An Anatomical Atlas-Based Scaling Study for Quantifying Muscle and Hip Joint Contact Forces in Above and Through-Knee Amputees Using Validated Musculoskeletal Modelling

• Published in: IEEE transactions on biomedical engineering 2021-11, Vol.68 (11), p.3447-3456
• Main Authors: Toderita, Diana, Henson, David P., Klemt, Christian, Ding, Ziyun, Bull, Anthony M. J.
• Format: Article
• Language: English
• Subjects: Amputation; amputee biomechanics; anatomical atlas; Anthropometry; Biomedical materials; Body mass; Body mass index; Body size; Contact force; Electromyography; Errors; Force plates; Gait; Hip joint; Knee; linear scaling; lower limb musculoskeletal modelling; Magnetic resonance imaging; Model accuracy; Motion capture; Muscles; Pelvis; Predictions; Predictive models; Prosthetics; Regression analysis; Regression models; Scaling; Similarity; Three-dimensional displays
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2021.3075041

Objective: 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. Methods: 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. Results: 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. Conclusion: 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. Significance: 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.