Active human body models (AHBM) are essential engineering tools to provide further biomechanical knowledge. For example, to predict injury risks and kinematic behaviour in a wide range of possible scenarios such as low-g and multiaxial loading scenarios where muscle activity has shown to affect head and neck kinematics. The validation of the AHBM, in particular, the tuning and selection of an appropriate control strategy is a significant challenge. There are two main contributions of this paper. First, a Driver-in-the-Loop (DiL) simulator, used for reproducible and safe data acquisitions of human behaviour, is presented. Second, subject-specific control parameter identification to replicate the unique behaviour of each subject by using a modular calibration approach. The DiL setup is modelled in Madymo using the active human model (AHM) as a representation of the human. The Matlab/Simulink interface of Madymo is extended to implement in Matlab two new individual muscle control strategies for the head-neck region of the AHM; (i) PD controllers based on the muscle length – motivated by the equilibrium point control theory and (ii) the in-vivo stretch reflex – based on the strain measuring capabilities of the muscle spindles. Any optimization procedure available in Matlab, i.e. a particle swarm optimizer, can be used to calibrate the control parameters to achieve a good agreement between DiL measurement data and the simulation output. Finally, this modular workflow is used to identify two subject-specific sets of control parameters. These subject-specific parameters play an important role in a robust representation of human occupants.
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