This work focuses on the problem of dynamic signature segmentation and representation. A brief review of segmentation techniques for online signatures and movement modelling is provided. Two dynamic signature segmentation/representation methods are proposed. These methods are based on psychophysical evidences that led to the well-known Minimum Jerk Model. These methods are alternatives to the existing techniques and are very simple to implement. Experimental evidence indicates that the Minimum Jerk is in fact a good choice for signature representation amongst the family of quadratic derivative cost functions defined in Section 2.