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An overview of human activity recognition based on smartphone

Guan Yuan (School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China and School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, China and Department of Computer Science and Engineering, University at Buffalo, Buffalo, New York, USA)
Zhaohui Wang (School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China)
Fanrong Meng (School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China)
Qiuyan Yan (School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China)
Shixiong Xia (School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China)

Sensor Review

ISSN: 0260-2288

Article publication date: 16 October 2018

Issue publication date: 18 March 2019

724

Abstract

Purpose

Currently, ubiquitous smartphones embedded with various sensors provide a convenient way to collect raw sequence data. These data bridges the gap between human activity and multiple sensors. Human activity recognition has been widely used in quite a lot of aspects in our daily life, such as medical security, personal safety, living assistance and so on.

Design/methodology/approach

To provide an overview, the authors survey and summarize some important technologies and involved key issues of human activity recognition, including activity categorization, feature engineering as well as typical algorithms presented in recent years. In this paper, the authors first introduce the character of embedded sensors and dsiscuss their features, as well as survey some data labeling strategies to get ground truth label. Then, following the process of human activity recognition, the authors discuss the methods and techniques of raw data preprocessing and feature extraction, and summarize some popular algorithms used in model training and activity recognizing. Third, they introduce some interesting application scenarios of human activity recognition and provide some available data sets as ground truth data to validate proposed algorithms.

Findings

The authors summarize their viewpoints on human activity recognition, discuss the main challenges and point out some potential research directions.

Originality/value

It is hoped that this work will serve as the steppingstone for those interested in advancing human activity recognition.

Keywords

Acknowledgements

This work was supported by the National Natural Science Foundation of China (with grants of 71774159 and U1610124), the State’s Key Project of Research and Development Plan (with grant of 2016YFC0600908), the Fundamental Research Funds for the Central Universities, China (with grant of 2015XKMS085). Guan Yuan and Zhaohui Wang have contributed equally to this paper.

Disclosure statement: No potential conflict of interest was reported by the authors.

Citation

Yuan, G., Wang, Z., Meng, F., Yan, Q. and Xia, S. (2019), "An overview of human activity recognition based on smartphone", Sensor Review, Vol. 39 No. 2, pp. 288-306. https://doi.org/10.1108/SR-11-2017-0245

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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