한국정보통신학회:학술대회논문집 (Proceedings of the Korean Institute of Information and Commucation Sciences Conference)
- 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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- Pages.229-232
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- 2008
Human activity classification using Neural Network
- Sharma, Annapurna (Graduate School of Design & IT, Dongseo University) ;
- Lee, Young-Dong (Graduate School of Design & IT, Dongseo University) ;
- Chung, Wan-Young (Division of Computer & Information Engineering, Dongseo University)
- 발행 : 2008.05.30
초록
A Neural network classification of human activity data is presented. The data acquisition system involves a tri-axial accelerometer in wireless sensor network environment. The wireless ad-hoc system has the advantage of small size, convenience for wearability and cost effectiveness. The system can further improve the range of user mobility with the inclusion of ad-hoc environment. The classification is based on the frequencies of the involved activities. The most significant Fast Fourier coefficients, of the acceleration of the body movement, are used for classification of the daily activities like, Rest walk and Run. A supervised learning approach is used. The work presents classification accuracy with the available fast batch training algorithms i.e. Levenberg-Marquardt and Resilient back propagation scheme is used for training and calculation of accuracy.