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In the last decade, many studies have significantly pushed the limits ofwireless device-free human sensing (WDHS) technology and facilitated various applications, ranging from activity identification to vital sign monitoring. This survey presents a novel taxonomy that classifies the state-of-the-art WDHS systems into eleven categories according to theirsensing task type and motiongranularity . In particular, existing WDHS systems involve three primary sensing task types. The first type,behavior recognition , is a classification problem of recognizing predefined meaningful behaviors. The second type ismovement tracking , monitoring the quantitative values of behavior states integrating with spatiotemporal information. The third type,user identification , leverages the unique features in behaviors to identify who performs the movements. The selected papers in each sensing task type can be further divided into sub-categories according to their motion granularity. Recent advances reveal that WDHS systems within a particular granularity follow similar challenges and design principles. For example, fine-grained hand recognition systems target extracting subtle motion-induced signal changes from the noisy signal responses, and their sensing areas are limited to a relative small range. Coarse-grained activity identification systems need to overcome the interference of other moving objects within the room-level sensing range. A novel research framework is proposed to help to summarize WDHS systems from methodology, evaluation performance, and design goals. Finally, we conclude with several open issues and present the future research directions from the perspectives ofdata collection ,sensing methodology ,performance evaluation , andapplication scenario .

A Survey on Wireless Device-free Human Sensing: Application Scenarios, Current Solutions, and Open Issues