Department of Computer Science and Technology, Ocean University of China, Qingdao 266100, China.
Sensors (Basel). 2020 Feb 22;20(4):1210. doi: 10.3390/s20041210.
Wireless networks have been widely deployed with a high demand for wireless data traffic. The ubiquitous availability of wireless signals brings new opportunities for non-intrusive human activity sensing. To enhance a thorough understanding of existing wireless sensing techniques and provide insights for future directions, this survey conducts a review of the existing research on human activity sensing with wireless signals. We review and compare existing research of wireless human activity sensing from seven perspectives, including the types of wireless signals, theoretical models, signal preprocessing techniques, activity segmentation, feature extraction, classification, and application. With the development and deployment of new wireless technology, there will be more sensing opportunities in human activities. Based on the analysis of existing research, the survey points out seven challenges on wireless human activity sensing research: robustness, non-coexistence of sensing and communications, privacy, multiple user activity sensing, limited sensing range, complex deep learning, and lack of standard datasets. Finally, this survey presents four possible future research trends, including new theoretical models, the coexistence of sensing and communications, awareness of sensing on receivers, and constructing open datasets to enable new wireless sensing opportunities on human activities.
无线网络已经得到广泛部署,对无线数据流量的需求也很高。无处不在的无线信号为非侵入式人体活动感应带来了新的机会。为了更深入地了解现有的无线感应技术,并为未来的方向提供见解,本调查对利用无线信号进行人体活动感应的现有研究进行了回顾。我们从七种视角综述和比较了现有的无线人体活动感应研究,包括无线信号的类型、理论模型、信号预处理技术、活动分割、特征提取、分类和应用。随着新的无线技术的发展和部署,将会有更多的人体活动感应机会。基于对现有研究的分析,本调查指出了无线人体活动感应研究的七个挑战:鲁棒性、感应与通信的共存、隐私、多用户活动感应、有限的感应范围、复杂的深度学习和缺乏标准数据集。最后,本调查提出了四个可能的未来研究趋势,包括新的理论模型、感应与通信的共存、对接收器上的感应的认识,以及构建开放数据集以实现新的无线人体活动感应机会。