  The ever evolving informatics technology has gradually bounded human and
computer in a compact way. Understanding user behavior becomes a key enabler in
many fields such as sedentary-related healthcare, human-computer interaction
(HCI) and affective computing. Traditional sensor-based and vision-based user
behavior analysis approaches are obtrusive in general, hindering their usage in
realworld. Therefore, in this article, we first introduce WiFi signal as a new
source instead of sensor and vision for unobtrusive user behaviors analysis.
Then we design BeSense, a contactless behavior analysis system leveraging
signal processing and computational intelligence over WiFi channel state
information (CSI). We prototype BeSense on commodity low-cost WiFi devices and
evaluate its performance in realworld environments. Experimental results have
verified its effectiveness in recognizing user behaviors.
