This paper presents a review of techniques used for biometric identification and verification based on dynamic signatures; it also shows studies on the application of nonlinear analysis in physiological processes such as signing. This review shows the need for research focused on feature extraction using nonlinear dynamic techniques, because the advantages of nonlinear analysis in biometric identification processes are unknown, and those related to the capture of the intrinsic dynamics of the process. Preliminary results of biometric identification using the SVC database show a classifier accuracy of 94.08%.