| Literature DB >> 19162860 |
Wan-Young Chung1, Amit Purwar, Annapurna Sharma.
Abstract
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.Entities:
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Year: 2008 PMID: 19162860 DOI: 10.1109/IEMBS.2008.4649357
Source DB: PubMed Journal: Conf Proc IEEE Eng Med Biol Soc ISSN: 1557-170X