An Activity Recognition Algorithm Based on Energy Expenditure Model
- https://doi.org/10.2991/icmra-15.2015.193How to use a DOI?
- Energy Expenditure; Fast Fourier Transform (FFT); Discrete Wavelet Transform (DWT); triaxial accelerometer
Human activity recognition via triaxial accelerometers can provide valuable information to evaluate functional abilities. In this paper, we present an accelerometer sensor-based approach for human activity recognition. Our proposed recognition method uses a model of Activity Energy Expenditure to recognize six activities. The classifier utilizes Fast Fourier transform (FFT) and Discrete Wavelet Transform (DWT) algorithms to get energy expenditures of different activities. Every activity is recognized by the max amplitude and its frequency, 1-D decomposition energy of triaxial accelerometer signals. This activity recognition method can recognize six activities with an average accuracy of 90% using only a single triaxial.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yuhuang Zheng PY - 2015/04 DA - 2015/04 TI - An Activity Recognition Algorithm Based on Energy Expenditure Model BT - Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation PB - Atlantis Press SP - 995 EP - 998 SN - 2352-538X UR - https://doi.org/10.2991/icmra-15.2015.193 DO - https://doi.org/10.2991/icmra-15.2015.193 ID - Zheng2015/04 ER -