This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24–74 years underwent the same set of measurements on two separate occasions. Retroreflective markers were placed on anatomical regions, including C7, T1, T4, T5, T8, T9, T12 and L1 spinous processes, pelvis, upper and lower limbs, and head. We created full-body musculoskeletal models with detailed thoracolumbar spines, and scaled these to create subject-specific models for each individual and each session. Models were scaled from distances between markers, and spine curvature was adjusted according to marker-estimated measurements. Using these models, we estimated vertebral compressive loading for five different standardized postures: neutral standing, 45˚ trunk flexion, 15˚ trunk extension, 20˚ lateral bend to the right, and 45˚ axial rotation to the right. Intraclass correlation coefficients (ICCs) and standard error of measurement were calculated as measures of between-session reliability and measurement error, respectively. Spine curvature measures showed excellent reliability (ICC = 0.79–0.91) and body scaling segments showed fair to excellent reliability (ICC = 0.46–0.95). We found that musculoskeletal models showed mostly excellent between-session reliability to estimate spine loading, with 91% of ICC values > 0.75 for all activities. This information is a necessary precursor for using motion capture data to estimate spine loading from subject-specific musculoskeletal models, and suggests that marker data will deliver reproducible subject-specific models and estimates of spine loading.

本研究评估了使用光电运动捕捉数据创建特定主题肌肉骨骼模型并使用它们来估计脊柱负荷的会话间可靠性。19 名 24-74 岁的健康参与者在两个不同的场合接受了相同的测量。逆反射标记放置在解剖区域，包括 C7、T1、T4、T5、T8、T9、T12 和 L1 棘突、骨盆、上下肢和头部。我们创建了带有详细胸腰椎的全身肌肉骨骼模型，并对其进行缩放以创建针对每个人和每个会话的特定主题模型。模型根据标记之间的距离进行缩放，并根据标记估计的测量值调整脊柱曲率。使用这些模型，我们估计了五种不同标准姿势的椎体压缩负荷：中立站立、45° 躯干屈曲、15° 躯干伸展、20° 向右侧弯和 45° 向右轴向旋转。类内相关系数 (ICC) 和测量标准误差分别计算为会话间可靠性和测量误差的度量。脊柱曲率测量显示出极好的可靠性（ICC = 0.79-0.91），身体缩放节段显示出相当到极好的可靠性（ICC = 0.46-0.95）。我们发现，肌肉骨骼模型在估计脊柱负荷方面大多表现出出色的会话间可靠性，所有活动的 91% ICC 值 > 0.75。该信息是使用运动捕捉数据从特定主题的肌肉骨骼模型估计脊柱负荷的必要前提，