A biometric system recognizes users based on the way they physically interact with the system. In this work, we discover a common behavior that a typist consistently displays in non-trivial computer work. We sought to demonstrate three objectives: first, compelling proof that a user can be actively recognized over the course of a lengthy task via a neutral posture struck multiple times in that task; two, a sensing concept for capturing the neutral posture, and, third, an objective method for determine the level of work performed by each typist. This thesis develops a model for hand tracking using a simple ellipse to describe the neutral posture where a typist pauses before typing. Initial results of a group of 10 users indicate that the neutral posture can be established with only a few seconds of training data and can perform with approximately 92.1% accuracy. Analysis of the typed text determined the complexity of the typists' work using Bloom's Taxonomy - a taxonomy based on verb usage; parsed verb phrases indicated the level of competency that the users endeavored to demonstrate. This competency or expertise may further distinguish users and their performance in their most engaging work.