Bodily expression of felt emotion has been documented in the literature. However, it is often associated with high motor variability between individuals. This study aimed to identify individual motor signature (IMS) of emotions. IMS is a new method of motion analysis and visualization able to capture the subtle differences in the way each of us moves, seen as a kinematic fingerprint. We hypothesized that the individual motor signature would be different depending on the induced emotional state and that an emotional motor signature of joy and sadness common to all participants would emerge. For that purpose, we elicited these emotions (joy, sadness, and a neutral control emotion) in 26 individuals using an autobiographical memory paradigm, before they performed a motor improvization task (e.g., the mirror game). We extracted the individual motor signature under each emotional condition. Participants completed a self-report emotion before and after each trial. Comparing the similarity indexes of intra- and inter-emotional condition signatures, we confirmed our hypothesis and showed the existence of a specific motor signature for joy and sadness, allowing us to introduce the notion of emotional individual motor signature (EIMS). Our study indicates that EIMS can reinforce emotion discrimination and constitutes the first step in modeling emotional behavior during individual task performances or social interactions.