[1] Wang Y, Wu K, Ni L M. WiFall: device-Free fall detection by wireless networks[J]. IEEE Trans on Mobile Computing, 2017, 16(2):581-594
[2] Wang Y, Liu J, Chen Y, et al. E-eyes:Device-free location-oriented activity identification using fine-grained WiFi signatures[C]// Proc of Int Conf on Mobile Computing and Networking. New York: ACM, 2014:617-628
[3] Ali K, Liu A X, Wang W, et al. Keystroke recognition using WiFi signals[C]// Proc of Inte Conf on Mobile Computing & Networking. New York: ACM, 2015:90-102
[4] Halperin D, Hu W, Sheth A, et al. Tool release:gathering 802.11n traces with channel state information[J]. ACM SIGCOMM Computer Communication Review, 2011, 41(1):53-53
[5] Adib F, Kabelac Z, Katabi D, et al. 3d tracking via body radio reflections[C]// Proc of the 11th USENIX Symp on Networked Systems Design and Implementation. Berkeley: USENIX, 2014:317-329
[6] Kellogg B, Talla V, Gollakota S. Bringing gesture recognition to all devices[C]// Proc of USENIX Conf on Networked Systems Design and Implementation. Berkeley: USENIX, 2014:303-316
[7] Seifeldin M, Youssef M. A deterministic large-scale device-free passive localization system for wireless environments[C]// Proc of Int Conf on Pervasive Technologies Related to Assistive Environments. Piscataway, NJ: IEEE, 2010:1-8
[8] Sigg S, Shi S, Buesching F, et al. Leveraging RF-channel fluctuation for activity recognition: Active and passive systems, continuous and RSSI-based signal features[M]// Earth Observation of Global Change. 2013:109-14
[9] Wang G, Zou Y, Zhou Z, et al. We can hear you with Wi-Fi![C]// Proc of Int Conf on Mobile Computing and Networking. New York: ACM, 2014:593-604
[10] Zheng X, Wang J, Shangguan L, et al. Smokey: Ubiquitous smoking detection with commercial WiFi infrastructures[C]//Proc of IEEE Int Confrence on Computer Communications. Piscataway, NJ: IEEE, 2016:1-9
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