This paper seeks to explore an alternative and more embedded-oriented approach to the recognition of a person's motion and pose, using sensor types that can easily be distributed in clothing. A large proportion of this type of research so far has been carried out with carefully positioned accelerometers, resulting in fairly good recognition rates. An alternative approach targets a more pervasive sensing vision where the clothing is saturated with small, embedded sensors. By increasing the quantity of sensors, while decreasing their individual information quality, a preliminary comparative study between the two approaches looks at the pros, cons, and differences in algorithm requirements.