This study examined the effects of obesity level, standing time and their interaction on postural sway during a prolonged quiet upright standing task. Ten extremely obese (BMI > 40 kg/m(2)) and 10 non-obese (18.5 kg/m(2) < BMI < 24.9 kg/m(2)) participants performed quiet upright standing on a force plate for over 18 min. Eleven postural sway measures were computed for each 1-min time interval based on the centre-of-pressure data from the force plate. ANOVA and regression analyses showed that for all the 11 postural sway measures, the extremely obese group had higher postural sway than the non-obese at the beginning of the prolonged standing task and postural sway increased significantly faster for the extremely obese group than the non-obese over time. The results suggest that obesity may impair postural control and may be a risk factor of balance loss and falls, especially during prolonged physical work activities. The research findings are relevant to identifying and reducing risks of balance loss and falls in various workplace settings for a wide variety of workers.

Existing posture prediction and motion simulation models generally lack the capability of simulating human obstruction avoidance during target reach. This compromises the utility of digital human models for ergonomics, as many design problems involve interactions between humans and obstructions. To address this problem, this paper presents a novel memory-based posture planning (MBPP) model, which plans reach postures that avoid obstructions. In this model, the task space is partitioned into small regions called cells. For a given human figure, each cell is linked to a memory that stores various alternative postures for reaching the cell. When a posture planning problem is given in terms of a target and an obstruction configuration, the model examines postures belonging to the relevant cell, selects collision-free ones and modifies them to exactly meet the hand target acquisition constraint. Simulation results showed that the MBPP model is capable of rapidly and robustly planning reach postures for various scenarios.