RESUMEN

Accurate predictions of spinal loads in subject-specific musculoskeletal models require precise body segment parameters, including segment mass and center of mass (CoM) locations. Existing upper body models often assume a constant percentage of total body mass to calculate segmental masses, disregarding inter-individual variability and limiting their predictive capacity. This study evaluated the sensitivity of subject-specific upper body musculoskeletal model predictions to body mass scaling methods. The upper body segmental masses and corresponding CoM of six male subjects with varying body mass indices were computed using two mass scaling methods: the constant-percentage-based (CPB) scaling method, commonly used in AnyBody software; and our recently developed body-shape-based (BSB) method. Subsequently, these values were used by a validated musculoskeletal model to predict the muscle and disc forces in upright and flexed postures. The discrepancies between the results of the two scaling methods were compared across subjects and postures. Maximum deviations in thorax masses reached up to 7.5% of total body weight (TBW) in overweight subjects, while maximum CoM location differences of up to 35 mm were observed in normal weight subjects. The root mean squared errors (RMSE) of the CPB results, calculated with the BSB results as baseline, showed that the muscle and shear forces of the two scaling methods were quite similar (<4.5% of TBW). Though, there were small to moderate differences in compressive forces (6.5-16.0% of TBW). Thus, the compressive forces predicted with CPB method should be used with caution, particularly for overweight and obese subjects.

Asunto(s)

Sobrepeso , Columna Vertebral , Humanos , Masculino , Soporte de Peso/fisiología , Fenómenos Biomecánicos , Postura/fisiología , Músculo Esquelético/fisiología

RESUMEN

One of the surgical treatments for pelvic sarcoma is the restoration of hip function with a custom pelvic prosthesis after cancerous tumor removal. The orthopedic oncologist and orthopedic implant company must make numerous often subjective decisions regarding the design of the pelvic surgery and custom pelvic prosthesis. Using personalized musculoskeletal computer models to predict post-surgery walking function and custom pelvic prosthesis loading is an emerging method for making surgical and custom prosthesis design decisions in a more objective manner. Such predictions would necessitate the estimation of forces generated by muscles spanning the lower trunk and all joints of the lower extremities. However, estimating trunk and leg muscle forces simultaneously during walking based on electromyography (EMG) data remains challenging due to the limited number of EMG channels typically used for measurement of leg muscle activity. This study developed a computational method for estimating unmeasured trunk muscle activations during walking using lower extremity muscle synergies. To facilitate the calibration of an EMG-driven model and the estimation of leg muscle activations, EMG data were collected from each leg. Using non-negative matrix factorization, muscle synergies were extracted from activations of leg muscles. On the basis of previous studies, it was hypothesized that the time-varying synergy activations were shared between the trunk and leg muscles. The synergy weights required to reconstruct the trunk muscle activations were determined through optimization. The accuracy of the synergy-based method was dependent on the number of synergies and optimization formulation. With seven synergies and an increased level of activation minimization, the estimated activations of the erector spinae were strongly correlated with their measured activity. This study created a custom full-body model by combining two existing musculoskeletal models. The model was further modified and heavily personalized to represent various aspects of the pelvic sarcoma patient, all of which contributed to the estimation of trunk muscle activations. This proposed method can facilitate the prediction of post-surgery walking function and pelvic prosthesis loading, as well as provide objective evaluations for surgical and prosthesis design decisions.