Biology subjects

Troy, K. L.

Publications and source records attributed to Troy, K. L..

4 recordsLinked to original sources

bioRxiv2025

Peak Anteroposterior Heel Slip Acceleration Predicts Lateral Trunk Flexion During Unexpected Slip Perturbations

Slip-induced falls are a major contributor to hip fractures and injury, particularly during sideways falls where lateral trunk flexion drives impact to the hip. While past studies have focused on sagittal-plane slip mechanics, the mechanisms of inducing frontal-plane trunk excursion remain poorly understood. This study investigated which slip foot kinematic variables predict lateral trunk flexion during unexpected slips. Twenty-six healthy young adults experienced an unexpected slip while walking in a laboratory setting. Peak anteroposterior (AP) heel slip distance, velocity, and acceleration, as well as mediolateral (ML) slip distance, velocity, and acceleration, were measured using three-dimensional motion capture. A stepwise multiple linear regression identified peak AP heel slip acceleration as the sole significant predictor of lateral trunk flexion (p = .026, R2 = 0.19). One-way repeated measures ANOVA and one-tailed paired t-tests further revealed that peak heel acceleration occurred significantly earlier than both peak heel velocity (p = .012) and the onset of lateral trunk flexion (p < .001), supporting its role as an early destabilizing mechanism. In contrast, neither velocity nor slip distance predicted lateral trunk flexion magnitude. These findings suggest that peak AP heel acceleration is associated with inducing lateral trunk flexion movements that likely precede lateral falls. Reducing heel acceleration through slip-resistant flooring or footwear, or enhancing compensatory strategies such as reactive arm movements, may reduce the likelihood of losing sideways balance. This work highlights the need for balance training interventions that emphasize rapid responses to early-phase slip dynamics. HighlightsO_LIEvery 1000 cm/s2 increase in AP heel acceleration leads to 6 degrees more lateral trunk flexion C_LIO_LIHeel acceleration occurs significantly earlier than heel velocity or the onset of lateral trunk flexion C_LIO_LIFindings highlight the importance in reducing forward heel acceleration to reduce sideways loss of balance C_LI

bioengineering↗

bioRxiv2024

How many segments are enough to biomechanically model the feet? A comparison of inverse kinematics and dynamics in multisegmented foot models

Multisegmented foot models (MSFMs) capture kinematic and kinetic data of specific regions of the foot instead of representing the foot as a single, rigid segment. Models differ by the number of segments and segment definitions, so there is no consensus for best practice. It is unknown whether MSFMs yield the same joint kinematic and kinetic data and what level of detail is necessary to accurately measure such values. We compared the angle, moment, and power measurements at the tibiotalar, midtarsal, and metatarsophalangeal joints of four MSFMs using motion capture data of young adult runners during stance phase of barefoot walking and jogging. Of these models, three were validated: Oxford Foot Model, Milwaukee Foot Model, and Ghent Foot Model. One model was developed based upon literature review of existing models: the "Vogel" model. We performed statistical parametric mapping comparing joint measurements from each model to the corresponding results from the Oxford Model, the most heavily studied MSFM. We found that the Oxford Foot Model, Milwaukee Foot Model, Vogel Foot Model, and Ghent Foot Model do not provide the same results. The changes in model segment definitions impact the degrees of freedom in ways that alter the measured kinematic function of the foot, which in turn impacts the kinetic results. We also found that dynamic function of the midfoot/arch may be better captured by MSFMs with a separate midfoot segment. The results of this study capture the variability in performance of MSFMs and indicate a need to standardize the design of MSFMs.

bioengineering↗

bioRxiv2024

How to Use Gravity to Accelerate Bone Adaptation: A Computational/Experimental Investigation of Exercises for Bone

Impact exercises are known to increase bone mineral density (BMD) and in turn, bone strength and resistance to fracture. The biochemical pathways driving changes in BMD take months to complete, complicating our ability to understand how specific exercises influence the remodeling stimulus received by the bone. The purpose of this study was to compare several measures that have been theoretically linked to bone remodeling stimulus, including accelerations measured by Inertial Measurement Units (IMUs) at the middle of the tibia, ground reaction forces measured by force plate, joint contact forces estimated by musculoskeletal modeling, and tibia strains estimated by finite element modeling informed by high-resolution CT imaging. Twenty healthy adults (10 male: 22.1 +/- 2.2 years; 10 female: 21.3 +/- 1.3 years) participated in a biomechanical investigation of how drop height and landing style (bilateral vs. unilateral) affect the various bone remodeling stimuli. The results showed that while drop height consistently had significant direct relationships with stimulus magnitude, there was little benefit to drop heights greater than 0.4 m. In contrast, switching from a bilateral to a unilateral landing had a large positive effect. The stimuli calculated based on IMU data showed opposite trends compared to force plate and musculoskeletal modeling-based calculations, highlighting the need for caution in how IMUs are placed, and the resulting data interpreted, in the context of bone loading. A post-hoc analysis showed that a linear regression with predictor variables of kinematics, jump height, landing type (unilateral vs. bilateral) and the Ground Reaction Force FFT Integral could explain 79% of the variance in the bone remodeling stimulus that was predicted using much more sophisticated (and labor intensive) modeling. We conclude that higher level biomechanical modeling may not be necessary to understand the magnitude of a bone remodeling stimulus of an exercise.

bioengineering↗

bioRxiv2017

Intrinsic and Modifiable Contributors to Distal Radius Microstructure, Macrostructure and Strength in Premenopausal Women

While weight-bearing and resistive exercise modestly increases aBMD, the precise relationship between physical activity and bone microstructure, and strain in humans is not known. Previously, we established a voluntary upper-extremity loading model that assigns a persons target force based on their subject-specific, continuum FE-estimated radius bone strain. Here, our purpose was to quantify the inter-individual variability in radius microstructure and FE-estimated strain explained by site-specific mechanical loading history, and to determine whether variability in strain is captured by aBMD, a clinically relevant measure of bone density and fracture risk. Seventy-two women aged 21-40 were included in this cross-sectional analysis. High resolution peripheral quantitative computed tomography (HRpQCT) was used to measure macro- and micro-structure in the distal radius. Mean energy equivalent strain in the distal radius was calculated from continuum finite element models generated from clinical resolution CT images of the forearm. Areal BMD was used in a nonlinear regression model to predict FE strain. Hierarchical linear regression models were used to assess the predictive capability of intrinsic (age, height) and modifiable (body mass, grip strength, physical activity) predictors. Fifty-one percent of the variability in FE bone strain was explained by its relationship with aBMD, with higher density predicting lower strains. Age and height explained up to 31.6% of the variance in microstructural parameters. Body mass explained 9.1% and 10.0% of the variance in aBMD and bone strain, respectively, with higher body mass indicative of greater density. Overall, results suggest that meaningful differences in bone structure and strain can be predicted by subject characteristics.\n\nHighlightsO_LIAreal bone mineral density (aBMD) explains 51% of the variability in bone strain.\nC_LIO_LIAdult bone loading predicts greater cortical porosity and trabecular density.\nC_LIO_LIGreater body mass predicts greater aBMD and lower bone strain.\nC_LI

physiology↗