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DOI: 10.14569/IJACSA.2019.0100311
PDF

Survey on Human Activity Recognition based on Acceleration Data

Author 1: Salwa O. Slim
Author 2: Ayman Atia
Author 3: Marwa M.A. Elfattah
Author 4: Mostafa-Sami M.Mostafa

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 3, 2019.

  • Abstract and Keywords
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Abstract: Human activity recognition is an important area of machine learning research as it has many utilization in different areas such as sports training, security, entertainment, ambient-assisted living, and health monitoring and management. Studying human activity recognition shows that researchers are interested mostly in the daily activities of the human. Therefore, the general architecture of HAR system is presented in this paper, along with the description of its main components. The state of the art in human activity recognition based on accelerometer is surveyed. According to this survey, Most of the researches recently used deep learning for recognizing HAR, but they focused on CNN even though there are other deep learning types achieved a satisfied accuracy. The paper displays a two-level taxonomy in accordance with machine learning approach (either traditional or deep learning) and the processing mode (either online or offline). Forty eight studies are compared in terms of recognition accuracy, classifier, activities types, and used devices. Finally, the paper concludes different challenges and issues online versus offline also using deep learning versus traditional machine learning for human activity recognition based on accelerometer sensors.

Keywords: Human activity recognition; accelerometer; online system; offline system; traditional machine learning; deep learning

Salwa O. Slim, Ayman Atia, Marwa M.A. Elfattah and Mostafa-Sami M.Mostafa, “Survey on Human Activity Recognition based on Acceleration Data” International Journal of Advanced Computer Science and Applications(IJACSA), 10(3), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100311

@article{Slim2019,
title = {Survey on Human Activity Recognition based on Acceleration Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100311},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100311},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {3},
author = {Salwa O. Slim and Ayman Atia and Marwa M.A. Elfattah and Mostafa-Sami M.Mostafa}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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