Christen Cogan
Research Mentor: Sujata Khandare
Mentor Department: University of Michigan Transportation Research Institute, Engineering
Author(s): Christen Cogan , Sujata Khandare
Session: Session 1 (9:00 AM – 9:50 AM)
Presentation Type: Poster 138
Abstract
Female athletes, including soccer players, experience higher rates of neck injuries, suggesting that anatomical differences may influence cervical spine biomechanics. Human movement and force production are strongly influenced by skeletal geometry; however, many current musculoskeletal and digital human models rely on generic or uniformly scaled anatomy. These simplified representations may fail to capture subject-specific or sex-specific anatomical differences that influence muscle mechanics, joint loading, and overall movement patterns. The objective of this study is to quantify how variations in cervical vertebral geometry affect predicted muscle moment arms, activation patterns, and joint loading within the cervical spine (C-spine). The cervical spine is a particularly important system to study because of its complex curvature, high mobility, and sensitivity to anatomical variation between individuals, including known differences between male and female vertebral anatomy. To investigate these effects, subject-specific musculoskeletal models of the cervical spine are developed representing both male and female vertebral geometries. These models are integrated into a digital human modeling framework and used to simulate representative neck motions, including neutral posture, flexion, and extension under dynamic loading conditions. Model outputs include predicted muscle activation patterns, muscle moment arms, joint kinematics, and force transmission across cervical vertebrae. By isolating vertebral geometry as a primary variable, this work evaluates how anatomical structure alone influences neuromuscular mechanics and mechanical advantage within the cervical spine. The results provide insight into how geometric differences can produce distinct biomechanical responses even under similar loading conditions. Ultimately, this work supports the development of subject-specific and sex-informed musculoskeletal models that improve digital human modeling, injury biomechanics research, and the accuracy of human digital twins.
