Biodynamic modelling of seated human body under whole body vibration exposure using ANN

Vehicle developers and design engineers require understanding of human response to vibration for optimising the seat in order to meet the objective of passenger ride comfort. This paper attempts to develop an artificial neural networks (ANN) based model to measure biodynamic response seat to head transmissibility (STHT), incorporating factors like vibration frequency, vibration magnitude and posture for seated subjects exposed to random whole body vibration (WBV) in three different directions (vertical, fore-aft, lateral). After training the model is able to predict STHT with high accuracy when compared with the experimental values. Cross-axis coupling, i.e., excitation in one axis producing a response in the other axis, is also validated through ANN modelling in this paper.