied load weights, load sites, and exercise types. For a target bone site, it is beneficial to customize exercise programs based on individual biomechanical properties in order to maximize training benefits and meanwhile reduce risks of injuries.
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http://dx.doi.org/10.1007/s11517-025-03335-9 | DOI Listing |
J Agric Biol Environ Stat
February 2024
Department of Statistics, North Carolina State University, Raleigh, NC USA.
Unlabelled: This article focuses on the study of lactating sows, where the main interest is the influence of temperature, measured throughout the day, on the lower quantiles of the daily feed intake. We outline a model framework and estimation methodology for quantile regression in scenarios with longitudinal data and functional covariates. The quantile regression model uses a time-varying regression coefficient function to quantify the association between covariates and the quantile level of interest, and it includes subject-specific intercepts to incorporate within-subject dependence.
View Article and Find Full Text PDFPeerJ
March 2025
Centre for Orthopaedic & Trauma Research, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia.
Objective: Inertial measurement units (IMUs) offer a method for assessing gait beyond the confines of a laboratory. Signal noise and calibration errors pose significant obstacles to accurately estimating joint angles, particularly during dynamic activities such as running. Advancements in dynamic optimisation tools could enable a more comprehensive analysis with fewer sensors and/or low-quality data.
View Article and Find Full Text PDFJ Aerosol Sci
March 2025
Department of Medicine, University of California, San Diego, CA, USA.
Existing one-dimensional (1D) models of aerosol dosimetry often ignore mixing mechanisms of inhaled aerosols during their transport in the lung. This mixing or aerosol dispersion results from different physical mechanisms in different regions of the lung. It is a higher order effect, which cannot be directly captured in 1D modeling approaches, and thus is sometimes modeled as a diffusive process.
View Article and Find Full Text PDFMed Biol Eng Comput
March 2025
Academy for Engineering and Technology, Fudan University, Shanghai, China.
Physical exercise is recommended to improve tibia strength, a common site for stress injuries, while identifying optimal training regimens remains a significant challenge. This study investigated tibial responses to varied exercise regimens using a subject-specific computational modeling approach. A subject-specific neuro-musculoskeletal model was combined with a finite element model to assess the effects of various exercises (jumping, landing, squatting, and walking) on tibial strain energy density (SED), as well as the impact of adjustable leg weights placed at different sites (shank versus thigh).
View Article and Find Full Text PDFBrain Topogr
March 2025
School of Automation Science and Engineering, South China University of Technology, & Pazhou Laboratory, Guangzhou, China.
Electroencephalographic (EEG) oscillations occur across a wide range of spatial and spectral scales, and analysis of neural rhythmic variability have attracted recent attention as markers of development, intelligence, cognitive states and neural disorders. Nonnegative matrix factorization (NMF) has been successfully applied to multi-subject electroencephalography (EEG) spectral analysis. However, existing group NMF methods have not explicitly optimized the individual-level EEG components derived from group-level components.
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