Distributed computing infrastructures provided by sensor networks supports new ways of observing human motion. In this paper, we discuss algorithms that use data from sensor networks for tracking the gait of human walk. Three methods for identifying footsteps and footstep patterns that describe a walk of a subject are discussed. The methods interpret the data into a set of coordinates that represent a trajectory of the subject?s walk. The results show that the proposed methods are more accurate and cost less than existing methods.