Sensitivity of subject-specific upper body musculoskeletal model predictions to mass scaling methods.
Comput Biol Med
; 165: 107376, 2023 10.
Article
en En
| MEDLINE
| ID: mdl-37611422
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.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Columna Vertebral
/
Sobrepeso
Tipo de estudio:
Diagnostic_studies
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Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
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Male
Idioma:
En
Revista:
Comput Biol Med
Año:
2023
Tipo del documento:
Article
País de afiliación:
Canadá
Pais de publicación:
Estados Unidos