Abstract
Background Joint moments modeled from a musculoskeletal tool differ from those recorded by a dynamometer. In order to solve the problem, numerical methods to minimize the variance of the joint moments have been adopted [1]. The existing objective function (EOF) in the optimization, however, might not be sufficient to estimate reasonable muscle forces due to a possibility of predicting well-matched joint moments with the combination of unrealistic individual muscle forces [2]. In this study, we introduce a new objective function (NOF) for predicting reasonable muscle forces and to compare its performance with EOF.
Highlights
Joint moments modeled from a musculoskeletal tool differ from those recorded by a dynamometer
Dynamometer tasks were performed with Biodex System 3 Pro (Biodex Medical Systems, New York, USA) to measure elbow joint moments
To evaluate the effects of new objective function (NOF) compared to existing objective function (EOF) briefly, we focused on the changes in biceps brachii long head (BIClong) muscle force and compared the relative root-mean-square error
Summary
Joint moments modeled from a musculoskeletal tool differ from those recorded by a dynamometer. Methods NOF was designed to strengthen the linear relationship between: (1) the recorded and modeled joint moments, and (2) the muscle activations and the muscle forces. One male (age: 18 years; mass: 78 kg; height: 178 cm) participated in the study with the informed consent prior to commencing the experimental trials.
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