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

Authors: Pieter Oomen; Janneke Annegarn; John Rasmussen; Jessica Rausch; Karl Siebertz; Lex Verdijk; Maarten Drost; Kenneth Meijer

Addresses: Department of Human Movement Sciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands ' Department of Human Movement Sciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands ' Department of Mechanical and Manufacturing Engineering, The Faculty of Engineering and Science, Aalborg University, Fibigerstræde 16, 9220, Aalborg, Denmark ' Ford Forschungszentrum Aachen GmbH, Süsterfeldstraße 200, 52062 Aachen, Nordrhein-Westfalen, Germany ' Ford Forschungszentrum Aachen GmbH, Süsterfeldstraße 200, 52062 Aachen, Nordrhein-Westfalen, Germany ' Department of Human Movement Sciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands ' Department of Human Movement Sciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands ' Department of Human Movement Sciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands

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.

Keywords: muscle strength; personalised models; maximal voluntary contractions; MVC; isometric peak torque; knee extensions; multiple linear regression; MLR; calibration; leg press; model validation; rule-based strength scaling; musculoskeletal modelling; age; body mass; gender.

DOI: 10.1504/IJHFMS.2015.068121

International Journal of Human Factors Modelling and Simulation, 2015 Vol.5 No.1, pp.19 - 32

Received: 09 Jan 2014
Accepted: 24 Aug 2014
Published online: 18 Mar 2015 *

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