Yafeng Yin’s research group has recently made new advancements in the field of human activity recognition. They systematically analyze the research progress of mobile device-based human activity recognition technology for the first time, from the perspective of research challenges, research status, research trends, open issues, and so on. The research can increase people’s attention to the field of human activity recognition and promote further research in this area.

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

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 research work, they review the research of HAR based on mobile devices, aiming to advance the following research in this area. Firstly, they give an overview of HAR based on mobile devices, including the general rationales, main components and challenges. Secondly, they 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, they present some promising trends in HAR based on mobile devices for future research.

This research work has been published in IEEE Communications Surveys and Tutorials, which is one of the top journals in the field of communications, with an impact factor of 35.6, and this is the journal with the highest impact factor in IEEE. Academic peers interested in this research are welcome to contact us for further discussions: yafeng@nju.edu.cn.