How much information with regard to identity and further individual participant characteristics are revealed by relatively short spatio-temporal motion trajectories of a person? We study this question by selecting a set of individual participant characteristics and analysing motion captured trajectories of an exemplary class of familiar movements, namely handover of anobject to another person. The experiment is performed with different participants under different, predefined conditions. A selection of participant characteristics, such as the Big Five personality traits, gender, weight, or sportiness, are assessed and we analyse the impact of the three factor groups “participant identity”, “participant characteristics”, and “experimental conditions” on the observed hand trajectories. The participants’ movements are recorded via optical marker-based hand motion capture. One participant, the giver, hands over an object to the receiver. The resulting time courses of three-dimensional positions of markers are analysed. Multidimensional scaling is used to project trajectories to points in a dimension-reduced feature space. Supervised learning is also applied. We find that “participant identity” seems to have the highest correlation with the trajectories, with factor group “experimental conditions” ranking second. On the other hand, it is not possible to find a correlation between the “participant characteristics” and the hand trajectory features.