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Personalized Muscle Strength Improves Accuracy of Military Load Carriage Simulations.

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Title: Personalized Muscle Strength Improves Accuracy of Military Load Carriage Simulations.
Authors: Corman, Anna C.1 ancorman@mines.edu, Sturdy, Jordan T.1 sturdy@mines.edu, Rizeq, Hedaya N.2,3 hedaya.n.rizeq.ctr@health.mil, Daquino, Carlie J.2,3 carlie.j.daquino.ctr@health.mil, Whittier, Tyler T.4 tyler.whittier@montana.edu, Silder, Amy3 amy.b.silder.civ@health.mil, Sessoms, Pinata H.3 pinata.h.sessoms.civ@health.mil, Silverman, Anne K.1,5 asilverm@mines.edu
Source: Journal of Biomechanical Engineering. Apr2026, Vol. 148 Issue 4, p1-11. 11p.
Subjects: Muscle strength, Computer simulation, Prevention of injury, Biomechanics
Abstract: Military overuse injuries are often associated with load carriage, and poor physical fitness is a risk factor. However, muscle strength is modifiable, which is important for injury prevention. Active-duty military populations are generally stronger than the civilian population; therefore, musculoskeletal models with military-specific muscle strengths are needed, especially if they are used for injury prediction. The purpose was to evaluate the effect of muscle strength personalization on muscle excitation prediction accuracy from movement simulations of musculoskeletal models. Maximum voluntary isometric contractions (MVICs) of lumbar, hip, knee, and ankle muscles were measured with an instrumented dynamometer for 16 active-duty participants. These measurements were used to personalize muscle maximum isometric force from a generic musculoskeletal model to create strength-scaled models. Participants walked under two conditions: (1) no-pack (body armor and helmet) and (2) pack with 46 kg total load (body armor, helmet, and posteriorly loaded backpack). Full-body kinematics, ground reaction forces (GRFs), and right-side electromyography (EMG) of 11 lower-limb and torso muscles were collected. Muscle-driven simulations were produced using both generic and strength-scaled models for each condition. Simulation accuracy was determined by comparing measured electromyography signals to simulated muscle excitations using a root-mean-square difference (RMSD). Personalized muscle strength scaling improved overall muscle excitation predictions in walking simulations of military service members carrying heavy backpacks by 19% (p < .001). Improved model accuracy enables better predictions of internal joint mechanics, which are important for understanding injury risk and evaluating injury prevention strategies. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Military overuse injuries are often associated with load carriage, and poor physical fitness is a risk factor. However, muscle strength is modifiable, which is important for injury prevention. Active-duty military populations are generally stronger than the civilian population; therefore, musculoskeletal models with military-specific muscle strengths are needed, especially if they are used for injury prediction. The purpose was to evaluate the effect of muscle strength personalization on muscle excitation prediction accuracy from movement simulations of musculoskeletal models. Maximum voluntary isometric contractions (MVICs) of lumbar, hip, knee, and ankle muscles were measured with an instrumented dynamometer for 16 active-duty participants. These measurements were used to personalize muscle maximum isometric force from a generic musculoskeletal model to create strength-scaled models. Participants walked under two conditions: (1) no-pack (body armor and helmet) and (2) pack with 46 kg total load (body armor, helmet, and posteriorly loaded backpack). Full-body kinematics, ground reaction forces (GRFs), and right-side electromyography (EMG) of 11 lower-limb and torso muscles were collected. Muscle-driven simulations were produced using both generic and strength-scaled models for each condition. Simulation accuracy was determined by comparing measured electromyography signals to simulated muscle excitations using a root-mean-square difference (RMSD). Personalized muscle strength scaling improved overall muscle excitation predictions in walking simulations of military service members carrying heavy backpacks by 19% (p < .001). Improved model accuracy enables better predictions of internal joint mechanics, which are important for understanding injury risk and evaluating injury prevention strategies. [ABSTRACT FROM AUTHOR]
ISSN:01480731
DOI:10.1115/1.4071130