While interacting with computer applications, we submit an important amount of information unconsciously. By studying these implicit interactions we can better understand what characteristics of user interfaces add benefit (or not), thus deriving design implications for future systems. The main advantage of processing implicit input data from the user is that every interaction with the system can contribute to enhance its utility. Additionally, such an input removes the cost of having to interrupt the user to submit explicit information that can be little related to the purpose of using the system. On the contrary, sometimes implicit interactions do not provide clear and concrete data. As such, how this source of information is managed deserves a special attention. This research is two-fold: 1) to apply new perspectives both to the design and the development of tools that can take advantage from user's implicit interactions, and 2) provide researchers with a series of evaluation methodologies of interactive systems that are ruled by such implicit input methods. Five scenarios are discussed to illustrate the feasibility and suitability of this thesis framework. Empirical results with real users show that tapping implicit interactions is a useful asset to enhance computer systems in a variety of ways.