Frequency domain approach for activity classification using accelerometer.
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
WY
Division of Computer & Information Engineering, Dongseo University, Busan 617-716, Korea. wychung@dongseo.ac.kr
Purwar
Amit
A
Sharma
Annapurna
A
D000054:Acceleration; D000465:Algorithms; D006801:Humans; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013686:Telemetry / Q000295:instrumentation*; D014159:Transducers