This chapter presents a novel framework for dynamic biometric monitoring of behaviour towards user authentication, utilizing dynamic and static anthropometric information. The recognition of the performed activity is based on Generalized Radon transforms that are applied on spatiotemporal motion templates. User authentication is performed exploiting the behavioural variations between different users, regardless of small variations in the interaction setting. The upper body limb anthropometric information is extracted for each user and an attributed body-related graph structure framework is employed for the detection of static biometric features of important discrimination power. Finally, a quality factor based on ergonomic criteria evaluates the recognition capacity of each activity. Experimental validation illustrates that the proposed approach for integrating static anthropometric features and activity-related recognition, advances significantly the authentication performance. In this concept, a series of possible applications of the proposed system is also presented.