Prediction the Biodynamic Response of the Seated Human Body using Artificial Intelligence Technique

The biodynamic response behaviors of seated human body subject to wholebodyvibration have been widely investigated. The biodynamic responsecharacteristics of seated human subjects have been extensively reported interms of apparent mass and driving-point mechanical impedance while seat-toheadvibration transmissibility has been widely used to characterize responsebehavior of the seated subjects exposed to vibration. These functions (apparentmass, driving-point mechanical impedance) describe “to-the-body” force–motionrelationship at the human–seat interface, while the transmissibility functiondescribes “through-the-body” vibration transmission properties. The current studyproposed a 4-DOF analytic biomechanical model of the human body in a sittingposture without backrest in vertical vibration direction to investigate thebiodynamic responses of different masses and stiffness. Following the analyticalapproach, numerical technique developed in the present paper to facilitate andrapid the analysis. The numerical analysis used here applies one of the artificialintelligence technique to simulate and predict the response behaviors of seatedhuman body for different masses and stiffness without the need to go through theanalytic solution every time. The Artificial Neural Network (ANN) technique isintroduced in the current study to predict the response behaviors for differentmasses and stiffness rather than those used in the analytic solution. The resultsof the numerical study showed that the ANN method with less effort was veryefficiently capable of simulating and predicting the response behaviors of seatedhuman body subject to whole-body vibration.