Development of a 7-DOF Biodynamic Model for a Seated Human and a Hybrid Optimization Method for Estimating Human-Seat Interaction Parameters

Abstract

Existing biodynamic models adopt apparent mass and seat-to-head transmissibility to predict the response of seated humans to whole-body vibration, limiting their ability to capture the actual response of distinct body segments in different excitation conditions. This study systematically develops a 7-DOF seated human model, a vibration experiment, and a novel hybrid optimization to estimate unknown mechanical parameters and predict the response of different human body segments to vertical vibrations. Experimental results showed that the upper trunk and head were most susceptible to transmitted vibrations. Combining the 7-DOF model and HOM resulted in accelerated optimization, improved numerical stability, and significant minimization of the objective function value compared to conventional algorithms. Notably, the estimated parameters, particularly stiffness, remained consistent regardless of increasing excitation magnitude or change in the body segment data used. Additionally, the model captured the non-linearity in human biodynamics through stiffness softening. These findings are applicable in seating systems optimization for comfort and safety.