  This work presents, the classification of user activities such as Rest, Walk
and Run, on the basis of frequency component present in the acceleration data
in a wireless sensor network environment. As the frequencies of the above
mentioned activities differ slightly for different person, so it gives a more
accurate result. The algorithm uses just one parameter i.e. the frequency of
the body acceleration data of the three axes for classifying the activities in
a set of data. The algorithm includes a normalization step and hence there is
no need to set a different value of threshold value for magnitude for different
test person. The classification is automatic and done on a block by block
basis.
