ABSTRACT
Recent research has demonstrated the feasibility of detecting human respiration rate non-intrusively using commodity WiFi devices. However, it is not always possible to sense human respiration when a subject is in different locations or faces different orientations. In this demo, we will show how a centimeter-scale position change affects the respiration detection performance. Counter-intuitively, when a subject is moving closer to the LoS, the performance of respiration sensing is not always getting better. In fact, the detectable and undetectable regions are determined by the Fresnel zone model based theory developed in [7].
- Fadel Adib, Hongzi Mao, Zachary Kabelac, Dina Katabi, and Robert C Miller. 2015. Smart homes that monitor breathing and heart rate. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 837--846. Google ScholarDigital Library
- Daniel Halperin, Wenjun Hu, Anmol Sheth, and David Wetherall. 2011. Tool release: Gathering 802.11 n traces with channel state information. ACM SIGCOMM Computer Communication Review 41, 1 (2011), 53--53. Google ScholarDigital Library
- Chunmei Han, Kaishun Wu, Yuxi Wang, and Lionel M Ni. 2014. WiFall: Device-free fall detection by wireless networks. In IEEE INFOCOM 2014-IEEE Conference on Computer Communications. IEEE, 271--279.Google ScholarCross Ref
- Jian Liu, Yan Wang, Yingying Chen, Jie Yang, Xu Chen, and Jerry Cheng. 2015. Tracking Vital Signs During Sleep Leveraging Off-the-shelf WiFi. In Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing. ACM, 267--276. Google ScholarDigital Library
- Xuefeng Liu, Jiannong Cao, Shaojie Tang, and Jiaqi Wen. 2014. Wi-Sleep: Contactless sleep monitoring via WiFi signals. In Real-Time Systems Symposium (RTSS), 2014 IEEE. IEEE, 346--355.Google ScholarCross Ref
- Xuefeng Liu, Jiannong Cao, Shaojie Tang, Jiaqi Wen, and Peng Guo. 2016. Contactless Respiration Monitoring via WiFi Signals. Mobile Computing, IEEE Transactions on (2016).Google Scholar
- Hao Wang, Daqing Zhang, Junyi Ma, Yasha Wang, Yuxiang Wang, Dan Wu, Tao Gu, and Bing Xie. 2016a. Human Respiration Detection with Commodity WiFi Devices: Do User Location and Body Orientation Matter? International conference on Ubiquitous computing (2016). Google ScholarDigital Library
- Hao Wang, Daqing Zhang, Yasha Wang, Junyi Ma, Yuxiang Wang, and Shengjie Li. 2016b. RT-Fall: A Real-time and Contactless Fall Detection System with Commodity WiFi Devices. Mobile Computing, IEEE Transactions (2016).Google Scholar
- Chenshu Wu, Zheng Yang, Zimu Zhou, Xuefeng Liu, Yunhao Liu, and Jiannong Cao. 2015. Non-Invasive Detection of Moving and Stationary Human With WiFi. Selected Areas in Communications, IEEE Journal on 33, 11 (2015), 2329--2342.Google Scholar
- Daqing Zhang, Hao Wang, Yasha Wang, and Junyi Ma. 2015. Anti-fall: A non-intrusive and real-time fall detector leveraging csi from commodity wifi devices. In International Conference on Smart Homes and Health Telematics. Springer, 181--193.Google ScholarCross Ref
Index Terms
- When can we detect human respiration with commodity wifi devices?
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