Improving Human Muscle Modeling
Using Numerical Optimization
Author(s)
M. El-Sayed, J. Brelin-Fornari & P. Shah
Abstract
For an accurate simulation of human body behavior during crashes,
computational models of muscle activation and deactivation in flexion and
extension need to be developed. Several attempts have been made since the late
seventies to validate various three-dimensional, lumped parameter models of the
human head and neck. The behavior of these models was compared to data
gathered on live volunteers at the Naval Bio-dynamics Laboratory. While these
experiments involved live, active muscles, the models represented muscles only
in the passive state.
A recently developed model introduced muscle activation and deactivation for
the Naval Bio-dynamics Laboratory data. The model utilizes several muscle
pairs. Activation and deactivation timing is different for each of the muscle pairs
and is based on the change in length of each muscle. Therefore, both flexors and
extensors are activated during the events. To further develop the muscle
activation and deactivation model, for optimum parameters in correlation with
the Naval Bio-dynamics Laboratory data, numerical optimization techniques
were utilized. In this paper, the numerical optimization process developed for
dealing with such models is discussed along with some correlation results.
1 Introduction
Several three-dimensional, lumped parameter numerical models of the human
head and neck developed [1-3], are compared to data gathered on live volunteers
at the Naval Biodynamics Laboratory (NBDL) in the late 1970s [4-7]. While
these experiments involved live, active muscles, the models represented muscles
only in the passive state.
Recently, a model by Brelin-Fornari [8], introduced muscle activation and
deactivation for the NBDL data. Activation and deactivation timing was
Keywords
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