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This study investigates the effects of anthropometric attributes, biologicalsex, and posture on translational body kinematic responses in translationalvibrations. In total, 35 participants were recruited. Perturbations wereapplied on a standard car seat using a motion-based platform with 0.1 to 12.0Hz random noise signals, with 0.3 m/s2 rms acceleration, for 60 seconds.Multiple linear regression models (three basic models and one advanced model,including interactions between predictors) were created to determine the mostinfluential predictors of peak translational gains in the frequency domain perbody segment (pelvis, trunk, and head). The models introduced experimentallymanipulated factors (motion direction, posture, measured anthropometricattributes, and biological sex) as predictors. Effects of included predictorson the model fit were estimated. Basic linear regression models could explainover 70% of peak body segments' kinematic body response (where the R2 adjustedwas 0.728). The inclusion of additional predictors (posture, body height andweight, and biological sex) did enhance the model fit, but not significantly(R2 adjusted was 0.730). The multiple stepwise linear regression, includinginteractions between predictors, accounted for the data well with an adjustedR2 of 0.907. The present study shows that perturbation direction and bodysegment kinematics are crucial factors influencing peak translational gains.Besides the body segments' response, perturbation direction was the strongestpredictor. Adopted postures and biological sex do not significantly affectkinematic responses.

Explaining human body responses in random vibration: Effect of motion direction, sitting posture, and anthropometry