For the past few years, there have been ongoing debates about whether people can become dependent on vaping and e-cigarettes. These devices certainly cause damage (as we’ve documented in our blogs) and, in our opinion, are wreaking havoc among younger Americans. But there hasn’t been a lot of hard data to prove (or disprove) their addictiveness. Now, though, that may change thanks to some new tech developed by engineers at Cornell University.
A group there recently helped design the PuffPacket. As mentioned in the popular gadget site Tech Crunch, PuffPacket has been gaining a lot of notoriety as of late. It is designed as a small device that can attach to an e-cigarette. From there, it begins to measure use patterns and trends via a smartphone app.
The idea would be for users to self diagnose and truly see whether or not they have a problem with vaping. The app itself is highly interactive and can analyze a lot of behavioral data, which is then sent to people’s phones.
Cornell PhD student (and co-developer) Alexander Adams spoke to Tech Crunch about the potential he sees in the PuffPacket.
“The lack of continuous and objective understanding of vaping behaviors led us to develop PuffPacket,” he explained. “The goal is to enable proper measurement, monitoring, tracking and recording of e-cigarette use, as opposed to inferring it from location and activity data, or self-reports.”
The technology is actually so advanced that it can measure physical movements related to e-cigarette use. App data can show if people smoke while sedentary, or after visiting bars or even while Instagramming. The point is to understand what habits drive people to vape and whether that behavior needs to be put in check.
We could certainly see this as a useful for other researchers as well. As described in the article, PuffPackets are quite easy to install and fit aside the mouthpiece of most e-cigarettes. It generates its data based on voltage counts and can measure how much liquid is being vaporized at any given time.
Adams emphasized that this technology can most certainly help educate people within the recovery industry.
“Getting these correlations between time of day, place and activity is important for understanding addiction,” he concluded. “Research has shown that if you can keep people away from the paths of their normal habits, it can disrupt them.”
