The representation of self reported affect in body posture and body posture simulation

It is taken for granted that the non-verbal information we acquire from a person's body posture and position affects our perception of others. However, to date human postures have never been described on an empirical level. This study is the first approach to tackle the unexplored topic of human postures. We combined two approaches: traditional behavior observation and modern anthropometric analysis. Photographs of 100 participants were taken, their body postures were transferred to a three dimensional virtual environment and the occurring body angles were measured. The participants were asked to fill in a questionnaire about their current affective state. A principal component analysis with the items of the affect questionnaire (Positive Negative Affect Scales, PANAS) revealed five main factors: aversion, openness, irritation, happiness, and self-confidence. The body angles were then regressed on these factors and the respective postures were reconstructed within a virtual environment. 50 different subjects rated the reconstructed postures from the positive and negative end of the regression. We found the ratings to be valid and accurate in respect to the five factors.