WiFi connection signal is everywhere. Homes, offices, non-residential premises, public spaces… If there was a map showing the presence of wireless connections (whether public or private networks), it is clear to me that in many regions you would not see the surface. Reinventing a classic saying, a squirrel could cross Spain these days, hopping from router to router without ever touching the ground.

WiFi connectivity has changed our lives, yes, but it’s also true that we also have a significant impact on the wireless signal. Our bodies and everything connected to them affects signal distribution. Let’s not forget that we are ultimately talking about electromagnetic waves that cross space, reflect, are affected by obstacles (and human beings can also fall into that category in this case), etc.

This occurrence is well-known and generally not considered because it does not affect the quality of the signal. Our cell phone can connect to the router without any problems even when we are between two devices, even when the air is full of the cigarettes we smoke, even when the seasonal cold makes us constantly cough… in short, he could actually say that a signal or a twitch with our presence.

But in reality it is not, the truth is that it is, and the most interesting thing is that very interesting data can be extracted from the said occurrence. The most recent example of this can be found in Engadget, which reflects an investigation by the US National Institute of Standards and Technology (NIST), the entity that developed an algorithm called BreatheSmart that is able to detect respiratory problems by analyzing WiFi connection traffic. And no, when I’m talking about traffic, I’m not talking about the websites you visit, I’m talking about the data connection between the router and other devices.

BreatheSmart is compatible with common routers and is based on Channel State Information (CSI), a commonly performed set of measurements that analyzes the connection between a router and devices and extracts values ​​such as dispersion, attenuation and power loss over distance. To obtain the necessary volume of investigation, the researchers forced the router to retrieve this information up to 10 times per second.

They then used a dummy capable of reproducing different respiratory patterns and verified their occurrence in CSI WiFi connectivity measurements, which allowed them to verify not only that the user’s occurrence is real, but also that it varies substantially depending on whether we breathe one way or the other, so this analysis of information can become an indicator of possible respiratory problems.