A Systematic Review of Human Activity Recognition Based on Mobile Devices: Overview, Progress and Trends

被引:25
作者
Yin, Yafeng [1 ]
Xie, Lei [1 ]
Jiang, Zhiwei [1 ]
Xiao, Fu [2 ]
Cao, Jiannong [3 ]
Lu, Sanglu [1 ]
机构
[1] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210023, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Sch Comp Sci, Nanjing 210023, Peoples R China
[3] Hong Kong Polytech Univ, Dept Comp, Hong Kong, Peoples R China
关键词
Human activity recognition; Mobile handsets; Servers; Wireless fidelity; Cameras; Sensors; Image recognition; mobile devices; human activities; sensor data; data preprocessing; recognition approaches; evaluation standards; application cases; NEURAL-NETWORK; MULTI-TOUCH; AUTHENTICATION; SMARTPHONES; MOTION; SENSORS; INPUT;
D O I
10.1109/COMST.2024.3357591
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to the ever-growing powers in sensing, computing, communicating and storing, mobile devices (e.g., smartphone, smartwatch, smart glasses) become ubiquitous and an indispensable part of people's daily life. Until now, mobile devices have been adopted in many applications, e.g., exercise assessment, daily life monitoring, human-computer interactions, user authentication, etc. Among the various applications, Human Activity Recognition (HAR) is the core technology behind them. Specifically, HAR gets the sensor data corresponding to human activities based on the built-in sensors of mobile devices, and then adopts suitable recognition approaches to infer the type of activity based on sensor data. The last two decades have witnessed the ever-increasing research in HAR. However, new challenges and opportunities are emerging, especially for HAR based on mobile devices. Therefore, in this paper, we review the research of HAR based on mobile devices, aiming to advance the following research in this area. Firstly, we give an overview of HAR based on mobile devices, including the general rationales, main components and challenges. Secondly, we review and analyze the research progress of HAR based on mobile devices from each main aspect, including human activities, sensor data, data preprocessing, recognition approaches, evaluation standards and application cases. Finally, we present some promising trends in HAR based on mobile devices for future research.
引用
收藏
页码:890 / 929
页数:40
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