DocumentCode
3064753
Title
Frequency domain approach for activity classification using accelerometer
Author
Chung, Wan-Young ; Purwar, Amit ; Sharma, Annapurna
Author_Institution
Division of Computer & Information Engineering, Dongseo University, Busan 617-716, Korea
fYear
2008
fDate
20-25 Aug. 2008
Firstpage
1120
Lastpage
1123
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.
Keywords
Acceleration; Accelerometers; Base stations; Frequency domain analysis; Legged locomotion; Micromechanical devices; Performance analysis; Performance evaluation; Testing; Wireless sensor networks; Acceleration; Algorithms; Humans; Monitoring, Physiologic; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Telemetry; Transducers;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location
Vancouver, BC
ISSN
1557-170X
Print_ISBN
978-1-4244-1814-5
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2008.4649357
Filename
4649357
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