IEEE Trans Biomed Eng. 2021 Nov;68(11):3447-3456. doi: 10.1109/TBME.2021.3075041. Epub 2021 Oct 19.
Customisation of musculoskeletal modelling using magnetic resonance imaging (MRI) significantly improves the model accuracy, but the process is time consuming and computationally intensive. This study hypothesizes that linear scaling to a lower limb amputee model with anthropometric similarity can accurately predict muscle and joint contact forces.
An MRI-based anatomical atlas, comprising 18 trans-femoral and through-knee traumatic lower limb amputee models, is developed. Gait data, using a 10-camera motion capture system with two force plates, and surface electromyography (EMG) data were collected. Muscle and hip joint contact forces were quantified using musculoskeletal modelling. The predicted muscle activations from the subject-specific models were validated using EMG recordings. Anthropometry based multiple linear regression models, which minimize errors in force predictions, are presented.
All predictions showed excellent (error interval c = 0-0.15), very good (c = 0.15-0.30) or good (c = 0.30-0.45) similarity to the EMG data, demonstrating accurate computation of muscle activations. The primary predictors of discrepancies in force predictions were differences in pelvis width (p < 0.001), body mass index (BMI, p < 0.001) and stump length to pelvis width ratio (p < 0.001) between the respective individual and underlying dataset.
Linear scaling to a model with the most similar pelvis width, BMI and stump length to pelvis width ratio results in modelling outcomes with minimal errors.
This study provides robust tools to perform accurate analyses of musculoskeletal mechanics for high-functioning lower limb military amputees, thus facilitating the further understanding and improvement of the amputee's function. The atlas is available in an open source repository.
使用磁共振成像(MRI)对肌肉骨骼模型进行定制化处理可以显著提高模型的准确性,但该过程耗时且计算密集。本研究假设,通过与人体测量学相似的线性缩放至下肢截肢模型,可以准确预测肌肉和关节接触力。
开发了一个基于 MRI 的解剖图谱,其中包含 18 个经股骨和经膝部创伤性下肢截肢模型。使用带有两个力板的 10 个摄像机运动捕捉系统和表面肌电图(EMG)数据收集步态数据。使用肌肉骨骼建模来量化肌肉和髋关节接触力。使用 EMG 记录验证了从个体特定模型预测的肌肉激活情况。提出了基于人体测量学的多元线性回归模型,该模型可最大限度地减少力预测误差。
所有预测结果均与 EMG 数据具有极好的(误差间隔 c = 0-0.15)、非常好的(c = 0.15-0.30)或好的(c = 0.30-0.45)相似性,表明肌肉激活的计算准确。力预测差异的主要预测因素是个体与基础数据集之间骨盆宽度(p < 0.001)、体重指数(BMI,p < 0.001)和残肢长度与骨盆宽度比(p < 0.001)的差异。
线性缩放至具有最相似骨盆宽度、BMI 和残肢长度与骨盆宽度比的模型可使建模结果误差最小。
本研究为高性能下肢军事截肢者的肌肉骨骼力学进行准确分析提供了可靠的工具,从而有助于进一步理解和改善截肢者的功能。该图谱可在开源存储库中获得。