Fascinating! First wearable to .....
First Wearable To Analyze Your Saliva (compliments to Ray Hammond on his future trends!)
Your spit says a lot about your health, and now there’s wearable technology being tested to track it.
Researchers at the University of California, San Diego, have demonstrated a mouth guard with electronic sensors that can detect concentrations of certain chemicals in saliva. Such a gadget could be useful to soldiers, pilots, athletes, and even hospital patients.
The group recently revealed a new sensor that can detect the concentration of uric acid—an elevated concentration of uric acid in the blood and urine has been associated with various metabolic disorders.
This is the second sensor the group has made for the mouth guard. Last year, it showed that it was possible to measure lactate—elevated concentrations of which have been associated with muscle fatigue, among other things.
The device wirelessly transmits the information it collects to a smartphone or computer via Bluetooth Low Energy, a technology that consumes much less power than classic Bluetooth.
Selfies Can Reveal Your Health!
Compliments of Ray Hammond again! I love this one! (Follow him here -- @hammondfuturist )
A team of researchers at the University of Rochester has developed a computer program that can help health professionals monitor a person`s mental health through the images from selfie videos the patient records while engaging in social media activity.
The method is a variation of existing health monitoring programs. The novelty here is that the user’s behavior. can be monitored quietly and unobtrusively while they routinely use their computer or smartphone. No extra information about how the user is feeling needs to be provided. No special accessories are required, either. The user just needs to go about their computer routine as usual.
During its experiments, the team, successfully measured a user’s heart rate simply by monitoring small changes in the patient’s forehead color. Other visual signals could be extracted, such as blinking rate, eye pupil radius and head movement rate, from the video data, all of this using modern computer vision and signal processing techniques.