A method for posture prediction of the upper trunk of video terminal operators

This paper presents a method for posture prediction of the upper trunk of video terminal (VDT) operators, which is then verified by means of some test cases. The prediction of the upper trunk posture is, in fact, a very difficult task to carry out due mainly to the complexity of the anatomy of the spine and the surrounding muscles. The method being proposed in this paper is based on the integration of the knowledge which is obtained experimentally through the posture analysis of real cases into a configured human multi-body kinematic model which has been implemented in a commercial CAD system. A trained artificial neural network retains the knowledge concerning the VDT operator’s postures detected in different working positions. The posture simulations obtained with the proposed method are subsequently compared with the real ones determined by a 3D scanner. The results obtained confirm the effectiveness of such a method, which is deemed promising to implement other anthropometric data and further human poses.