  Activity classification was performed using MEMS accelerometer and wireless
sensor node for wireless sensor network environment. Three axes MEMS
accelerometer measures body's acceleration and transmits measured data with the
help of sensor node to base station attached to PC. On the PC, real time
accelerometer data is processed for movement classifications. In this paper,
Rest, walking and running are the classified activities of the person. Both
time and frequency analysis was performed to classify running and walking. The
classification of rest and movement is done using Signal magnitude area (SMA).
The classification accuracy for rest and movement is 100%. For the
classification of walk and Run two parameters i.e. SMA and Median frequency
were used. The classification accuracy for walk and running was detected as
81.25% in the experiments performed by the test persons.
