An Activity Recognition Algorithm Based on Energy Expenditure Model

DOI

10.2991/icmra-15.2015.193How to use a DOI?

Keywords

Energy Expenditure; Fast Fourier Transform (FFT); Discrete Wavelet Transform (DWT); triaxial accelerometer

Abstract

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.

Copyright

© 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/).

Download article (PDF)

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  - 10.2991/icmra-15.2015.193
ID  - Zheng2015/04
ER  -