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Recent work has revealed the sensing theory of human respiration outside the First Fresnel Zone (FFZ) using commodity Wi-Fi devices. However, there is still no theoretical model to guide human respiration detection when the subject locates in the FFZ. In our work [10], we propose a diffraction-based sensing model to investigate how to effectively sense human respiration in FFZ. We present this demo system to show human respiration sensing performance varies based on different human locations and postures. By deploying the respiration detection system using COTS Wi-Fi devices, we can observe that the respiration sensing results match the theoretical model well.