Computer Science – Emerging Technologies
Scientific paper
2011-07-22
Computer Science
Emerging Technologies
30th Annual International IEEE EMBS Conference, Vancouver, British Columbia, Canada, August 20-24, 2008
Scientific paper
10.1109/IEMBS.2008.4649357
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.
Chung Wan-Young
Purwar Amit
Sharma Annapurna
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