Development and validation of a rule-based strength scaling method for musculoskeletal modelling

Abstract

Rule–based strength scaling is an easy, cheap and relatively accurate technique to personalise musculoskeletal models. This paper presents a new strength scaling approach for musculoskeletal models and validates it by maximal voluntary contractions. A heterogeneous group of 63 healthy subjects performed maximal isometric knee extensions. A multiple linear regression analysis resulted in a best–fit rule–based strength scaling equation, with age, mass, height, gender, segment masses and segment lengths as predictors. A second strength scaling equation was obtained through multiple linear regression using backwards elimination, resulting in an equation consisting of only the significant predictors: age, body mass and gender. For validation purposes, 20 newly included healthy subjects performed a maximal isometric leg–press. The newly developed strength scaling technique taking all predictors into account resulted in the most accurate predictions of muscle activities compared to alternative strength scaling methods. These techniques personalise musculoskeletal models to a larger extend. However, some applications that require more detailed personalised models, imaging might be necessary to obtain more specific individual muscle characteristics.