Optimization-Based Seated Posture Prediction Considering Contact With Environment

People can spend much of everyday completing seated tasks. Therefore it is important to understand postures needed to complete seated tasks, and the associated environmental contacts. This paper presents a method to predict seated postures and the general forces needed in order to support resulting postural configurations. This study uses optimization techniques to predict human posture based on a 56 degree of freedom (DOF) 50^th percentile female human model. The support reaction forces (SRFs) are predicted using joint torques and the zero-moment point (ZMP) formulation derived from the Lagrangian recursive dynamics. The SRFs are applied at points on the body based on center of pressure (COP) locations gathered from pressure mapping experiments. The specific application points include the two feet, the two thighs, and back. Multiple seated orientations based on an experimental study found in published literature are simulated. When comparing these simulation results to the literature data, a good correlation can be established, which provides an initial validation of the proposed methods.